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Helicobacter pylori eradication treatment for gastric carcinoma prevention in asymptomatic or dyspeptic adults: systematic review and Bayesian meta-analysis of randomised controlled trials

Objectives Recent meta-analyses of eradication therapy in Helicobacter pylori-infected adults reported significant reductions in gastric carcinoma risk. However, concerns about supporting unfocused screening and eradication programme in healthy, asymptomatic populations have arisen. We performed a systematic review and Bayesian meta-analysis to provide an accurate interpretation of randomised evidence on the preventive effectiveness of eradication therapy on gastric carcinoma risk. Methods We searched databases including PubMed, Cochrane Central and Embase for reference and citation tracking without language restrictions, from inception through 31 July 2018. Paired investigators independently selected randomised controlled trials (RCTs) comparing eradication therapy with placebo or no treatment for asymptomatic or dyspeptic H. pylori-infected adults with no previous gastric carcinoma. The main outcome was gastric carcinoma incidence; secondary outcomes included gastric carcinoma-specific, non-gastric carcinoma and all-cause mortality. Results A total of 5 population-based and 2 outpatient care-based RCTs involving 7303 adults were eligible. Eradication algorithms were heterogeneous, and unsuccessful eradication and reinfection were frequently observed. A Bayesian meta-analysis with competing risk outcomes found low-certainty evidence that eradication therapy might be more likely than control to reduce gastric carcinoma risk (HR=0.65; 95% credible interval (CrI) 0.41 to 1.0; I2=11%). The CrIs included the null effects across the subgroup and sensitivity analyses, apart from those based on particular models that excluded two RCTs that enrolled subjects with specific histological findings only (HR=0.55; CrI 0.30 to 0.89; I2=14%). The uncertainty of the average 41% risk reduction in gastric carcinoma-specific mortality included a clinically important mortality risk increase (HR=0.59 favouring eradication therapy; CrI 0.25 to 1.20; I2=13%; low certainty). Conclusions There is insufficient evidence to support or refute the effectiveness of eradication therapy in preventing gastric carcinoma in H. pylori-infected, high-risk populations. Rigorously conducted large RCTs of healthy infected adults only would provide evidence of the true efficacy of successful eradication. PROSPERO registration number: CRD42014009245.


BACKGROUND
Gastric carcinoma is the third most common cancer-specific cause of death worldwide and the most prevalent cancer in East Asia. 1 Infection with Helicobacter pylori is a strong risk factor for gastric carcinoma. 2 Several postulated oncogenic mechanisms 3 and epidemiological evidence 4,5 supporting this association exist. Explanations for the high gastric carcinoma incidence in East Asia include environmental factors such as high sodium intake 6 and the geographically distinct predominance of H. pylori strains characterized by strain-specific polymorphisms in the cagA gene, producing a highly virulent CagA. 6,7 Since the establishment of effective eradication treatments in the 1990s, several randomized controlled trials (RCTs) have assessed whether eradicating H. pylori can reduce the risk of gastric carcinoma in healthy adults. After multiple reports of inconclusive results, with the long-term follow-up of the largest RCT that showed a significant reduction in gastric carcinoma risk in the eradication group, 8 several meta-analyses reported similar findings. [9][10][11][12] On this basis, clinical guidelines and consensus reports have consistently recommended screening and eradication of H. pylori in high-risk populations. [13][14][15][16][17][18] However, these meta-analyses had several limitations, [9][10][11] which raised concerns about supporting unfocused screening and eradication programs in healthy, asymptomatic populations. The evidence partly derived from studies focusing on patients treated for early-stage gastric carcinoma 9,11 cannot be directly applied to the general population. Also, concerns about the evidence obtained from cohort studies 9,10 include confounding and other sources of bias. 19 12 relied on data reported in conference abstracts 21 and used statistical approaches that can calculate falsely narrow confidence intervals (CIs) when the number of studies is small and events are rare. [22][23][24][25] Additionally, the sensitivity analyses used for exploring the effect of censored cases on the summary estimates were for binary outcomes, 26,27 not for time-to-event outcomes with competing risks. 28 Bayesian random-effects meta-analysis is an increasingly used flexible methodology that accounts for uncertainty by combining all available external evidence as the initial belief through the likelihood function, using new data to update the evidence. 29, 30 We conducted a systematic review and Bayesian meta-analysis to provide an accurate interpretation of the currently available evidence from RCTs on the preventive effect of H. pylori eradication on gastric carcinoma.

METHODS
This study is an updated systematic review and meta-analysis based on an evidence report that was produced for developing the Japanese Guidelines for Gastric Cancer Screening (see Supplementary Methods for details). 31 The original protocol was registered at PROSPERO (CRD42014009245).

Data Sources and Searches
We searched PubMed, the Cochrane Central Register of Controlled Trials, and Embase from inception through July 31, 2018 using search terms including "gastric cancer," "Helicobacter pylori," "eradication," and their synonyms, without language restrictions.
To supplement the search, we perused the reference lists of eligible studies and relevant

Study Selection
Paired reviewers, drawn from the group of seven investigators (TT, CH, KK, IM, TY, RT, and HN), independently screened non-overlapping sets of abstracts and full texts of potentially eligible studies. RCTs that compared eradication therapies for H. pylori with placebo or no treatment in asymptomatic or otherwise healthy, dyspeptic H. pylori-infected adults (aged ≥18 years) with no history of gastric carcinoma were eligible. We allowed for the inclusion of "otherwise healthy, dyspeptic subjects" post hoc because both uninvestigated and functional dyspepsia are common in Asia, 32

Data Extraction
One reviewer (TT) extracted trial, subject, and intervention characteristics from each eligible paper; another (KK) verified the data. If the paper with the longest follow-up period did not report the relevant information but cited earlier publications, we extracted data from the cited publications (see Supplementary Methods).
Our primary outcome was the incidence of gastric carcinoma; non-carcinoma tumors (e.g., lymphomas or sarcomas) were excluded. Our secondary outcomes were gastric carcinoma-specific mortality, non-gastric carcinoma mortality, and all-cause mortality.
Two reviewers (TT, IM) independently extracted the number of randomly allocated participants as the intention-to-treat analysis population, excluding any mistakenly enrolled ineligible subjects 26,33 as well as the numbers of gastric carcinoma events, deaths from gastric carcinoma and other causes, and censored subjects as missing outcome data (MOD) for each arm from the publications with the longest follow-up.
Censored subjects included those lost to follow-up for interim exclusion due to protocol deviation, noncompliance and withdrawal. 34 Disagreements were resolved by consensus.
For any missing information or unresolved discrepancies, we contacted the authors of the primary studies for clarification or to request unpublished data. We considered the request rejected if two emails received no response.

Assessment of Risk of Bias
Two independent reviewers (TT, TY) analyzed sequence generation; allocation concealment; blinding of participants; trial personnel and outcome assessment; incomplete outcome data; selective reporting; and other biases using the Cochrane Collaboration's Risk of Bias tool. 35 The kappa coefficient for inter-rater agreement was 0.76, indicating good agreement. 36 Disagreements were resolved by consensus.

Data Synthesis
We calculated summary hazard ratios (HRs) and their 95% credible intervals (CrIs) and prediction intervals (PrIs), 30,37 using a hierarchical Bayesian random-effects meta-analysis method for competing risk time-to-event outcomes. 38,39 For gastric carcinoma incidence, we modeled the baseline and relative hazard rates for gastric carcinoma events, non-gastric carcinoma deaths, and MOD as mutually exclusive outcomes and their respective random-effect parameters in a single analysis; we assumed that no cases of gastric carcinoma later died from a cause other than gastric carcinoma. For analyzing gastric carcinoma-specific and non-gastric carcinoma mortality, deaths from gastric carcinoma, deaths from all other causes, and MOD were simultaneously modeled. As a sensitivity analysis, we calculated summary odds ratios (ORs) for cumulative gastric carcinoma incidence as a binary outcome. For MOD and non-gastric carcinoma deaths, we applied hierarchical Bayesian random-effects meta-analytic models using the conventional deterministic analytical methods 26 and models, directly allowing for uncertainty due to missing data. 40 We used the context-specific informative prior distributions on the between-trial standard deviations (tau) in the main analysis. 41 Alternative prior distributions were explored in the sensitivity analyses. 24,39 The Supplementary Methods provide complete details of the methodologies, model fitting, choice of prior distributions for the parameters, and the operational definitions used in the sensitivity analysis.
We assessed the certainty of evidence for each outcome using the Grading of Recommendation Assessment, Development and Evaluation (GRADE) approach. 42 We quantified between-study heterogeneity using the tau and I 2 statistics with their 95% CrIs. 43 To examine how each trial affected the summary estimate of the other RCTs, we performed a leave-one-out meta-analysis by calculating summary estimates iteratively, excluding one trial at a time. 44 We did not perform the planned tests for funnel plot asymmetry because eligible studies were <10. 45 To explore clinical heterogeneity, we performed trial-level subgroup analyses and univariable meta-regressions according to outpatient), and subject selection (all invited subjects regardless of baseline gastric histology vs. those with specific histologic subtypes). 44,46 All analyses were conducted using Stata/SE 14.2 (Stata Corp, College Station, TX, USA) and WinBUGS 1.4.3 (MRC Biostatistics Unit, Cambridge, UK). P-values for all comparisons were two-tailed, and statistical significance was defined as P <0.05.

Literature Search and Eligible Studies
After abstract-level screening of the main searches, citation index searches, and citations identified from other sources, we reviewed the full texts of 42 potentially eligible published articles (Supplementary Figure 1). After exclusions and review of unpublished data provided by the authors, 7 independent RCTs reported in 16 publications were ultimately eligible. 8,[47][48][49][50][51][52][53][54][55][56][57][58][59][60][61] We excluded the long-term follow-up reports from one RCT 62,63 because of a possibility of treatment contamination due to crossover (64% of participants in the control group received eradication therapy after 6 years of follow-up). The Supplementary Results provide full details of the study selection and excluded studies.

