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Managing Multiple Myeloma in Older Adults Using Real World Evidence and Clinical Integration of a Geriatric Assessment Tool in Clinical Practice


 Background: Over two thirds of patients with Multiple Myeloma (MM) are ≥ 65 years old at the time of diagnosis. Older adults are at greater risk for treatment related toxicity and inferior survival; such risks are inadequately explained by chronologic age and performance status. In 2015, the International Myeloma Working Group (IMWG) proposed a geriatric assessment (GA) based frailty index to identify older adults with MM at greatest risk of toxicities. Yet, routine implementation of GA in busy oncology practice remains challenging. We have previously shown the feasibility of a tablet-based modified Geriatric Assessment (mGA), capturing the Charlson Comorbidity Index (CCI), Katz Activity of Daily Living (ADL) Score, and Lawton Instrumental Activity of Daily Living (IADL) score, and its impact on clinical decision-making and treatment outcomes (Nathwani, et al. JOP. 2020). In the prior study, physicians recommended integration of the mGA into the electronic medical record (EMR) to improve usefulness at the clinic.
 Methods: We conducted a single institution pilot study to test the feasibility of integrating an electronic care planning system within the EMR such that with a single sign on, the dashboard showing results of the mGA was visualized within the EMR. Eligible patients had symptomatic MM, > 60 years old, and seeing their oncology providers to make a decision about treatment. After completing informed consent, patients completed a tablet-based mGA in clinic just prior to seeing the physician. Survey results were compiled and were immediately available for evaluation on a dashboard within the EMR. Providers reviewed the mGA results before meeting with the patient and completed a short survey after the visit regarding their own subjective impression of frailty and how the mGA influenced their treatment decision making. Agreement between provider's subjective vs mGA based frailty categorization was measured using Cohen's Kappa statistic. We measured relevant toxicity outcomes at 3 months post treatment initiation.
 Results: 25 patients were enrolled, with a median age of 68 (range=61-82), 52% (n=13) female, and 68% (n= 17) white. One patient did not complete the mGA survey and was not included in the analysis. The remaining patients completed the mGA successfully without interrupting clinic flow and mGA was immediately available for providers to review during the clinic visit. The average time providers spent reviewing results was of 5 (range 1-10) minutes. Providers subjectively categorized patients as 42% (n=10) fit, 58% (n=14) intermediate fit, and 0% (n=0) frail. According to the mGA, patients were 50% (n=12) fit, 29% (n=7) intermediate fit, and 21% (n=5) frail. There was an overall 46% (n=11) concordance between physician and mGA result. The most agreement was in fit status (58%, n=7) and least was frail (0%, n=0). There was 33% (n=4) agreement on intermediate fit status. The unweighted Cohen's kappa statistic was 0.09 indicating only slight agreement between the two methods. Providers reported mGA influenced their treatment decision in 33% (n=8), with the decision being either chemotherapy modification (n=6) or reduced dose transplant (n=2). One patient, who was frail and received induction treatment, died during the 3-month study period. The remaining patients (n=23) received treatment as planned.
 Discussion: In this study, we report the feasibility of an EMR integrated mGA tool completed by the patient prior to meeting with the physician. Patients completed the survey with assistance and without disrupting the clinic workflow. The mGA results were reviewed by providers in real time and influenced treatment decisions one third of the time. Nearly all patients (96%, n=24) completed therapy as planned. Providers tended to view the patients as more fit than the mGA result, suggesting that the mGA uncovers additional information related to the patient's ability to tolerate therapy. Toxicity follow up is ongoing and will be updated at the time of presentation.
 
 
 Giri: CareVive: Honoraria, Research Funding; PackHealth: Research Funding. Costa: BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Karyopharm: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Speakers Bureau.
