ArticleCancer research communications2026
Leveraging AI to Evaluate Minimal Residual Disease Endpoint Surrogacy in Multiple Myeloma.
Article in Cancer research communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Minimal residual disease (MRD) has been endorsed by the FDA Oncology Drugs Advisory Committee as an endpoint for accelerated approval in multiple myeloma based on individual patient data collected from randomized trials. However, emerging data from recent trials were not included. A novel artificial intelligence (AI)-assisted framework is proposed, which automates information identification and extraction, providing up-to-date analyses that confirm moderate trial-level and strong individual patient-level associations between MRD- rates at suspected complete response (MRD-CR) and survival endpoints in multiple myeloma. Specifically, this study utilized an AI-assisted framework that identifies relevant studies and filters critical information to analyze published data via 2 independent objectives. First, we examined the trial-level association using the coefficients of determination (R2) and its 95% confidence intervals (CI) based on published statistics of treatment effects on MRD and various endpoints. Next, we generated synthetic individual patient data with covariates through AI-curated tools to estimate the individual-level association. The AI tool searched for eligible randomized clinical trials (RCT). A total of 20 two-arm comparisons from 19 RCTs were analyzed. Trial-level analysis showed an R2 of 0.71 (95% CI, 0.52-0.89) pooling disease subpopulations. Furthermore, AI techniques were applied to create synthetic individual data, combining information extracted from Kaplan-Meier curves and subgroup analyses from published literatures. Using generated synthetic data, we estimated the individual-level correlation between MRD-CR rates and progression-free survival outcomes with a bivariate copula model and calculated a global odds ratio of 7.28 (95% CI, 5.60-8.95). SIGNIFICANCE: (i) A novel AI-assisted framework is proposed, which automates information identification and extraction, providing rapid up-to-date analyses. (ii) Moderate trial-level and strong individual patient-level associations between MRD and various clinical endpoints in multiple myeloma are confirmed.
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