Study and Clinical Characteristics
The seven RCTs-five from China, 8,47,55,56,61 one from Japan, 60 12 participants with dyspeptic symptoms in addition to asymptomatic subjects. The other trials, three population-based 8,56,58 and one outpatient care-based RCT, 61 did not report on symptoms at enrollment. One RCT diagnosed H. pylori infection by serologic testing only. 8 Four trials used a parallel design, 47,55,60,61 whereas the other three adopted factorial designs with co-interventions of vitamins; 58 vitamins, selenium, and garlic extract; 8 or celecoxib, a cyclooxygenase-2 inhibitor. 56 Two RCTs focused on populations with specific precancerous lesions based on pre-enrollment histology results. 56,58 The follow-up duration extended beyond 10 years in only 2 trials. 8,55 Gastric carcinoma incidence was the primary outcome in only one RCT. 47 Another long-term follow-up report from the largest trial cohort reported gastric carcinoma as the post hoc primary outcome. 8 No trials defined gastric carcinoma-specific mortality or all-cause mortality as their primary outcomes before conducting the study. Methods used to confirm the outcomes were non-uniform. Four RCTs periodically performed endoscopic gastric surveys with biopsies of multiple sites; 8,55,58,60 the other three scheduled similar routine gastric surveys only once. 47,56,61 Three trials also examined patients' clinical records, the regional cancer registry, and/or death certificates to identify gastric carcinoma cases and death events. 8,47,56 The sample sizes ranged from 236 to 2,258 (median, 852) subjects with an average age of 42 to 53 years (Supplementary Table 2). Pre-cancerous gastric lesions at enrollment varied across trials; one trial that enrolled subjects with advanced gastric lesions reported gastric dysplasia in 54% of the participants. 56 The adopted eradication algorithms also varied. Two trials repeated first-line therapy for non-responders, 8 13 provided no salvage therapy, 55,56 and one employed dual combination therapy. 8 While the post-treatment eradication rates assessed at 1-72 months ranged from 72% to 89%, follow-up eradication rates at 7 to 12 years were approximately 50%, suggesting recurrence or re-infection. 8,55,62 The baseline incidence of gastric carcinoma ranged from 107 to 1,802 per 100,000 person-years. The two RCTs of populations with specific histologic findings reported the lowest and second lowest incident rates. 56,58 Gastric carcinoma events were missing in 565 (15%) and 543 (15%) participants in the eradication and control arms, respectively.

Assessment of Risk of Bias
Overall, only one RCT, a long-term follow-up report of the largest trial, 8 Table 3). Only two RCTs used the proportional hazard model to analyze time-to-event outcomes-one for gastric carcinoma incidence, 56 the other for mortality. 8

Incidence of Gastric Carcinoma
A total of 7 RCTs, including 7,303 adults, observed 138 gastric carcinoma events (Table   1). They failed to observe the primary outcome in 369 subjects who died from non-gastric carcinoma causes and in 649 subjects with MOD. Although the summary estimates showed a 35% risk reduction for gastric carcinoma associated with eradication therapy, the upper limit of the 95% CrI included 1, the null effect, suggesting no average

Gastric Carcinoma-Specific Mortality
A total of 3 community-based RCTs (4,400 adults) provided data on deaths from gastric carcinoma ( Table 1). While the CrI for the pooled effect crossed 1, the plausible effects suggest both a clinically important mortality benefit of 75% and risk increase of 20% (HR=0. 59 26; low certainty) ( Figure 1). Concerns about precision due to the wide CrIs and indirectness due to the adoption of inadequate eradication strategies downgraded certainty.

All-Cause Mortality and Non-Gastric Carcinoma Mortality
A total of 5 community-based RCTs (6,316 adults) contributed data on deaths from all and non-gastric carcinoma causes (Table 1) 16; low certainty) ( Figure 1). Certainty was down-rated because of the wide CrIs that included a clinically important mortality benefit and increase.

Subgroup Analysis
The subgroup meta-analysis for trials conducted in East Asia found an average reduction in gastric carcinoma risk of 38% ( Table 4).
The meta-regression analyses showed no differential effects by geographic location, research setting, or subject selection.

Sensitivity Analysis
For gastric carcinoma incidence, the CrIs for the summary HRs generally became wider, with the upper limit crossing 1, when alternative, less informative priors for tau were specified except for the subgroup analysis where the 2 trials of populations with specific histologic findings were excluded (Supplementary Table 4). Similarly, the CrIs crossed 1, unless 1 of 2 RCTs for histologically selected populations was excluded in the leave-one-out meta-analysis (Supplementary Figure 3). In the sensitivity analyses using the conventional Bayesian meta-analysis for binary outcomes, the summary ORs were generally congruent to the summary HRs of the main analysis. However, the CrIs were consistently wider and crossed 1, regardless of the prior distributions for tau, the use of deterministic analytical approaches or models directly accounting for uncertainty to account for MOD, or exclusion of non-gastric carcinoma deaths from MOD (Supplementary Table 5). The summary HRs for the mortality outcomes were not  Table 4).

Main findings
Our meta-analysis found no preventive effects of H. pylori eradication treatment on the risk of gastric carcinoma development overall. This finding was generally consistent across subgroup and sensitivity analyses except when two factorial design trials that focused on enrollees with specific histologic findings were excluded. Although we calculated a similar average effect size, our wide CrIs were not congruent with those of previous meta-analyses including the Cochrane meta-analysis that reported that H. pylori eradication significantly reduced gastric carcinoma risk. 12 This highlights the uncertainty surrounding the effectiveness of unfocused test-and-eradicate programs, even in high-risk regions. A recently published fixed-effects meta-analysis using risk difference as the outcome measure, although naïvely conducted, reported a non-significant risk reduction associated with eradication therapy, which raised concerns about the conclusions from previous meta-analyses. 64 The results of our Bayesian meta-analysis corroborate this finding.
The preventive effects became larger and significant-an average of 45% risk reduction-when the two factorial design trials that selected more histologically advanced lesions were excluded. This suggests that eradication therapy may be more effective in non-focused, potentially lower-risk populations; this is in line with the meta-analysis of a subgroup from the primary prevention RCTs conducted by Chen et al. 11 The fixed-effects meta-analysis of subjects with better pre-eradication histology than intestinal metaplasia or dysplasia only, comprising only one case who developed gastric carcinoma out of 1,221 subjects in the eradication group versus 10 cases out of 1,228 in the control group, although the balance between the two groups created from randomization might no longer hold, reported a significant 78% risk reduction (relative risk=0. 22 [95% CI, 0.06 to 0.86]). However, the severity of the baseline precancerous lesions across the trials could not directly be compared due to variations including the histologic criteria used. Further, baseline histology may not necessarily be the sole risk for gastric carcinoma events, given the lowest baseline incidence rates in the two factorial RCTs of "high-risk" populations. For example, given the subjective nature of endoscopic evaluation in particular, "missed" cases of gastric carcinoma at enrollment and/or during the follow-up rounds are always a concern affecting the validity of gastric carcinoma research. 65 Therefore, our observation based on subgroup analysis should be viewed as hypothesis generation.
We found that evidence on gastric carcinoma-specific and overall mortality was insufficient because the RCTs were not powered to detect differences in these outcomes.
The wide CrIs for the average effect suggest that while a clinically meaningful 75% reduction in gastric carcinoma-specific mortality is possible, a 20% increase cannot be ruled out.
Our meta-analysis has several strengths. We employed Bayesian approaches to account for multiple time-to-event outcomes with competing risks and frequent censored observations. Our literature search found one RCT 61 that previous meta-analyses had failed to include. We also utilized data extracted from full-text publications and obtained unpublished data from two RCTs, 55,60 for which previous meta-analyses had relied on the data presented in conference abstracts 9,12 or earlier short-term reports. 11 These additional data allowed us to perform a more comprehensive analysis than was possible in previous meta-analyses that focused on RCTs only 11,12,64 regarding across-trial differences in research settings, patient symptoms at enrollment, missing outcomes, and mortality events.

Limitations
Limitations of the included RCTs other than short, incomplete follow-ups, need to be noted. The RCTs employed potentially sub-optimal eradication algorithms and reported frequent rates of recurrence or reinfection. These unsuccessful eradication attempts could have affected the preventive effect. In addition, as already noted, inclusion of RCTs that allowed for the inclusion of subjects with advanced pre-neoplastic lesions, those at high risk for progression to gastric carcinoma, 13 might have attenuated the preventive effects. Moreover, interactions with concurrent interventions, regardless of their directions, cannot be ruled out in the three factorial design trials. Similar to previous meta-analyses, 11,12,64 our Bayesian meta-analysis could not address these limitations analytically without access to individual-level data.
In the meta-analysis of gastric carcinoma incidence, our assumption that those who developed gastric carcinoma would not die from causes other than gastric carcinoma should be clinically acceptable. Nevertheless, more accurate analysis would require individual-level data or modeling with additional assumptions for the conditional risk of non-gastric carcinoma deaths.

Implications
Given the insufficient randomized evidence, rigorously conducted large RCTs adopting stringent research methodologies would be ideal if demonstration of the true efficacy of eradication therapy is the central issue. This context would include the use of more effective eradication strategies, including accurate response assessment, better salvage therapies, and meticulous longer-term follow-up. Implementation of high-quality pre-enrollment gastric survey, including the strict exclusion of subjects who already have pre-neoplastic lesions, would be particularly relevant if healthy subjects are truly targeted. Nevertheless, challenges exist when conducting de novo long-term large high-quality RCTs of rare outcomes. Hence, the analysis of the current trends utilizing large, clinical, practice-based registries is a realistic primary research option. If feasible, conducting individual-level consortia meta-analysis of all existing RCTs remains a viable option to repurpose the already available resources. Exploring effect modifiers for identifying subgroups that benefit most (or least) from the eradication strategy should be the highest priority. 37 Further, we should not ignore all-cause and gastric carcinoma-specific mortality and long-term adverse events as important outcomes attributable to eradication.
In conclusion, there is insufficient randomized evidence to support or refute the effectiveness of eradication therapy in preventing gastric carcinoma in H.

Competing interests
All authors declare no conflicts of interest associated with this publication.
For complete transparency, TY reports taking grants and personal fees from Chugai Pharmaceutical Co., grants and personal fees from Taiho Pharmaceutical, grants and personal fees from Yakult, personal fees from Lilly, grants from Novartis, personal fees from Ono, personal fees from Takeda, personal fees from Nippon Kayaku Co. Ltd., personal fees from Covidien, personal fees from Johnson and Johnson, personal fees from Olympus, personal fees from NPO Epidemiological and Clinical Research Information Network, personal fees from NPO KSATTS, and personal fees from NPO Cancer Net Japan, outside the submitted work.

Ethics approval and consent to participate
Not required.

Patient consent
Not required.

Study Selection
We modified the original inclusion criterion of "healthy adults" after perusing full-text articles to allow the inclusion of otherwise generally healthy subjects with gastric symptoms (e.g., benign gastric diseases other than tumors, unless specific therapeutic interventions were necessary at enrollment) in addition to "truly" healthy asymptomatic adults. However, we explicitly excluded trials that enrolled patients, 1) with gastric lesions requiring specific therapies at enrollment, 2) with a history of gastric carcinoma, 3) with gastric carcinoma at enrollment, and 4) those diagnosed with severe or systemic diseases. We made this We defined eradication therapy as the combination of a proton-pump inhibitor and at least one antibiotic, irrespective of drug class, dose, or treatment duration. We included RCTs with a parallel-group design (comparing eradication therapy with placebo or no treatment) and any form of factorial design (comparing the effects of eradication therapy/other intervention(s) alone/a combination thereof and placebo/no treatment). For eligibility, we did not specify the minimum follow-up period, how follow-up was conducted, or how gastric carcinoma was verified. We excluded trials that reported no gastric carcinoma events in all arms. However, we included trials irrespective of sample size or whether they were stopped early for any reason, if at least one gastric carcinoma event was observed. Only trials published as full text were included. Non-peer-reviewed scholarly articles (e.g., full-text articles in conference proceedings or special issues of regular peer-reviewed journals) 6 were included if they provided detailed analytical methodologies and sufficient data to allow for our analyses. We excluded trials that were only published as conference abstracts. In the case of multiple publications from one trial, we adopted the results from the publication with the longest follow-up duration, although we considered the information from all papers.

