4.3 Article

Evaluation of the Simplified Score to Predict Early Relapse in Multiple Myeloma (S-ERMM) in the MMRF CoMMpass study

Journal

LEUKEMIA RESEARCH
Volume 127, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.leukres.2023.107037

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The study validated a new risk score for identifying high-risk patients for relapse within 18 months of diagnosis and compared its predictive ability with other risk stratification systems. The results showed that the new risk score had similar predictive performance as existing systems and further studies are needed to find the optimal approach.
Background: Zaccaria and colleagues recently proposed a new risk score to identify patients at high risk for relapse within 18 months of diagnosis (ER18), the Score for Early Relapse in Multiple Myeloma (S-ERMM). We performed external validation of the S-ERMM using data from the CoMMpass study.Patients and methods: Clinical data was obtained from the CoMMpass study. Patients were assigned S-ERMM risk scores and risk categories by the three iterations of the International Staging System (ISS): ISS, R-ISS and R2-ISS. Patients with missing data or early mortality in remission were excluded. Our primary endpoint was the relative predictive ability of the S-ERMM versus other risk scores for ER18 as assessed by area-under-the-curve (AUC).Results: 476 patients had adequate data to assign all four risk scores. 65%, 25% and 10% were low, intermediate and high risk by S-ERMM. 17% experienced ER18. All four risk scores stratified patients by risk for ER18. S-ERMM (AUC: 0.59 [95% CI 0.53-0.65]) was similar to R-ISS (0.63 [95% CI 0.58-0.69]) and statistically inferior to ISS (0.68 [95% CI 0.62-0.75]) and R2-ISS (0.66 [95% CI 0.61-0.72]) for prediction of ER18. Sensitivity analyses were performed and did not significantly impact results.Conclusion: The S-ERMM risk score is not superior to existing risk stratification systems for predicting early relapse in NDMM and further studies are needed to identify the optimal approach.

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