{'fraction_non_alphanumeric': 0.018908608392768287, 'fraction_numerical': 0.004312489633438381, 'mean_word_length': 5.134282807731434, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Reporting of adjuvant breast cancer trials: when is the right time?

The article by Joensuu et al1 published in Journal of Clinical Oncology (JCO) is an example of the timely reporting of an adjuvant breast cancer trial adding oral capecitabine to standard chemotherapy. Although there is no effect in the whole trial population, subgroup analysis demonstrates a statistically significant benefit for the addition of capecitabine in triple-negative patients, an interesting result first presented at the American Society of Clinical Oncology Annual Meeting in Chicago, IL, in 2010.2 However, this is not the first time the Finland Capecitabine Trial, also known as FinXX, has been presented. It was reported in full in Lancet Oncology in 2009,3 and at that point, capecitabine showed a benefit for the whole population. How can the result of a trial change? Has it really changed, or was the earlier report simply premature? The most likely conclusion is the latter, which raises questions about the right time to report trial results. 
 
As a lead clinician on adjuvant and neoadjuvant breast cancer trials over the past 15 years,4,5 I have slowly and rather reluctantly (on my part) been schooled in patient perseverance, not only with regard to what is required to complete large trials, but also in terms of waiting for that all-important first analysis. Gregory et al6 published on the dangers of early reporting in a fascinating analysis of adjuvant breast cancer data and demonstrated the misleading results of early and repeated analyses. Only as time passed and follow-up matured did the survival curves become stable and provide a robust estimate of progression-free (PFS) and overall survival (OS). Is that what has happened here? Were the initial positive data simply the results of a few random events overly influencing the curves? If so, how do we assess the right time to report and incorporate results clinically? 
 
In adjuvant breast cancer trials, there is another complication resulting from the enrollment of patients with different subtypes of disease associated with different natural histories. This may be more widespread in breast as opposed to other cancers. Blows et al7 have, in an elegantly simplified analysis using immunohistochemistry in more than 10,000 breast cancers, demonstrated how different these populations are with regard to the shapes of their PFS and OS curves. After publication of these data, the group is now using the same immunohistochemistry set to examine the NEAT (National Epirubicin Adjuvant Trial)4 translational tumor bank. We are particularly interested in investigating when adjuvant chemotherapy has maximum effect (benefit) in the various subgroups. Just as the PFS and OS curves have different shapes (early fall and then leveling off in high-risk populations, compared with slow and steady decline in better-risk populations), so it has been shown by Berry et al8 that the differential benefit of additional chemotherapy is seen earlier in high-risk populations. Analysis of the type described will require repetition with longer follow-up, because only then will the long-term benefit of the treatment to the whole breast cancer population be apparent. Analyzing the different subgroups and the differential, time-dependent effects of chemotherapy will require collaborative meta-analysis to achieve the necessary numbers. For clinical trialists, this suggests that the accrual of patients with subtypes of breast cancer should be preplanned and adequately powered prospectively to allow independent analyses. Alternatively, clinical trials should be restricted to specific subtypes. 
 
The enrollment of patients from different subgroups that experience differences in the timing of the effects of chemotherapy could indeed be an explanation here. In the earlier analysis of the FinXX study,3 events were more likely in the high-risk population, and therefore, early reporting would contain more information from the high-risk population. This is borne out by the subgroup analysis in the triple-negative population in the present report,1 which does continue to show benefit for the addition of capecitabine. In summary, there is a risk in reporting trials too early that a positive result may simply be either the play of chance or the emergence of a predominant effect/benefit in a high-risk early-relapsing population, and clinical trialists and statisticians need to consider these issues prospectively as they plan trials and their analyses and reporting. 
 
We must applaud the authors as well as JCO for publishing what is now a trial with an essentially negative result. Whatever is stated in editorials and review articles, there remains a strong bias for positive-results reporting, whereas equally significant but negative results continue to face publication challenges. We should acknowledge the temptation to look early and publish quickly if results are positive, but trialists should resist this, as should journals. 
 
It is clear that timely reporting of large randomized phase III adjuvant breast cancer trials can be an ethical imperative when life-saving treatment may be made available earlier, but we have an equal imperative to avoid the harm that would occur from broad adoption of what are ultimately shown to be ineffective therapies. The right time for that important first analysis must be decided carefully on an individual trial basis, by chief and principal investigators and biostatisticians working on the trial. In addition, we should recognize that the current biostatistical concern is simply another manifestation of our increased understanding of the molecular biology and natural histories of the several common breast cancer subtypes. If we acknowledge that they represent different diseases with different natural histories, we can then plan to analyze treatment effects in subtype-specific ways, which will generally be at different time points. At the same time, the reporting of negative results should be encouraged.