Data Extraction
We extracted information on trial, subject, and intervention characteristics.

Data Synthesis
We calculated summary hazard ratios (HRs) and their 95% credible intervals (CrIs), which are the Bayesian analogues of confidence intervals (CIs), and prediction intervals (PrIs) 8,9 using a hierarchical Bayesian random-effects meta-analysis method based on multinomial likelihood and a log link for multiple competing risk outcomes [10][11][12] to account for the uncertainty derived from the small number of RCTs with varied follow-up durations and censored subjects (i.e., any failures to observe the outcome events before the end of follow-up, defined as missing outcome data [MOD]). To stabilize the meta-analytic model, we selected the contrast-based and baseline model instead of the conventional standalone contrast-based model, 13,14 jointly modeling baseline and relative hazard rates because one RCT 15 reported no censored observations in both arms. For gastric carcinoma incidence, we modeled the baseline and relative hazard rates for gastric carcinoma events, non-gastric carcinoma deaths, and MOD, as mutually exclusive competing risk outcomes and their respective random-effect parameters independently in a single analysis. We assumed that hazards were constant over time (i.e., proportional hazards) for each outcome and that no cases of gastric carcinoma later died from a cause other than gastric carcinoma. For analyzing gastric carcinoma-specific and non-gastric carcinoma mortality, the model was applied for deaths from gastric carcinoma, deaths from all other causes, and MOD as competing risk outcomes. Likewise, we simultaneously modeled deaths from all causes and MOD for the analysis of all-cause mortality.
In the main analysis, the meta-analysis included only RCTs that observed at least one event for each outcome of interest. Specifically, we included all seven RCTs that reported at least one respective event for the meta-analysis of gastric carcinoma incidence; the meta-analysis of gastric carcinoma-specific mortality was based on only three RCTs with at least one such event; and the meta-analyses of non-gastric carcinoma mortality and all-cause mortality were based on five RCTs with at least one respective event for these outcomes. We also calculated the summary HRs of four outcomes each (i.e., gastric carcinoma-specific mortality, non-gastric carcinoma mortality, and all-cause mortality), based on all seven RCTs regardless of events observed as sensitivity analysis; the contrast-based and baseline model allowed for the inclusion of trials with zero events for any competing risk outcomes in both arms. 13,14 In the sensitivity analysis, we calculated summary ORs for cumulative gastric carcinoma incidence based on binomial logistic regression because gastric carcinoma events are rare. 11,12,16 For MOD and non-gastric carcinoma deaths, we performed two alternative analytical approaches: 17 1) a two-stage approach based on a standard hierarchical Bayesian meta-analytic model and "deterministic" analytical methods, 18 and 2) hierarchical Bayesian meta-analytic models directly allowing for uncertainty due to missing data. 19 Regarding non-gastric carcinoma deaths, we used two alternative analysis sets. First, we considered non-gastric carcinoma deaths as zero events and only considered censored cases as MOD. We then considered cases who died from non-gastric carcinoma in addition to censored subjects as MOD, assuming that subjects who died from other causes had remained at risk of developing gastric carcinoma and were comparable to censored subjects.
For the standard two-stage approach, we used "complete case analysis" as the primary analytical method.
All participants with MOD were excluded from the study, assuming that they were missing at random. 17,18 We then used the "last observation carried forward" method by imputing zero events for subjects with MOD. We performed another set of sensitivity analyses by imputing, in each arm, the same incidence of gastric carcinoma for subjects with MOD as that in the "complete case" analysis population in the same arm, assuming a common gastric carcinoma incidence regardless of the reasons for MOD.
For the meta-analytic models directly taking uncertainty into account, we based the analysis on all available information without relying on deterministic analytical assumptions. In the main analysis, because gastric carcinoma events are rare even in highly prevalent regions, we used, as recommended, 19 an informative beta (4.885, 195.555) prior distribution on the probability of an event for those with MOD, based on the gastric carcinoma incidence rates for trial participants in the control group and those for H. 100,000 person-years). We transformed the incidence rates to their corresponding cumulative incidences, accounting for the respective follow-up durations. In the sensitivity analysis, we used the informative missing OR. 20 In the main analysis, we used the recently proposed context-specific informative prior distributions on the between-trial standard deviations (tau) for outcomes comparing a pharmacological intervention with no treatment. 21 Specifically, for the between-trial variance (tau 2 ), we used log-normal (-3.95, 1.34 2 ) for all-cause mortality, log-normal (-3.71, 1.74 2 ) for gastric carcinoma mortality and non-gastric carcinoma mortality, log-normal (-2.99, 1.74 2 ) for MOD, and log-normal (-2.49, 1.52 2 ) for gastric carcinoma incidence. In the sensitivity analyses, we used two conventional alternative distributions: a minimally informative, vague uniform distribution on tau in the range between 0 and 2, i.e., unif(0,2) and an "inverse-gamma" prior, namely, gamma (0.001, 0.001) prior distribution for the inverse of tau 2 . 11,16 The informative priors in the main analysis were selected after all alternative analyses had been conducted. As there were only seven RCTs, we judged that the data were insufficient to inform multiple between-trial variance parameters using conventional priors. In all analyses, we used a vague uniform prior distribution, unif(0,2), for the between-trial standard deviation for baseline hazard rates for all outcomes.
We quantified between-study heterogeneity using the tau and I 2 statistics with their 95% CrIs. 22 An I 2 of >50% or >75%, respectively, suggests intermediate or high heterogeneity. 23 This interpretation, however, needs to be made carefully because the I 2 statistic may be unreliable, particularly when the number of studies is small. 24 For each model in the Bayesian meta-analysis, we based results on 3 different chains and 100,000 iterations (i.e., 300,000 total iterations) after a burn-in of 100,000 iterations. We considered nodes to have converged when the Brooks-Gelman-Rubin statistic was <1.01. 25 We estimated the residual deviance for assessing model fit. For example, we considered a model with residual deviance of ≤42 (unconstrained data points based on 7 RCTs with 2 arms and 3 competing risk outcomes in the main analysis) for gastric carcinoma incidence to be a good fit to the data 12, 26 We compared alternative models using the deviance information criterion (DIC) 12 We tested differences between subgroups as the ratio of ORs (rORs) or HRs (rHRs) by univariable meta-regression. 27,28 All analyses were conducted using the series of "wbs" commands 29

Goodness of Model Fit
In general, all sets of the Bayesian meta-analytic models, except those based on the inverse gamma prior for tau 2 , had residual deviance statistics that were comparable to the number of data points (e.g., 42 in the main analysis for gastric carcinoma incidence), suggesting a good model fit (Supplementary Table 4).
Although the models with vague uniform priors for tau in general had smaller residual deviance statistics than those of the informative priors, the differences were <1.5. Based on the DIC for the observed event data, models with the informative prior distributions were deemed to be the comparably best-fitting models (Supplementary Table 4). The differences between the highest and lowest DICs across the alternative prior distributions for the between-trial variance, however, were again generally <5, suggesting no definitively preferred selection (Supplementary Table 4).
|| Two other interventions included a "vitamin and mineral supplement" consisting of vitamin, C vitamin E, and selenium; and a "garlic supplement" consisting of garlic extract and oil. ¶ The prevalence of severe chronic atrophic gastritis, intestinal metaplasia, dysplasia, or gastric cancer; and the average score of a customized severity scale of gastric pre-cancerous lesions were the two other "major" endpoints planned before analysis. In the long-term follow-up report on the trial cohort, gastric cancer incidence and gastric cancer-specific mortality were the primary outcomes. # Moderate to severe dysplasia at any biopsy site or mild dysplasia at least two biopsy sites ** Severe chronic atrophic gastritis, intestinal metaplasia, indefinite dysplasia, and dysplasia (n = 285) † † Celecoxib 200 mg qd for 24 months following H. pylori eradication therapy or placebo as co-intervention ‡ ‡ The original inclusion criterion was a subject age of 16-75 years.   The Cochrane meta-analysis 7 extracted the following numerical data from the conference abstract (Saito 2005 45 ): 3 gastric carcinoma events; 379 and 313 subjects in the eradication and control arms, respectively, as the complete case analysis population; and 313 subjects in the control arm in the intention-to-treat analysis. † The Cochrane meta-analysis 7 and the Chen meta-analysis 46 do not include this trial. ‡ While the Chen meta-analysis 46 used the same dataset, the Cochrane meta-analysis 7 used the datasets from the eradication-and placebo-only arms and excluded the arms in which celecoxib was co-administered with eradication therapy or placebo in the main analysis and those from the total subjects including the celecoxib arms in the sensitivity analysis. § The Cochrane meta-analysis 7 extracted the following numerical data from the conference abstract (Zhou 2008 47 ): 276 subjects in each, eradication and control arm as the complete case

METHODS
Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
7 Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.

8; Appendix 2-3
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

7-8
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

Appendix 1-2
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
8 Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

8-9; Appendix 3-4
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

Section/topic # Checklist item Reported on page #
Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).

RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
11; Appendix 7-11; Suppl. Figure 1 Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
Suppl. Tables 1 and 2 Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot. 13-14; Figure 1; Appendix 11-12; Suppl. Table 4 Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15).

DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).

16-17
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).

METHODS: We searched databases including PubMed, Cochrane Central, and
Embase for reference and citation tracking without language restrictions, from inception through July 31, 2018. Paired investigators independently selected randomized controlled trials (RCTs) comparing eradication therapy with placebo or no treatment for asymptomatic or dyspeptic H. pylori-infected adults with no previous gastric carcinoma.
The main outcome was gastric carcinoma incidence; secondary outcomes included gastric carcinoma-specific, non-gastric carcinoma, and all-cause mortality.

CONCLUSIONS:
There is insufficient evidence to support or refute the effectiveness of eradication therapy in preventing gastric carcinoma in H. pylori-infected, high-risk populations. Rigorously conducted large RCTs of healthy infected adults only would provide evidence of the true efficacy of successful eradication.

Strengths and limitations of this study
 This is the first meta-analysis of the preventive effectiveness of eradication attempts in healthy-appearing H. pylori-infected subjects with no previous gastric carcinoma that adopted fully Bayesian approaches to account for multiple time-to-event outcomes with competing risks and frequent censored observations.  This review also performed comprehensive literature searches, obtained updated data from the trial authors, and used the Grading of Recommendation Assessment, Development and Evaluation (GRADE) approach to formally assess the certainty of the evidence.
 The eligible trials included subjects with high-risk preneoplastic lesions and adopted suboptimal eradication algorithms, which precluded reliable assessments of the true efficacy of successful eradication in healthy H. pylori-infected adults.

