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Recognition of early mortality in multiple myeloma by a prediction matrix.
Terebelo, Howard; Srinivasan, Shankar; Narang, Mohit; Abonour, Rafat; Gasparetto, Cristina; Toomey, Kathleen; Hardin, James W; Larkins, Gail; Kitali, Amani; Rifkin, Robert M; Shah, Jatin J.
Afiliação
  • Terebelo H; Providence Cancer Center, Southfield, Michigan.
  • Srinivasan S; Celgene Corporation, Summit, New Jersey.
  • Narang M; Maryland Oncology Hematology, Columbia, Maryland.
  • Abonour R; Indiana University Simon Cancer Center, Indianapolis, Indiana.
  • Gasparetto C; Division of Cellular Therapy, Duke University Medical Center, Durham, North Carolina.
  • Toomey K; Steeplechase Cancer Center, Somerville, New Jersey.
  • Hardin JW; University of South Carolina, Columbia, South Carolina.
  • Larkins G; Celgene Corporation, Summit, New Jersey.
  • Kitali A; Celgene Corporation, Summit, New Jersey.
  • Rifkin RM; US Oncology Research, Rocky Mountain Cancer Centers, Denver, Colorado.
  • Shah JJ; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Am J Hematol ; 92(9): 915-923, 2017 Sep.
Article em En | MEDLINE | ID: mdl-28543165
ABSTRACT
Early 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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores Tumorais / Sistema de Registros / Mieloma Múltiplo Tipo de estudo: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: Am J Hematol Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores Tumorais / Sistema de Registros / Mieloma Múltiplo Tipo de estudo: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: Am J Hematol Ano de publicação: 2017 Tipo de documento: Article