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 -