BACKGROUND
Gastric carcinoma is the second most common cancer-specific cause of death worldwide and the third most prevalent cancer in East Asia. 1

Infection with
Helicobacter pylori is a strong risk factor for gastric carcinoma. 2  pylori in high-risk populations. [13][14][15][16][17][18] However, concerns about implementing unfocused screening and eradication programs in healthy, asymptomatic populations still remain because these meta-analyses had several limitations. [9][10][11][12] The evidence partly derived from studies focusing on patients treated for early-stage gastric carcinoma 10,11 cannot be directly applied to the general population. Also, concerns about the evidence obtained from cohort studies 11,12 include confounding and other sources of bias. 19,20 A recent Cochrane review, the only meta-analysis focusing on RCTs of subjects without previous gastric carcinoma, 9 relied on data reported in conference abstracts 21 and used statistical approaches that can calculate falsely narrow confidence intervals (CIs) when the number of studies is small and events are rare. [22][23][24][25] Additionally, the sensitivity analyses used for exploring the effect of censored cases on the summary estimates were for binary outcomes, 26,27 not for time-to-event outcomes with competing risks. 28 Bayesian random-effects meta-analysis is an increasingly used flexible methodology that accounts for uncertainty by combining all available external evidence as the initial belief through the likelihood function, using new data to update the evidence. 29, 30 We conducted a systematic review and Bayesian meta-analysis to provide an accurate interpretation of the currently available evidence from RCTs on the preventive effect of H. pylori eradication on gastric carcinoma.

METHODS
This study is an updated systematic review and meta-analysis based on an evidence report that was produced for developing the Japanese Guidelines for Gastric Cancer Screening (see Supplementary Methods for details). 31 The original protocol was registered at PROSPERO (CRD42014009245).

Data Sources and Searches
We searched PubMed, the Cochrane Central Register of Controlled Trials, and Embase from inception through July 31, 2018 using search terms including "gastric cancer," "Helicobacter pylori," "eradication," and their synonyms, without language restrictions.

Data Extraction
One reviewer (TT) extracted trial, subject, and intervention characteristics from each eligible paper; another (KK) verified the data. If the paper with the longest follow-up period did not report the relevant information but cited earlier publications, we extracted data from the cited publications (see Supplementary Methods).
Our primary outcome was the incidence of gastric carcinoma; non-carcinoma tumors (e.g., lymphomas or sarcomas) were excluded. Our secondary outcomes were gastric carcinoma-specific mortality, non-gastric carcinoma mortality, and all-cause mortality.
Two reviewers (TT, IM) independently extracted the number of randomly allocated participants as the intention-to-treat analysis population, excluding any mistakenly enrolled ineligible subjects 26,33 as well as the numbers of gastric carcinoma events, deaths from gastric carcinoma and other causes, and censored subjects as missing outcome data (MOD) for each arm from the publications with the longest follow-up.
Censored subjects included those lost to follow-up for interim exclusion due to protocol deviation, noncompliance and withdrawal. 34 Disagreements were resolved by consensus. For any missing information or unresolved discrepancies, we contacted the authors of the primary studies for clarification or to request unpublished data. We considered the request rejected if two emails received no response.

Assessment of Risk of Bias
Two independent reviewers (TT, TY) analyzed sequence generation; allocation concealment; blinding of participants; trial personnel and outcome assessment; incomplete outcome data; selective reporting; and other biases using the Cochrane Collaboration's Risk of Bias tool. 35 The kappa coefficient for inter-rater agreement was 0.76, indicating good agreement. 36 Disagreements were resolved by consensus.

Data Synthesis
We calculated summary hazard ratios (HRs) and their 95% credible intervals (CrIs) and prediction intervals (PrIs), 30,37 using a hierarchical Bayesian random-effects metaanalysis method for competing risk time-to-event outcomes. 38,39 For gastric carcinoma incidence, we modeled the baseline and relative hazard rates for gastric carcinoma we applied hierarchical Bayesian random-effects meta-analytic models using the conventional imputation methods for binary outcomes, 26 and models directly allowing for uncertainty due to missing data. 40 After conducting the analyses based on three alternative prior distributions on the between-trial standard deviations (tau), we selected the context-specific informative prior distributions in the main analysis. 41 We determined this post-hoc selection since the data from only seven RCTs were deemed to be insufficient to inform multiple between-trial variance parameters using the other two conventional, less informative priors. 24,39 For each model in the Bayesian meta-analysis, we based results on 3 different chains and 100,000 iterations following a burn-in of 100,000 iterations. We considered nodes to have converged when the Brooks-Gelman-Rubin statistic was <1.01. 24 The Supplementary Methods provide complete details of the methodologies, model fitting, choice of prior distributions for the parameters, and the operational definitions used in the sensitivity analysis.  11 We assessed the certainty of evidence for each outcome using the Grading of Recommendation Assessment, Development and Evaluation (GRADE) approach. 42 We quantified between-study heterogeneity using the tau and I 2 statistics with their 95% CrIs. 43 To examine how each trial affected the summary estimate of the other RCTs, we performed a leave-one-out meta-analysis by calculating summary estimates iteratively, excluding one trial at a time. 44 We did not perform the planned tests for funnel plot asymmetry because eligible studies were <10. 45

Patient and Public Involvement
Although this study had no direct patient involvement, we modified the systematic review protocol based on input and feedback from the public regarding draft guidelines containing a set of interim results. 31

Literature Search and Eligible Studies
After abstract-level screening of the main searches, citation index searches, and

Study and Clinical Characteristics
The seven RCTs-five from China, 8 56,58 The follow-up duration extended beyond 10 years in only 2 trials. 8,55 Gastric carcinoma incidence was the primary outcome in only one RCT. 47 Another long-term follow-up report from the largest trial cohort reported gastric carcinoma as the post hoc primary outcome. 8 No trials defined gastric carcinoma-specific mortality or all-cause mortality as their primary outcomes before conducting the study. Methods used to confirm the outcomes were non-uniform. Four RCTs periodically performed endoscopic gastric surveys with biopsies of multiple sites; 8,55,58,60 the other three scheduled similar routine gastric surveys only once. 47,56,61 Three trials also examined patients' clinical records, the regional cancer registry, and/or death certificates to identify gastric carcinoma cases and death events. 8,47,56 The sample sizes ranged from 236 to 2,258 (median, 852) subjects with an average age of 42 to 53 years (Supplementary Table 2). Pre-cancerous gastric lesions at enrollment varied across trials; one trial that enrolled subjects with advanced gastric lesions reported gastric dysplasia in 54% of the participants. 56 The adopted eradication algorithms also varied. Two trials repeated first-line therapy for non-responders, 8,60 two provided no salvage therapy, 55,56 and one employed dual combination therapy. 8 While the post-treatment eradication rates assessed at 1-72 months ranged from 72% to 89%, follow-up eradication rates at 7 to 12 years were approximately 50%, suggesting recurrence or re-infection. 8,55,62 The baseline incidence of gastric carcinoma ranged from 107 to 1,802 per 100,000 person-years. The two RCTs of populations with specific histologic findings reported the lowest and second lowest incident rates. 56,58 Gastric carcinoma events were missing in 565 (15%) and 543 (15%) participants in the eradication and control arms, respectively. Overall, only one RCT, a long-term follow-up report of the largest trial, 8 was deemed to have a low risk of bias (Supplementary Figure 2 and Supplementary Table 3). Only two RCTs used the proportional hazard model to analyze time-to-event outcomes-one for gastric carcinoma incidence, 56 the other for mortality. 8

Incidence of Gastric Carcinoma
A total of 7 RCTs, including 7,303 adults, observed 138 gastric carcinoma events (

Gastric Carcinoma-Specific Mortality
A total of 3 community-based RCTs (4,400 adults) provided data on deaths from gastric carcinoma ( Table 1). Although gastric carcinoma-specific mortality was reduced on average by 41%, its uncertainty included both clinically important mortality benefit and  (Figure 1).
Concerns about precision due to the wide CrIs and indirectness due to the adoption of inadequate eradication strategies downgraded certainty.

All-Cause Mortality and Non-Gastric Carcinoma Mortality
A total of 5 community-based RCTs (6,316 adults) contributed data on deaths from all and non-gastric carcinoma causes (  16; low certainty) ( Figure 1). Certainty was down-rated because of the wide CrIs that included a clinically important mortality benefit and increase.

Subgroup Analysis
The subgroup meta-analysis for trials conducted in East Asia found an average  Table 4). The meta-regression analyses showed no differential effects by geographic location, research setting, or subject selection.

Sensitivity Analysis
For gastric carcinoma incidence, the CrIs for the summary HRs generally became wider, with the upper limit crossing 1, when alternative, less informative priors for tau were specified except for the subgroup analysis where the 2 trials of populations with specific histologic findings were excluded (Supplementary Table 4 Table 5). The summary HRs for the mortality outcomes were not materially different from the results in the main analysis when alternative priors for tau were used, or all seven trials were included in the sensitivity analysis (Supplementary Table 4).

Main findings
Our meta-analysis found only a low strength of evidence that H. pylori eradication may have been more likely than control treatment to reduce gastric carcinoma development-although the average effect suggested a risk reduction by 30%, its uncertainty included the null effects. This finding was generally consistent across subgroup and sensitivity analyses except when two factorial design trials that focused on enrollees with specific histologic findings were excluded. Although we calculated a similar average effect size, our wide CrIs were not congruent with those of previous meta-analyses including the Cochrane meta-analysis that reported that H. pylori eradication significantly reduced gastric carcinoma risk. 9 This highlights the uncertainty surrounding the effectiveness of unfocused test-and-eradicate programs, even in highrisk regions. A recently published fixed-effects meta-analysis using risk difference as the outcome measure, although naïvely conducted, reported a non-significant risk reduction associated with eradication therapy, which raised concerns about the conclusions from previous meta-analyses. 64 The results of our Bayesian meta-analysis corroborate this finding.
The preventive effects became larger and significant-an average of 45% risk reduction-when the two factorial design trials that selected more histologically advanced lesions were excluded. This suggests that eradication therapy may be more effective in non-focused, potentially lower-risk populations; this is in line with the meta-analysis of a subgroup from the primary prevention RCTs conducted by Chen et al. 10 The fixed-effects meta-analysis of subjects with better pre-eradication histology than intestinal metaplasia or dysplasia only, comprising only one case who developed gastric carcinoma out of 1,221 subjects in the eradication group versus 10 cases out of 1,228 in the control group, although the balance between the two groups created from affected gastric carcinoma events would exist, given the lowest baseline incidence rates in the two factorial RCTs of histologically "high-risk" populations. For example, given the subjective nature of endoscopic evaluation in particular, "missed" cases of gastric carcinoma at enrollment and/or during the follow-up rounds are always a concern affecting the validity of gastric carcinoma research. 65 Therefore, our observation based on subgroup analysis should be viewed as hypothesis generation.
We found that evidence on gastric carcinoma-specific and overall mortality was insufficient because the RCTs were not powered to detect differences in these outcomes. The wide CrIs for the average effect suggest that while a clinically meaningful 75% reduction in gastric carcinoma-specific mortality is possible, a 20% increase cannot be ruled out.
Our meta-analysis has several strengths. We employed Bayesian approaches to account for multiple time-to-event outcomes with competing risks and frequent censored observations. Our literature search found one RCT 61 that previous meta-analyses had failed to include. We also utilized data extracted from full-text publications and obtained unpublished data from two RCTs, 55,60 for which previous meta-analyses had relied on the data presented in conference abstracts 9,12 or earlier short-term reports (Supplementary Table 6). 10 These additional data allowed us to perform a more comprehensive analysis than was possible in previous meta-analyses that focused on RCTs only 9,10,64 regarding across-trial differences in research settings, patient symptoms at enrollment, missing outcomes, and mortality events.

