Discussion
MM
MINOR
Automated algorithms are increasingly used in clinical decision management due to their reliability and reproducibility, timely assessment of a large sample of patients, and adherence to recommended clinical practice [In this exploratory pilot study, we developed a dR algorithm to determine whether response assessment of patients with MM can be accurately performed using a limited set of laboratory measurements. The response assessments made using the dR algorithm showed strong agreement with the assessment of experienced clinicians (IRC) in a clinical trial setting. In addition, the robustness of the algorithm was demonstrated via a sensitivity analysis, with the exclusion of 75% of urine M protein measurements and 50% of other laboratory measurements resulting in only a minor reduction in the algorithm’s accuracy in assessing the number of patients with ≥PR (discordance observed in 26/291 patients, compared with 16/291 when using all measurements). This suggests that, in the clinical setting, where laboratory measurements are often reported at a lower frequency than in trials [If further validated within other clinical trial and/or RWD cohorts, the dR algorithm proposed here could be used as a robust tool to derive response status for patients with MM in RWD databases. It overcomes the limitations of EHR-captured responses, where large discrepancies between studies with regards to the criteria used for response determination have been reported [Using the dR algorithm we accurately reproduced the analysis of efficacy in the phase III BELLINI trial when considering overall response rate and ≥VGPR. This lays the foundations for dR to be used as a real-world endpoint in single-arm clinical studies to help accelerate drug development in MM. Recent guidance from the US Food and Drug Administration (FDA) recognizes the potential use of RWD as a comparator arm in an externally controlled trial [Overall survival is the standard endpoint used in oncology clinical trials to assess treatment efficacy of newly developed drugs. An attractive alternative to overall survival is overall response rate, which offers the possibility of earlier assessment with smaller cohort sizes, and is generally based on objective and quantitative assessment. One challenge raised by the FDA in relation to overall response rate is that it may not always relate well to overall survival [Although the algorithm was assessed in both a clinical trial and a large RWD cohort, some questions require further investigation. It is unclear whether certain treatment groups, the time stratification by two years, or the underlying mode of action of the therapies might have had an influence on the association between dR and overall survival. It is also possible that bias may have been introduced into the sensitivity analysis by assuming missing data occurs at random; in EHRs missingness is more often informative (i.e. the chance of missing data may be directly linked to the unobserved value itself [Here, we have shown that our newly developed dR algorithm based on flexible IMWG criteria can consistently reproduce response assessments for patients with MM in a clinical trial setting, and can also assess response status for a real-world patient cohort. With further validation in other real-world and clinical trial populations and with other degrees and mechanisms of missing data, dR has the potential to be used as an endpoint in real-world studies and as an endpoint in external comparator cohorts in the clinical trial setting.