Recognition of early mortality in multiple myeloma by a prediction matrix

dc.contributor.authorTerebelo, Howard
dc.contributor.authorSrinivasan, Shankar
dc.contributor.authorNarang, Mohit
dc.contributor.authorAbonour, Rafat
dc.contributor.authorGasparetto, Cristina
dc.contributor.authorToomey, Kathleen
dc.contributor.authorHardin, James W.
dc.contributor.authorLarkins, Gail
dc.contributor.authorKitali, Amani
dc.contributor.authorRifkin, Robert M.
dc.contributor.authorShah, Jatin J.
dc.contributor.departmentDepartment of Medicine, IU School of Medicineen_US
dc.date.accessioned2017-07-27T18:10:47Z
dc.date.available2017-07-27T18:10:47Z
dc.date.issued2017
dc.description.abstractEarly mortality (EM; death ≤ 6 months from diagnosis) has been reported in several newly diagnosed multiple myeloma (NDMM) trials. Before the era of novel agents, the incidence was 10%-14%. Causes of death included infections/pneumonia, renal failure, refractory disease, and cardiac events. Staging systems, such as the revised International Staging System (r-ISS), and prognostic factors including cytogenetics, lactate dehydrogenase levels, and myeloma-specific factors, are useful to assess overall prognosis; however, they cannot predict EM. We evaluated patients treated with novel agents in the Connect MM® Registry and identified risk factors of the EM cohort. Eligible patients were enrolled in the registry within 60 days of diagnosis. Univariate and multivariate analyses were conducted to evaluate associations between baseline characteristics and EM. Prediction matrices for EM were constructed from a logistic model. Between September 2009 and December 2011, 1493 patients were enrolled in the registry and had adequate follow-up. Of these patients, 102 (6.8%) had EM and 1391 (93.2%) survived for > 180 days. Baseline factors significantly associated with increased EM risk included age > 75 years, higher Eastern Cooperative Oncology Group performance status, lower EQ-5D mobility score, higher ISS stage, lower platelet count, and prior hypertension. Renal insufficiency trended toward increased EM risk. These risk factors were incorporated into a prediction matrix for EM. The EM prediction matrix uses differential weighting of risk factors to calculate EM risk in patients with NDMM. Identifying patients at risk for EM may provide new opportunities to implement patient-specific treatment strategies to improve outcomes.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.citationTerebelo, H., Srinivasan, S., Narang, M., Abonour, R., Gasparetto, C., Toomey, K., Hardin, J. W., Larkins, G., Kitali, A., Rifkin, R. M. and Shah, J. J. (2017), Recognition of early mortality in multiple myeloma by a prediction matrix. American Journal of Hematology. Accepted Author Manuscript. doi:10.1002/ajh.24796en_US
dc.identifier.urihttps://hdl.handle.net/1805/13625
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.isversionof10.1002/ajh.24796en_US
dc.relation.journalAmerican Journal of Hematologyen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.sourcePublisheren_US
dc.subjectearly mortalityen_US
dc.subjectmultiple myelomaen_US
dc.subjectprediction matricesen_US
dc.titleRecognition of early mortality in multiple myeloma by a prediction matrixen_US
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