Limitations
Limitations of the included RCTs other than short, incomplete follow-ups, need to be noted. The RCTs employed potentially sub-optimal eradication algorithms and reported frequent rates of recurrence or reinfection. These unsuccessful eradication attempts could have affected the preventive effect. In addition, as already noted, inclusion of RCTs that allowed for the inclusion of subjects with advanced pre-neoplastic lesions, those at high risk for progression to gastric carcinoma, 13 might have attenuated the preventive effects. Moreover, interactions with concurrent interventions, regardless of their directions, cannot be ruled out in the three factorial design trials. Similar to previous meta-analyses, 9,10,64 our Bayesian meta-analysis could not address these limitations analytically without access to individual-level data.
In the meta-analysis of gastric carcinoma incidence, our assumption that those who developed gastric carcinoma would not die from causes other than gastric carcinoma should be clinically acceptable. Nevertheless, more accurate analysis would require individual-level data or modeling with additional assumptions for the conditional risk of non-gastric carcinoma deaths.

Implications
Given the insufficient randomized evidence, rigorously conducted large RCTs adopting  37 Further, we should not ignore all-cause and gastric carcinoma-specific mortality and long-term adverse events as important outcomes attributable to eradication.
In conclusion, there is insufficient randomized evidence to support or refute the effectiveness of eradication therapy in preventing gastric carcinoma in H. pyloriinfected, high-risk populations. Large RCTs of only healthy H. pylori-infected adults adopting more stringent research methodologies will provide evidence regarding the true efficacy of successful eradication.

Ethics approval and consent to participate
Not required.

Patient consent
Not required.

Supplementary Methods
To update the Japanese Guidelines for Gastric Cancer Screening published in 2005, 1 we recently conducted a broad systematic review. 2 As an extension of "risk-stratified" screening strategies that incorporate Helicobacter pylori seropositivity and/or the pepsinogen test as primary screening 3

Study Selection
We modified the original inclusion criterion of "healthy adults" after perusing full-text articles to allow the inclusion of otherwise generally healthy subjects with gastric symptoms (e.g., benign gastric diseases other than tumors, unless specific therapeutic interventions were necessary at enrollment) in addition to "truly" healthy asymptomatic adults. However, we explicitly excluded trials that enrolled patients, 1) with gastric lesions requiring specific therapies at enrollment, 2) with a history of gastric carcinoma, 3) with gastric carcinoma at enrollment, and 4) those diagnosed with severe or systemic diseases. We made this  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  We defined eradication therapy as the combination of a proton-pump inhibitor and at least one antibiotic, irrespective of drug class, dose, or treatment duration. We included RCTs with a parallel-group design (comparing eradication therapy with placebo or no treatment) and any form of factorial design (comparing the effects of eradication therapy/other intervention(s) alone/a combination thereof and placebo/no treatment). For eligibility, we did not specify the minimum follow-up period, how follow-up was conducted, or how gastric carcinoma was verified. We excluded trials that reported no gastric carcinoma events in all arms. However, we included trials irrespective of sample size or whether they were stopped early for any reason, if at least one gastric carcinoma event was observed. Only trials published as full text were included. Non-peer-reviewed scholarly articles (e.g., full-text articles in conference proceedings or special issues of regular peer-reviewed journals) 6 were included if they provided detailed analytical methodologies and sufficient data to allow for our analyses. We excluded trials that were only published as conference abstracts. In the case of multiple publications from one trial, we adopted the results from the publication with the longest follow-up duration, although we considered the information from all papers.

Data Extraction
We extracted information on trial, subject, and intervention characteristics. Trial characteristics included study ID, location, setting (community vs. outpatient care), enrollment (year), target population, exclusion criteria, primary outcomes, verification of gastric cancer, and follow-up duration. Subject characteristics included the total and per-arm number of participants; mean or median age; percentage of male participants; percentage of participants with dyspepsia; baseline pre-cancerous histology; and primary, overall post-therapy, and longest follow-up eradication rates in the eradication arm. Intervention characteristics comprised the eradication algorithms used, including dose and duration. If the paper with the longest follow-up did not explicitly report these data but cited earlier publications, we consulted the

Data Synthesis
We calculated summary hazard ratios (HRs) and their 95% credible intervals (CrIs), which are the Bayesian analogues of confidence intervals (CIs), and prediction intervals (PrIs) 8 In the main analysis, the meta-analysis included only RCTs that observed at least one event for each outcome of interest. Specifically, we included all seven RCTs that reported at least one respective event for the meta-analysis of gastric carcinoma incidence; the meta-analysis of gastric carcinoma-specific mortality was based on only three RCTs with at least one such event; and the meta-analyses of non-gastric carcinoma mortality and all-cause mortality were based on five RCTs with at least one respective event for these outcomes. We also calculated the summary HRs of four outcomes each (i.e., all seven RCTs regardless of events observed as sensitivity analysis; the contrast-based and baseline model allowed for the inclusion of trials with zero events for any competing risk outcomes in both arms. 13,14 In the sensitivity analysis, we calculated summary ORs for cumulative gastric carcinoma incidence based on binomial logistic regression because gastric carcinoma events are rare. 11,12,16 For MOD and non-gastric carcinoma deaths, we performed two alternative analytical approaches: 17 1) a two-stage approach based on a standard hierarchical Bayesian meta-analytic model and "deterministic" analytical methods, 18 and 2) hierarchical Bayesian meta-analytic models directly allowing for uncertainty due to missing data. 19 Regarding non-gastric carcinoma deaths, we used two alternative analysis sets. First, we considered non-gastric carcinoma deaths as zero events and only considered censored cases as MOD. We then considered cases who died from non-gastric carcinoma in addition to censored subjects as MOD, assuming that subjects who died from other causes had remained at risk of developing gastric carcinoma and were comparable to censored subjects.
For the standard two-stage approach, we used "complete case analysis" as the primary analytical method.
All participants with MOD were excluded from the study, assuming that they were missing at random. 17,18 We then used the "last observation carried forward" method by imputing zero events for subjects with MOD. We performed another set of sensitivity analyses by imputing, in each arm, the same incidence of gastric carcinoma for subjects with MOD as that in the "complete case" analysis population in the same arm, assuming a common gastric carcinoma incidence regardless of the reasons for MOD.
For the meta-analytic models directly taking uncertainty into account, we based the analysis on all available information without relying on deterministic analytical assumptions. In the main analysis, because gastric carcinoma events are rare even in highly prevalent regions, we used, as recommended, 19 an informative beta (4.885, 195.555) prior distribution on the probability of an event for those with MOD, based on the gastric carcinoma incidence rates for trial participants in the control group and those for H. person-years) 20 ). In the sensitivity analysis, we used the informative missing OR. 21 In the main analysis, we used the recently proposed context-specific informative prior distributions on the between-trial standard deviations (tau) for outcomes comparing a pharmacological intervention with no treatment. 22 The context-specific informative priors consist of a set of data-based predictive distributions for heterogeneity, which are reported as lognormal distribution for 80 different settings (defined by type of outcome and type of intervention comparisons). 21 These 80 distributions are derived from over 14,000 existing meta-analyses of binary outcomes from nearly 2,000 systematic reviews included in the Cochrane Database of Systematic Reviews (Issue 1, 2008). Several applications of this set of informative prior distributions exist. [23][24][25][26] Specifically, for the between-trial variance (tau 2 ), we used log-normal (-3.95, 1.34 2 ) for all-cause mortality, log-normal (-3.71, 1.74 2 ) for gastric carcinoma mortality and non-gastric carcinoma mortality, log-normal (-2.99, 1.74 2 ) for MOD, and log-normal (-2.49, 1.52 2 ) for gastric carcinoma incidence. In the sensitivity analyses, we used two conventional alternative distributions: a minimally informative but still vague uniform distribution on tau in the range between 0 and 2, i.e., unif(0,2) and an "inverse-gamma" prior, namely, gamma (0.001, 0.001) prior distribution for the inverse of tau 2 . 11,16 The informative priors in the main analysis were selected after all alternative analyses had been conducted. As there were only seven RCTs, we judged that the data were insufficient to inform multiple between-trial variance parameters using conventional priors. In all analyses, we used a minimally informative but still vague uniform prior distribution, unif(0,2), for the between-trial standard deviation for baseline hazard rates for all outcomes.
We quantified between-study heterogeneity using the tau and I 2 statistics with their 95% CrIs. 27 An I 2 of >50% or >75%, respectively, suggests intermediate or high heterogeneity. 28 This interpretation, however,  29 For each model in the Bayesian meta-analysis, we based results on 3 different chains and 100,000 iterations (i.e., 300,000 total iterations) after a burn-in of 100,000 iterations. We considered nodes to have converged when the Brooks-Gelman-Rubin statistic was <1.01. 30 We estimated the residual deviance for assessing model fit. For example, we considered a model with residual deviance of ≤42 (unconstrained data points based on 7 RCTs with 2 arms and 3 competing risk outcomes in the main analysis) for gastric carcinoma incidence to be a good fit to the data 12, 31 We compared alternative models using the deviance information criterion (DIC) 12,31 and deemed a difference in DIC scores >5 to be important. 31 To explore differences in preventive effects between research settings, we performed post-hoc subgroup analyses of trials from East Asia (vs. non-East Asian countries), those conducted in the community (vs. outpatient settings), and of selected subjects with specific histologic subtypes (vs. not).
We tested differences between subgroups as the ratio of ORs (rORs) or HRs (rHRs) by univariable meta-regression. 32,33 All analyses were conducted using the series of "wbs" commands 34

