Cargando…
Recognition of early mortality in multiple myeloma by a prediction matrix
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...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5601204/ https://www.ncbi.nlm.nih.gov/pubmed/28543165 http://dx.doi.org/10.1002/ajh.24796 |
_version_ | 1783264348790063104 |
---|---|
author | 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. |
author_facet | 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. |
author_sort | Terebelo, Howard |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5601204 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-56012042017-10-03 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. Am J Hematol Research Articles 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. John Wiley and Sons Inc. 2017-07-19 2017-09 /pmc/articles/PMC5601204/ /pubmed/28543165 http://dx.doi.org/10.1002/ajh.24796 Text en © 2017 The Authors American Journal of Hematology Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles 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. Recognition of early mortality in multiple myeloma by a prediction matrix |
title | Recognition of early mortality in multiple myeloma by a prediction matrix |
title_full | Recognition of early mortality in multiple myeloma by a prediction matrix |
title_fullStr | Recognition of early mortality in multiple myeloma by a prediction matrix |
title_full_unstemmed | Recognition of early mortality in multiple myeloma by a prediction matrix |
title_short | Recognition of early mortality in multiple myeloma by a prediction matrix |
title_sort | recognition of early mortality in multiple myeloma by a prediction matrix |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5601204/ https://www.ncbi.nlm.nih.gov/pubmed/28543165 http://dx.doi.org/10.1002/ajh.24796 |
work_keys_str_mv | AT terebelohoward recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT srinivasanshankar recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT narangmohit recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT abonourrafat recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT gasparettocristina recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT toomeykathleen recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT hardinjamesw recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT larkinsgail recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT kitaliamani recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT rifkinrobertm recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix AT shahjatinj recognitionofearlymortalityinmultiplemyelomabyapredictionmatrix |