TY - JOUR AU1 - Hájek, Roman AU2 - Delforge, Michel AU3 - Raab, Marc S. AU4 - Schoen, Paul AU5 - DeCosta, Lucy AU6 - Spicka, Ivan AU7 - Radocha, Jakub AU8 - Pour, Ludek AU9 - Gonzalez‐McQuire, Sebastian AU1 - Bouwmeester, Walter AB - SummaryMultiple myeloma (MM) is a malignancy with varying survival outcomes and drivers of disease progression. Existing MM staging tools were developed using data from newly diagnosed patients. As patient characteristics and disease‐related factors change between diagnosis and the initiation of second‐line (2L) treatment, an unmet need exists for a tool that can evaluate risk of death at first relapse. We have developed a risk stratification algorithm (RSA) using data from patients with MM who were at 2L. Hazard ratios for independent predictors of overall survival (OS) were derived from a Cox models, and individual patient scores were calculated for total risk. K‐adaptive partitioning for survival was used to stratify patients into groups based on their scores. Relative risk doubled with ascending risk group; median OSs for patients in group 1 (lowest risk)–4 (highest risk) were 61·6, 29·6, 14·2 and 5·9 months, respectively. Differences in OS between risk groups were significant. Similar stratification was observed when the RSA was applied to an external validation data set. In conclusion, we have developed a validated RSA that can quantify total risk, frailty risk and disease aggressiveness risk, and stratify patients with MM at 2L into groups with profoundly different survival expectations. TI - Development and validation of a novel risk stratification algorithm for relapsed multiple myeloma JF - British Journal of Haematology DO - 10.1111/bjh.16105 DA - 2019-08-06 UR - https://www.deepdyve.com/lp/pubmed-central/development-and-validation-of-a-novel-risk-stratification-algorithm-9ZfVB5pDa0 SP - 447 EP - 458 VL - 187 IS - 4 DP - DeepDyve ER -