Goodness of Model Fit
In general, all sets of the Bayesian meta-analytic models, except those based on the inverse gamma prior for tau 2 , had residual deviance statistics that were comparable to the number of data points (e.g., 42 in the main analysis for gastric carcinoma incidence), suggesting a good model fit (Supplementary Table 4).
Although the models with vague uniform priors for tau in general had smaller residual deviance statistics than those of the informative priors, the differences were <1.5. Based on the DIC for the observed event data, models with the informative prior distributions were deemed to be the comparably best-fitting models (Supplementary Table 4). The differences between the highest and lowest DICs across the alternative prior distributions for the between-trial variance, however, were again generally <5, suggesting no definitively preferred selection (Supplementary Table 4). In the sensitivity analyses for gastric carcinoma incidence based on the conventional Bayesian meta-analysis for binary outcomes, all sets of the meta-analytic models had residual deviance statistics for the observed events that were comparable to the unconstrained data points, suggesting good model fit (Supplementary Table 5). Although the models directly accounting for MOD in general had smaller residual deviance statistics than those based on the 2-step approach using the deterministic analytical methods, the differences were typically <3. Based on the lower DICs for the observed event data, two approaches, models directly accounting for MOD with either the informative priors or the vague uniform prior, were deemed to be the comparably best-fitting models (Supplementary Table 5). The differences between the highest and lowest DICs across the alternative prior distributions for the between-trial variance, however, were again typically <5, suggesting no definitively preferred selection. Based on the residual deviance statistics and DICs for MOD, no particular models for alternative mechanisms for data missingness were considered to outperform any other (Supplementary Table 5). Two other interventions included beta-carotene and ascorbic acid. ‡ The evaluation of gastric cancer incidence was planned before analysis; however, it was not evaluated due to early termination of the trial because of low recruitment. § Primary outcomes were not explicitly specified.
|| Two other interventions included a "vitamin and mineral supplement" consisting of vitamin, C vitamin E, and selenium; and a "garlic supplement" consisting of garlic extract and oil. ¶ The prevalence of severe chronic atrophic gastritis, intestinal metaplasia, dysplasia, or gastric cancer; and the average score of a customized severity scale of gastric pre-cancerous lesions were the two other "major" endpoints planned before analysis. In the long-term follow-up report on the trial cohort, gastric cancer incidence and gastric cancer-specific mortality were the primary outcomes.

Trials of specific gastric lesions only excluded (5 studies)
Informative

Trials of specific gastric lesions only excluded (3 studies)
Informative       control arms, respectively, as the complete case analysis population; and 313 subjects in the control arm in the intention-to-treat analysis. † The Cochrane meta-analysis 7 and the Chen meta-analysis 51 do not include this trial. ‡ While the Chen meta-analysis 51 used the same dataset, the Cochrane meta-analysis 7 used the datasets from the eradication-and placebo-only arms and excluded the arms in which celecoxib was co-administered with eradication therapy or placebo in the main analysis and those from the total subjects including the celecoxib arms in the sensitivity analysis. § The Cochrane meta-analysis 7 extracted the following numerical data from the conference abstract (Zhou 2008 52 ): 276 subjects in each, eradication and control arm as the complete case  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46 36 analysis population as the number of censored cases was not reported. The Chen meta-analysis 51 used an earlier full-text report with a shorter 5-year follow-up (Leung 2004 48 ), which the Cochrane meta-analysis 7 employed in a sensitivity analysis.   Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.

8; Appendix 2-3
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

7-8
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

Appendix 1-2
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
8 Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

8-9; Appendix 3-4
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

8-9; Appendix 3-4 Risk of bias in individual studies
12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.  Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.

RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
Suppl. Tables 1 and 2 Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot. 14-15; Figure 1; Appendix 11-12; Suppl. Table 4 Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15).

DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).

METHODS: We searched databases including PubMed, Cochrane Central, and
Embase for reference and citation tracking without language restrictions, from inception through July 31, 2018. Paired investigators independently selected randomized controlled trials (RCTs) comparing eradication therapy with placebo or no treatment for asymptomatic or dyspeptic H. pylori-infected adults with no previous gastric carcinoma.
The main outcome was gastric carcinoma incidence; secondary outcomes included gastric carcinoma-specific, non-gastric carcinoma, and all-cause mortality.

BACKGROUND
Gastric carcinoma is the second most common cancer-specific cause of death worldwide and the third most prevalent cancer in East Asia. 1

Infection with
Helicobacter pylori is a strong risk factor for gastric carcinoma. 2 Several postulated oncogenic mechanisms 3 and epidemiological evidence 4,5 supporting this association exist. Explanations for the high gastric carcinoma incidence in East Asia include environmental factors such as high sodium intake 6 and the geographically distinct predominance of H. pylori strains characterized by strain-specific polymorphisms in the cagA gene, producing a highly virulent CagA. 6,7 Since the establishment of effective eradication treatments in the 1990s, several randomized controlled trials (RCTs) have assessed whether eradicating H. pylori can reduce the risk of gastric carcinoma in healthy adults. After multiple reports of inconclusive results, with the long-term follow-up of the largest RCT that showed a significant reduction in gastric carcinoma risk in the eradication group, 8 several metaanalyses that included RCTs only, 9,10 observational studies only, 11  pylori in high-risk populations. [13][14][15][16][17][18] However, concerns about implementing unfocused screening and eradication programs in healthy, asymptomatic populations still remain because these meta-analyses had several limitations. [9][10][11][12] The evidence partly derived from studies focusing on patients treated for early-stage gastric carcinoma 10,11 cannot be directly applied to the general population. Also, concerns about the evidence obtained from cohort studies 11,12 include confounding and other sources of bias. 19,20 A recent  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60   F  o  r  p  e  e  r  r  e  v  i  e  w  o  n  l  y   7 Cochrane review, the only meta-analysis focusing on RCTs of subjects without previous gastric carcinoma, 9 relied on data reported in conference abstracts 21 and used statistical approaches that can calculate falsely narrow confidence intervals (CIs) when the number of studies is small and events are rare. [22][23][24][25] Additionally, the sensitivity analyses used for exploring the effect of censored cases on the summary estimates were for binary outcomes, 26,27 not for time-to-event outcomes with competing risks. 28 Bayesian random-effects meta-analysis is an increasingly used flexible methodology that accounts for uncertainty by combining all available external evidence as the initial belief through the likelihood function, using new data to update the evidence. 29,30 We conducted a systematic review and Bayesian meta-analysis to provide an accurate interpretation of the currently available evidence from RCTs on the preventive effect of H. pylori eradication on gastric carcinoma.

METHODS
This study is an updated systematic review and meta-analysis based on an evidence report that was produced for developing the Japanese Guidelines for Gastric Cancer Screening (see Supplementary Methods for details). 31 The original protocol was registered at PROSPERO (CRD42014009245).

Study Selection
Paired reviewers, drawn from the group of seven investigators (TT, CH, KK, IM, TY, RT, and HN), independently screened non-overlapping sets of abstracts and full texts of potentially eligible studies. RCTs that compared eradication therapies for H. pylori with placebo or no treatment in asymptomatic or otherwise healthy, dyspeptic H. pyloriinfected adults (aged ≥18 years) with no history of gastric carcinoma were eligible. We allowed for the inclusion of "otherwise healthy, dyspeptic subjects" post hoc because both uninvestigated and functional dyspepsia are common in Asia, 32

Data Extraction
One reviewer (TT) extracted trial, subject, and intervention characteristics from each eligible paper; another (KK) verified the data. If the paper with the longest follow-up period did not report the relevant information but cited earlier publications, we extracted data from the cited publications (see Supplementary Methods).
Two reviewers (TT, IM) independently extracted the number of randomly allocated participants as the intention-to-treat analysis population, excluding any mistakenly enrolled ineligible subjects 26,33 as well as the numbers of gastric carcinoma events, deaths from gastric carcinoma and other causes, and censored subjects as missing outcome data (MOD) for each arm from the publications with the longest follow-up.
Censored subjects included those lost to follow-up for interim exclusion due to protocol deviation, noncompliance and withdrawal. 34 Disagreements were resolved by consensus. For any missing information or unresolved discrepancies, we contacted the authors of the primary studies for clarification or to request unpublished data. We considered the request rejected if two emails received no response.

Assessment of Risk of Bias
Two independent reviewers (TT, TY) analyzed sequence generation; allocation concealment; blinding of participants; trial personnel and outcome assessment; incomplete outcome data; selective reporting; and other biases using the Cochrane Collaboration's Risk of Bias tool. 35 The kappa coefficient for inter-rater agreement was 0.76, indicating good agreement. 36 Disagreements were resolved by consensus.

Data Synthesis
We calculated summary hazard ratios (HRs) and their 95% credible intervals (CrIs) and prediction intervals (PrIs), 30,37 using a hierarchical Bayesian random-effects metaanalysis method for competing risk time-to-event outcomes. 38,39 For gastric carcinoma incidence, we modeled the baseline and relative hazard rates for gastric carcinoma  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60   F  o  r  p  e  e  r  r  e  v  i  e  w  o  n  l  y 10 events, non-gastric carcinoma deaths, and MOD as mutually exclusive outcomes and their respective random-effect parameters in a single analysis; we assumed that no cases of gastric carcinoma later died from a cause other than gastric carcinoma. For analyzing gastric carcinoma-specific and non-gastric carcinoma mortality, deaths from gastric carcinoma, deaths from all other causes, and MOD were simultaneously modeled as mutually exclusive outcomes with their respective random-effect parameters. As a sensitivity analysis, we calculated summary odds ratios (ORs) for cumulative gastric carcinoma incidence as a binary outcome. For MOD and non-gastric carcinoma deaths, we applied hierarchical Bayesian random-effects meta-analytic models using the conventional imputation methods for binary outcomes, 26 and models directly allowing for uncertainty due to missing data. 40 After conducting the analyses based on three alternative prior distributions on the between-trial standard deviations (tau), we selected the context-specific informative prior distributions in the main analysis. 41 We determined this post-hoc selection since the data from only seven RCTs were deemed to be insufficient to inform multiple between-trial variance parameters using the other two conventional, less informative priors. 24,39 For each model in the Bayesian meta-analysis, we based results on 3 different chains and 100,000 iterations following a burn-in of 100,000 iterations. We considered nodes to have converged when the Brooks-Gelman-Rubin statistic was <1.01. 24 The Supplementary Methods provide complete details of the methodologies, model fitting, choice of prior distributions for the parameters, and the operational definitions used in the sensitivity analysis.  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60 F o r p e e r r e v i e w o n l y 11 We assessed the certainty of evidence for each outcome using the Grading of Recommendation Assessment, Development and Evaluation (GRADE) approach. 42 We quantified between-study heterogeneity using the tau and I 2 statistics with their 95% CrIs. 43 To examine how each trial affected the summary estimate of the other RCTs, we performed a leave-one-out meta-analysis by calculating summary estimates iteratively, excluding one trial at a time. 44 We did not perform the planned tests for funnel plot asymmetry because eligible studies were <10. 45 To explore clinical heterogeneity, we

