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Recognition of early mortality in multiple myeloma by a prediction matrix.

Publication ,  Journal Article
Terebelo, H; Srinivasan, S; Narang, M; Abonour, R; Gasparetto, C; Toomey, K; Hardin, JW; Larkins, G; Kitali, A; Rifkin, RM; Shah, JJ
Published in: Am J Hematol
September 2017

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.

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Published In

Am J Hematol

DOI

EISSN

1096-8652

Publication Date

September 2017

Volume

92

Issue

9

Start / End Page

915 / 923

Location

United States

Related Subject Headings

  • Survival Rate
  • Registries
  • Pneumonia
  • Platelet Count
  • Multiple Myeloma
  • Middle Aged
  • Male
  • L-Lactate Dehydrogenase
  • Infections
  • Immunology
 

Citation

APA
Chicago
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Terebelo, H., Srinivasan, S., Narang, M., Abonour, R., Gasparetto, C., Toomey, K., … Shah, J. J. (2017). Recognition of early mortality in multiple myeloma by a prediction matrix. Am J Hematol, 92(9), 915–923. https://doi.org/10.1002/ajh.24796
Terebelo, Howard, Shankar Srinivasan, Mohit Narang, Rafat Abonour, Cristina Gasparetto, Kathleen Toomey, James W. Hardin, et al. “Recognition of early mortality in multiple myeloma by a prediction matrix.Am J Hematol 92, no. 9 (September 2017): 915–23. https://doi.org/10.1002/ajh.24796.
Terebelo H, Srinivasan S, Narang M, Abonour R, Gasparetto C, Toomey K, et al. Recognition of early mortality in multiple myeloma by a prediction matrix. Am J Hematol. 2017 Sep;92(9):915–23.
Terebelo, Howard, et al. “Recognition of early mortality in multiple myeloma by a prediction matrix.Am J Hematol, vol. 92, no. 9, Sept. 2017, pp. 915–23. Pubmed, doi:10.1002/ajh.24796.
Terebelo H, Srinivasan S, Narang M, Abonour R, Gasparetto C, Toomey K, Hardin JW, Larkins G, Kitali A, Rifkin RM, Shah JJ. Recognition of early mortality in multiple myeloma by a prediction matrix. Am J Hematol. 2017 Sep;92(9):915–923.
Journal cover image

Published In

Am J Hematol

DOI

EISSN

1096-8652

Publication Date

September 2017

Volume

92

Issue

9

Start / End Page

915 / 923

Location

United States

Related Subject Headings

  • Survival Rate
  • Registries
  • Pneumonia
  • Platelet Count
  • Multiple Myeloma
  • Middle Aged
  • Male
  • L-Lactate Dehydrogenase
  • Infections
  • Immunology