Patient and Public Involvement
Although this study had no direct patient involvement, we modified the systematic review protocol based on input and feedback from the public regarding draft guidelines containing a set of interim results. 31

Study and Clinical Characteristics
The seven RCTs-five from China, 8,47,55,56,61 one from Japan, 60 Table 1). Two populationbased RCTs 47,55 and one outpatient care trial 60 explicitly included participants with dyspeptic symptoms in addition to asymptomatic subjects. The other trials, three population-based 8,56,58 and one outpatient care-based RCT, 61 did not report on symptoms at enrollment. One RCT diagnosed H. pylori infection by serologic testing only. 8 Four trials used a parallel design, 47,55,60,61 whereas the other three adopted factorial designs with co-interventions of vitamins; 58 vitamins, selenium, and garlic extract; 8 or celecoxib, a cyclooxygenase-2 inhibitor. 56 Two RCTs focused on populations with specific precancerous lesions based on pre-enrollment histology results. 56,58 The follow-up duration extended beyond 10 years in only 2 trials. 8,55 Gastric carcinoma incidence was the primary outcome in only one RCT. 47 Another  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60   F  o  r  p  e  e  r  r  e  v  i  e  w  o  n  l  y   13 long-term follow-up report from the largest trial cohort reported gastric carcinoma as the post hoc primary outcome. 8 No trials defined gastric carcinoma-specific mortality or all-cause mortality as their primary outcomes before conducting the study. Methods used to confirm the outcomes were non-uniform. Four RCTs periodically performed endoscopic gastric surveys with biopsies of multiple sites; 8,55,58,60 the other three scheduled similar routine gastric surveys only once. 47,56,61 Three trials also examined patients' clinical records, the regional cancer registry, and/or death certificates to identify gastric carcinoma cases and death events. 8,47,56 The sample sizes ranged from 236 to 2,258 (median, 852) subjects with an average age of 42 to 53 years (Supplementary Table 2). Pre-cancerous gastric lesions at enrollment varied across trials; one trial that enrolled subjects with advanced gastric lesions reported gastric dysplasia in 54% of the participants. 56 The adopted eradication algorithms also varied. Two trials repeated first-line therapy for non-responders, 8,60 two provided no salvage therapy, 55,56 and one employed dual combination therapy. 8 While the post-treatment eradication rates assessed at 1-72 months ranged from 72% to 89%, follow-up eradication rates at 7 to 12 years were approximately 50%, suggesting recurrence or re-infection. 8,55,62 The baseline incidence of gastric carcinoma ranged from 107 to 1,802 per 100,000 person-years. The two RCTs of populations with specific histologic findings reported the lowest and second lowest incident rates. 56,58 Gastric carcinoma events were missing in 565 (15%) and 543 (15%) participants in the eradication and control arms, respectively.  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60   F  o  r  p  e  e  r  r  e  v  i  e  w  o  n  l  y   14 Overall, only one RCT, a long-term follow-up report of the largest trial, 8 was deemed to have a low risk of bias (Supplementary Figure 2 and Supplementary Table 3). Only two RCTs used the proportional hazard model to analyze time-to-event outcomes-one for gastric carcinoma incidence, 56 the other for mortality. 8

Incidence of Gastric Carcinoma
A total of 7 RCTs, including 7,303 adults, observed 138 gastric carcinoma events (Table 1). They failed to observe the primary outcome in 369 subjects who died from non-gastric carcinoma causes and in 649 subjects with MOD. Although the summary estimates showed a 35% risk reduction for gastric carcinoma associated with eradication therapy, the upper limit of the 95% CrI included 1, the null effect, suggesting inconclusive average preventive effects of eradication therapy on gastric carcinoma risk

All-Cause Mortality and Non-Gastric Carcinoma Mortality
A total of 5 community-based RCTs (6,316 adults) contributed data on deaths from all and non-gastric carcinoma causes (Table 1) (Figure 1). Certainty was down-rated because of the wide CrIs that included a clinically important mortality benefit and increase.

Sensitivity Analysis
For gastric carcinoma incidence, the CrIs for the summary HRs generally became wider, with the upper limit crossing 1, when alternative, less informative priors for tau were specified except for the subgroup analysis where the 2 trials of populations with specific histologic findings were excluded (Supplementary Table 4). Similarly, the CrIs crossed 1, unless 1 of 2 RCTs for histologically selected populations was excluded in the leaveone-out meta-analysis (Supplementary Figure 3). In the sensitivity analyses using the conventional Bayesian meta-analysis for binary outcomes, the summary ORs were generally congruent to the summary HRs of the main analysis. The CrIs were generally wide and crossed the null effects (i.e., OR=1) regardless of the prior distributions for tau, the use of alternative imputation methods or models directly accounting for uncertainty to account for MOD, or exclusion of non-gastric carcinoma deaths from MOD, except for the subgroup analysis where two trials of histologically selected populations were excluded (Supplementary Table 5). The summary HRs for the mortality outcomes were not materially different from the results in the main analysis when alternative priors for tau were used, or all seven trials were included in the sensitivity analysis (Supplementary Table 4).

Main findings
Our meta-analysis found only a low strength of evidence that H. pylori eradication may  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60   F  o  r  p  e  e  r  r  e  v  i  e  w  o  n  l  y   17 have been more likely than control treatment to reduce gastric carcinoma development-although the average effect suggested a risk reduction by 30%, its uncertainty included the null effects. This finding was generally consistent across subgroup and sensitivity analyses except when two factorial design trials that focused on enrollees with specific histologic findings were excluded. Although we calculated a similar average effect size, our wide CrIs were not congruent with those of previous meta-analyses including the Cochrane meta-analysis that reported that H. pylori eradication significantly reduced gastric carcinoma risk. 9 This highlights the uncertainty surrounding the effectiveness of unfocused test-and-eradicate programs, even in highrisk regions. A recently published fixed-effects meta-analysis using risk difference as the outcome measure, although naïvely conducted, reported a non-significant risk reduction associated with eradication therapy, which raised concerns about the conclusions from previous meta-analyses. 64 The results of our Bayesian meta-analysis corroborate this finding.
The preventive effects became larger and significant-an average of 45% risk reduction-when the two factorial design trials that selected more histologically advanced lesions were excluded. This suggests that eradication therapy may be more effective in non-focused, potentially lower-risk populations; this is in line with the meta-analysis of a subgroup from the primary prevention RCTs conducted by Chen et al. 10 The fixed-effects meta-analysis of subjects with better pre-eradication histology than intestinal metaplasia or dysplasia only, comprising only one case who developed gastric carcinoma out of 1,221 subjects in the eradication group versus 10 cases out of 1,228 in the control group, although the balance between the two groups created from  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60   F  o  r  p  e  e  r  r  e  v  i  e  w  o  n  l  y 18 randomization might no longer hold, reported a significant 78% risk reduction (relative risk=0.22 [95% CI, 0.06 to 0.86]). However, the severity of the baseline precancerous lesions across the trials could not directly be compared due to variations including the histologic criteria used. Furthermore, in addition to baseline histology, other factors that affected gastric carcinoma events would exist, given the lowest baseline incidence rates in the two factorial RCTs of histologically "high-risk" populations. For example, given the subjective nature of endoscopic evaluation in particular, "missed" cases of gastric carcinoma at enrollment and/or during the follow-up rounds are always a concern affecting the validity of gastric carcinoma research. 65 Therefore, our observation based on subgroup analysis should be viewed as hypothesis generation.
We found that evidence on gastric carcinoma-specific and overall mortality was insufficient because the RCTs were not powered to detect differences in these outcomes. The wide CrIs for the average effect suggest that while a clinically meaningful 75% reduction in gastric carcinoma-specific mortality is possible, a 20% increase cannot be ruled out.
Our meta-analysis has several strengths. We employed Bayesian approaches to account for multiple time-to-event outcomes with competing risks and frequent censored observations. Our literature search found one RCT 61 that previous meta-analyses had failed to include. We also utilized data extracted from full-text publications and obtained unpublished data from two RCTs, 55,60 for which previous meta-analyses had relied on the data presented in conference abstracts 9,12 or earlier short-term reports (Supplementary Table 6). 10 These additional data allowed us to perform a more comprehensive analysis than was possible in previous meta-analyses that focused on RCTs only 9,10,64 regarding across-trial differences in research settings, patient symptoms at enrollment, missing outcomes, and mortality events.

Limitations
Limitations of the included RCTs other than short, incomplete follow-ups, need to be noted. The RCTs employed potentially sub-optimal eradication algorithms and reported frequent rates of recurrence or reinfection. These unsuccessful eradication attempts could have affected the preventive effect. In addition, as already noted, inclusion of RCTs that allowed for the inclusion of subjects with advanced pre-neoplastic lesions, those at high risk for progression to gastric carcinoma, 13 might have attenuated the preventive effects. Moreover, interactions with concurrent interventions, regardless of their directions, cannot be ruled out in the three factorial design trials. Similar to previous meta-analyses, 9,10,64 our Bayesian meta-analysis could not address these limitations analytically without access to individual-level data.
In the meta-analysis of gastric carcinoma incidence, our assumption that those who developed gastric carcinoma would not die from causes other than gastric carcinoma should be clinically acceptable. Nevertheless, more accurate analysis would require individual-level data or modeling with additional assumptions for the conditional risk of non-gastric carcinoma deaths.

Ethics approval and consent to participate
Not required.

Patient consent
Not required.

Data sharing statement
All data generated or analyzed during this study are included in APPENDIX.  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59   〇〇 ○ + ○ + Low * Uncertainty due to large loss to follow-up relative to the small number of events, possible interaction with co-treatments, and/or short follow-up † Uncertainty due to clinical heterogeneity (e.g., inclusion of subjects with dyspepsia in addition to asymptomatic healthy adults, different recruitment sources [population-vs. outpatient carebased], and/or subject selection based on pre-eradication gastric precancerous lesions [subjects with specific gastric lesions only vs. all participants regardless of histologic results]) and possible statistical heterogeneity suggested by the broad CrIs for I 2 and tau ‡ Unsatisfactory eradication attempts and frequent reinfections, limiting the applicability of the results to current clinical practice § While the CrI for the pooled effect crossed the null effect, the plausible effects suggest both reduction and increase by 31% and 28%, respectively. || While the CrI for the pooled effect crossed the null effect, the plausible effects suggest both reduction and increase by 75% and 20%, respectively. ¶ While the upper boundary of the CrI reached the null effect, the plausible average effects include risk reduction by as high as 59%.

Supplementary Methods
To update the Japanese Guidelines for Gastric Cancer Screening published in 2005, 1 we recently conducted a broad systematic review. 2 As an extension of "risk-stratified" screening strategies that incorporate Helicobacter pylori seropositivity and/or the pepsinogen test as primary screening 3

Study Selection
We modified the original inclusion criterion of "healthy adults" after perusing full-text articles to allow the inclusion of otherwise generally healthy subjects with gastric symptoms (e.g., benign gastric diseases other than tumors, unless specific therapeutic interventions were necessary at enrollment) in addition to "truly" healthy asymptomatic adults. However, we explicitly excluded trials that enrolled patients, 1) with gastric lesions requiring specific therapies at enrollment, 2) with a history of gastric carcinoma, 3) with gastric carcinoma at enrollment, and 4) those diagnosed with severe or systemic diseases. We made this  We defined eradication therapy as the combination of a proton-pump inhibitor and at least one antibiotic, irrespective of drug class, dose, or treatment duration. We included RCTs with a parallel-group design (comparing eradication therapy with placebo or no treatment) and any form of factorial design (comparing the effects of eradication therapy/other intervention(s) alone/a combination thereof and placebo/no treatment). For eligibility, we did not specify the minimum follow-up period, how follow-up was conducted, or how gastric carcinoma was verified. We excluded trials that reported no gastric carcinoma events in all arms. However, we included trials irrespective of sample size or whether they were stopped early for any reason, if at least one gastric carcinoma event was observed. Only trials published as full text were included. Non-peer-reviewed scholarly articles (e.g., full-text articles in conference proceedings or special issues of regular peer-reviewed journals) 6 were included if they provided detailed analytical methodologies and sufficient data to allow for our analyses. We excluded trials that were only published as conference abstracts. In the case of multiple publications from one trial, we adopted the results from the publication with the longest follow-up duration, although we considered the information from all papers.

Data Extraction
We extracted information on trial, subject, and intervention characteristics. Trial characteristics included study ID, location, setting (community vs. outpatient care), enrollment (year), target population, exclusion criteria, primary outcomes, verification of gastric cancer, and follow-up duration. Subject characteristics included the total and per-arm number of participants; mean or median age; percentage of male participants; percentage of participants with dyspepsia; baseline pre-cancerous histology; and primary, overall post-therapy, and longest follow-up eradication rates in the eradication arm. Intervention characteristics comprised the eradication algorithms used, including dose and duration. If the paper with the longest follow-up did not explicitly report these data but cited earlier publications, we consulted the

Data Synthesis
We calculated summary hazard ratios (HRs) and their 95% credible intervals (CrIs), which are the Bayesian analogues of confidence intervals (CIs), and prediction intervals (PrIs) 8,9 using a hierarchical Bayesian random-effects meta-analysis method based on multinomial likelihood and a log link for multiple competing risk outcomes [10][11][12] to account for the uncertainty derived from the small number of RCTs with varied follow-up durations and censored subjects (i.e., any failures to observe the outcome events before the end of follow-up, defined as missing outcome data [MOD]). To stabilize the meta-analytic model, we selected the contrast-based and baseline model instead of the conventional standalone contrast-based model, 13,14 jointly modeling baseline and relative hazard rates because one RCT 15 reported no censored observations in both arms. For gastric carcinoma incidence, we modeled the baseline and relative hazard rates for gastric carcinoma events, non-gastric carcinoma deaths, and MOD, as mutually exclusive competing risk outcomes and their respective random-effect parameters independently in a single analysis. We assumed that hazards were constant over time (i.e., proportional hazards) for each outcome and that no cases of gastric carcinoma later died from a cause other than gastric carcinoma. For analyzing gastric carcinoma-specific and non-gastric carcinoma mortality, the model was applied for deaths from gastric carcinoma, deaths from all other causes, and MOD as competing risk outcomes. Likewise, we simultaneously modeled deaths from all causes and MOD for the analysis of all-cause mortality.
In the main analysis, the meta-analysis included only RCTs that observed at least one event for each outcome of interest. Specifically, we included all seven RCTs that reported at least one respective event for the meta-analysis of gastric carcinoma incidence; the meta-analysis of gastric carcinoma-specific mortality was based on only three RCTs with at least one such event; and the meta-analyses of non-gastric carcinoma mortality and all-cause mortality were based on five RCTs with at least one respective event for these outcomes. We also calculated the summary HRs of four outcomes each (i.e., gastric carcinoma-specific mortality, non-gastric carcinoma mortality, and all-cause mortality), based on all seven RCTs regardless of events observed as sensitivity analysis; the contrast-based and baseline model allowed for the inclusion of trials with zero events for any competing risk outcomes in both arms. 13,14 In the sensitivity analysis, we calculated summary ORs for cumulative gastric carcinoma incidence based on binomial logistic regression because gastric carcinoma events are rare. 11,12,16 For MOD and non-gastric carcinoma deaths, we performed two alternative analytical approaches: 17 1) a two-stage approach based on a standard hierarchical Bayesian meta-analytic model and "deterministic" analytical methods, 18 and 2) hierarchical Bayesian meta-analytic models directly allowing for uncertainty due to missing data. 19 Regarding non-gastric carcinoma deaths, we used two alternative analysis sets. First, we considered non-gastric carcinoma deaths as zero events and only considered censored cases as MOD. We then considered cases who died from non-gastric carcinoma in addition to censored subjects as MOD, assuming that subjects who died from other causes had remained at risk of developing gastric carcinoma and were comparable to censored subjects.
For the standard two-stage approach, we used "complete case analysis" as the primary analytical method.
All participants with MOD were excluded from the study, assuming that they were missing at random. 17,18 We then used the "last observation carried forward" method by imputing zero events for subjects with MOD. We performed another set of sensitivity analyses by imputing, in each arm, the same incidence of gastric carcinoma for subjects with MOD as that in the "complete case" analysis population in the same arm, assuming a common gastric carcinoma incidence regardless of the reasons for MOD.
For the meta-analytic models directly taking uncertainty into account, we based the analysis on all available information without relying on deterministic analytical assumptions. In the main analysis, because gastric carcinoma events are rare even in highly prevalent regions, we used, as recommended, 19 an informative beta (4.885, 195.555) prior distribution on the probability of an event for those with MOD, based on the gastric carcinoma incidence rates for trial participants in the control group and those for H. person-years) 20 ). In the sensitivity analysis, we used the informative missing OR. 21 In the main analysis, we used the recently proposed context-specific informative prior distributions on the between-trial standard deviations (tau) for outcomes comparing a pharmacological intervention with no treatment. 22 The context-specific informative priors consist of a set of data-based predictive distributions for heterogeneity, which are reported as lognormal distribution for 80 different settings (defined by type of outcome and type of intervention comparisons). 21 These 80 distributions are derived from over 14,000 existing meta-analyses of binary outcomes from nearly 2,000 systematic reviews included in the Cochrane Database of Systematic Reviews (Issue 1, 2008). Several applications of this set of informative prior distributions exist. [23][24][25][26] Specifically, for the between-trial variance (tau 2 ), we used log-normal (-3.95, 1.34 2 ) for all-cause mortality, log-normal (-3.71, 1.74 2 ) for gastric carcinoma mortality and non-gastric carcinoma mortality, log-normal (-2.99, 1.74 2 ) for MOD, and log-normal (-2.49, 1.52 2 ) for gastric carcinoma incidence. In the sensitivity analyses, we used two conventional alternative distributions: a minimally informative but still vague uniform distribution on tau in the range between 0 and 2, i.e., unif(0,2) and an "inverse-gamma" prior, namely, gamma (0.001, 0.001) prior distribution for the inverse of tau 2 . 11,16 The informative priors in the main analysis were selected after all alternative analyses had been conducted. As there were only seven RCTs, we judged that the data were insufficient to inform multiple between-trial variance parameters using conventional priors. In all analyses, we used a minimally informative but still vague uniform prior distribution, unif(0,2), for the between-trial standard deviation for baseline hazard rates for all outcomes.
We quantified between-study heterogeneity using the tau and I 2 statistics with their 95% CrIs. 27 An I 2 of >50% or >75%, respectively, suggests intermediate or high heterogeneity. 28 This interpretation, however,  29 For each model in the Bayesian meta-analysis, we based results on 3 different chains and 100,000 iterations (i.e., 300,000 total iterations) after a burn-in of 100,000 iterations. We considered nodes to have converged when the Brooks-Gelman-Rubin statistic was <1.01. 30 We estimated the residual deviance for assessing model fit. For example, we considered a model with residual deviance of ≤42 (unconstrained data points based on 7 RCTs with 2 arms and 3 competing risk outcomes in the main analysis) for gastric carcinoma incidence to be a good fit to the data 12, 31 We compared alternative models using the deviance information criterion (DIC) 12,31 and deemed a difference in DIC scores >5 to be important. 31 To explore differences in preventive effects between research settings, we performed post-hoc subgroup analyses of trials from East Asia (vs. non-East Asian countries), those conducted in the community (vs. outpatient settings), and of selected subjects with specific histologic subtypes (vs. not).

Goodness of Model Fit
In general, all sets of the Bayesian meta-analytic models, except those based on the inverse gamma prior for tau 2 , had residual deviance statistics that were comparable to the number of data points (e.g., 42 in the main analysis for gastric carcinoma incidence), suggesting a good model fit (Supplementary Table 4).
Although the models with vague uniform priors for tau in general had smaller residual deviance statistics than those of the informative priors, the differences were <1.5. Based on the DIC for the observed event data, models with the informative prior distributions were deemed to be the comparably best-fitting models (Supplementary Table 4). The differences between the highest and lowest DICs across the alternative prior distributions for the between-trial variance, however, were again generally <5, suggesting no definitively preferred selection (Supplementary Table 4).  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  In the sensitivity analyses for gastric carcinoma incidence based on the conventional Bayesian meta-analysis for binary outcomes, all sets of the meta-analytic models had residual deviance statistics for the observed events that were comparable to the unconstrained data points, suggesting good model fit (Supplementary Table 5). Although the models directly accounting for MOD in general had smaller residual deviance statistics than those based on the 2-step approach using the deterministic analytical methods, the differences were typically <3. Based on the lower DICs for the observed event data, two approaches, models directly accounting for MOD with either the informative priors or the vague uniform prior, were deemed to be the comparably best-fitting models (Supplementary Table 5). The differences between the highest and lowest DICs across the alternative prior distributions for the between-trial variance, however, were again typically <5, suggesting no definitively preferred selection. Based on the residual deviance statistics and DICs for MOD, no particular models for alternative mechanisms for data missingness were considered to outperform any other (Supplementary Table 5).  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59   Two other interventions included beta-carotene and ascorbic acid. ‡ The evaluation of gastric cancer incidence was planned before analysis; however, it was not evaluated due to early termination of the trial because of low recruitment. § Primary outcomes were not explicitly specified.

8; Appendix 2-3
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

7-8
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

Appendix 1-2
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
8 Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

8-9; Appendix 3-4
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

Risk of bias in individual studies
12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.  Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).

RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
Suppl. Tables 1 and 2 Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.

Figure 1
Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency.
14-15; Figure 1; Appendix 11-12; Suppl. Table 4 Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15).

DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).