Development of a prognostic model for overall survival in multiple myeloma using the Connect® MM Patient Registry
Summary Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient characteristics. Current models use data from selected clinical trial populations, which prevent application to patients in an unselected co...
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| Published in | British journal of haematology Vol. 187; no. 5; pp. 602 - 614 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Blackwell Publishing Ltd
01.12.2019
John Wiley and Sons Inc |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Summary
Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient characteristics. Current models use data from selected clinical trial populations, which prevent application to patients in an unselected community setting that reflects routine clinical practice. Using data from the Connect® MM Registry, a large, US, multicentre, prospective observational cohort study (Cohort 1: 2009–2011; Cohort 2: 2012–2016) of 3011 patients with NDMM, we identified prognostic variables for OS via the multivariable analysis of baseline patient characteristics in Cohort 1 (n = 1493) and developed a tool to examine individual outcomes. Factors associated with OS (n = 1450 treated patients; P < 0·05) were age, del(17p), triplet therapy use, EQ‐5D mobility, International Staging System stage, solitary plasmacytoma, history of diabetes, platelet count, Eastern Cooperative Oncology Group performance status and serum creatinine, which were used to create survival matrices for 3‐ and 5‐year OS. The model was internally and externally validated using Connect MM Cohort 2 (Harrell's concordance index, 0·698), MM‐015 (0·649), and the phase 3 FIRST (0·647) clinical trials. This novel prognostic tool may help inform outcomes for NDMM in the era of triplet therapy use with novel agents. |
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| AbstractList | Summary
Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient characteristics. Current models use data from selected clinical trial populations, which prevent application to patients in an unselected community setting that reflects routine clinical practice. Using data from the Connect
®
MM Registry, a large, US, multicentre, prospective observational cohort study (Cohort 1: 2009–2011; Cohort 2: 2012–2016) of 3011 patients with NDMM, we identified prognostic variables for OS via the multivariable analysis of baseline patient characteristics in Cohort 1 (
n
= 1493) and developed a tool to examine individual outcomes. Factors associated with OS (
n
= 1450 treated patients;
P
< 0·05) were age, del(17p), triplet therapy use, EQ‐5D mobility, International Staging System stage, solitary plasmacytoma, history of diabetes, platelet count, Eastern Cooperative Oncology Group performance status and serum creatinine, which were used to create survival matrices for 3‐ and 5‐year OS. The model was internally and externally validated using Connect MM Cohort 2 (Harrell's concordance index, 0·698), MM‐015 (0·649), and the phase 3 FIRST (0·647) clinical trials. This novel prognostic tool may help inform outcomes for NDMM in the era of triplet therapy use with novel agents. Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient characteristics. Current models use data from selected clinical trial populations, which prevent application to patients in an unselected community setting that reflects routine clinical practice. Using data from the Connect ® MM Registry, a large, US, multicentre, prospective observational cohort study (Cohort 1: 2009–2011; Cohort 2: 2012–2016) of 3011 patients with NDMM, we identified prognostic variables for OS via the multivariable analysis of baseline patient characteristics in Cohort 1 ( n = 1493) and developed a tool to examine individual outcomes. Factors associated with OS ( n = 1450 treated patients; P < 0·05) were age, del(17p), triplet therapy use, EQ‐5D mobility, International Staging System stage, solitary plasmacytoma, history of diabetes, platelet count, Eastern Cooperative Oncology Group performance status and serum creatinine, which were used to create survival matrices for 3‐ and 5‐year OS. The model was internally and externally validated using Connect MM Cohort 2 (Harrell's concordance index, 0·698), MM‐015 (0·649), and the phase 3 FIRST (0·647) clinical trials. This novel prognostic tool may help inform outcomes for NDMM in the era of triplet therapy use with novel agents. Summary Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient characteristics. Current models use data from selected clinical trial populations, which prevent application to patients in an unselected community setting that reflects routine clinical practice. Using data from the Connect® MM Registry, a large, US, multicentre, prospective observational cohort study (Cohort 1: 2009–2011; Cohort 2: 2012–2016) of 3011 patients with NDMM, we identified prognostic variables for OS via the multivariable analysis of baseline patient characteristics in Cohort 1 (n = 1493) and developed a tool to examine individual outcomes. Factors associated with OS (n = 1450 treated patients; P < 0·05) were age, del(17p), triplet therapy use, EQ‐5D mobility, International Staging System stage, solitary plasmacytoma, history of diabetes, platelet count, Eastern Cooperative Oncology Group performance status and serum creatinine, which were used to create survival matrices for 3‐ and 5‐year OS. The model was internally and externally validated using Connect MM Cohort 2 (Harrell's concordance index, 0·698), MM‐015 (0·649), and the phase 3 FIRST (0·647) clinical trials. This novel prognostic tool may help inform outcomes for NDMM in the era of triplet therapy use with novel agents. Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient characteristics. Current models use data from selected clinical trial populations, which prevent application to patients in an unselected community setting that reflects routine clinical practice. Using data from the Connect® MM Registry, a large, US, multicentre, prospective observational cohort study (Cohort 1: 2009–2011; Cohort 2: 2012–2016) of 3011 patients with NDMM, we identified prognostic variables for OS via the multivariable analysis of baseline patient characteristics in Cohort 1 (n = 1493) and developed a tool to examine individual outcomes. Factors associated with OS (n = 1450 treated patients; P < 0·05) were age, del(17p), triplet therapy use, EQ‐5D mobility, International Staging System stage, solitary plasmacytoma, history of diabetes, platelet count, Eastern Cooperative Oncology Group performance status and serum creatinine, which were used to create survival matrices for 3‐ and 5‐year OS. The model was internally and externally validated using Connect MM Cohort 2 (Harrell's concordance index, 0·698), MM‐015 (0·649), and the phase 3 FIRST (0·647) clinical trials. This novel prognostic tool may help inform outcomes for NDMM in the era of triplet therapy use with novel agents. Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient characteristics. Current models use data from selected clinical trial populations, which prevent application to patients in an unselected community setting that reflects routine clinical practice. Using data from the Connect MM Registry, a large, US, multicentre, prospective observational cohort study (Cohort 1: 2009-2011; Cohort 2: 2012-2016) of 3011 patients with NDMM, we identified prognostic variables for OS via the multivariable analysis of baseline patient characteristics in Cohort 1 (n = 1493) and developed a tool to examine individual outcomes. Factors associated with OS (n = 1450 treated patients; P < 0·05) were age, del(17p), triplet therapy use, EQ-5D mobility, International Staging System stage, solitary plasmacytoma, history of diabetes, platelet count, Eastern Cooperative Oncology Group performance status and serum creatinine, which were used to create survival matrices for 3- and 5-year OS. The model was internally and externally validated using Connect MM Cohort 2 (Harrell's concordance index, 0·698), MM-015 (0·649), and the phase 3 FIRST (0·647) clinical trials. This novel prognostic tool may help inform outcomes for NDMM in the era of triplet therapy use with novel agents. |
| Author | Wagner, Lynne Agarwal, Amit Narang, Mohit Terebelo, Howard R. Flick, E. Dawn Yue, Lihua Durie, Brian G. M. Abonour, Rafat Toomey, Kathleen Jagannath, Sundar Hardin, James W. Srinivasan, Shankar Kitali, Amani Rifkin, Robert M. Gasparetto, Cristina J. |
| AuthorAffiliation | 5 Cedars‐Sinai Medical Center Los Angeles CA USA 8 Wake Forest School of Medicine Winston‐Salem NC USA 7 Mount Sinai Hospital New York NY USA 4 Steeplechase Cancer Center Somerville NJ USA 6 University of South Carolina Columbia SC USA 11 Rocky Mountain Cancer Centers US Oncology Denver CO USA 3 Duke University Medical Center Durham NC USA 2 Indiana University Indianapolis IN USA 10 Celgene Corporation Summit NJ USA 9 US Oncology Research Columbia MD USA 1 Providence Cancer Institute Southfield MI USA |
| AuthorAffiliation_xml | – name: 3 Duke University Medical Center Durham NC USA – name: 4 Steeplechase Cancer Center Somerville NJ USA – name: 1 Providence Cancer Institute Southfield MI USA – name: 5 Cedars‐Sinai Medical Center Los Angeles CA USA – name: 8 Wake Forest School of Medicine Winston‐Salem NC USA – name: 9 US Oncology Research Columbia MD USA – name: 11 Rocky Mountain Cancer Centers US Oncology Denver CO USA – name: 7 Mount Sinai Hospital New York NY USA – name: 10 Celgene Corporation Summit NJ USA – name: 2 Indiana University Indianapolis IN USA – name: 6 University of South Carolina Columbia SC USA |
| Author_xml | – sequence: 1 givenname: Howard R. orcidid: 0000-0002-4208-2353 surname: Terebelo fullname: Terebelo, Howard R. email: hiccup@comcast.net organization: Providence Cancer Institute – sequence: 2 givenname: Rafat surname: Abonour fullname: Abonour, Rafat organization: Indiana University – sequence: 3 givenname: Cristina J. surname: Gasparetto fullname: Gasparetto, Cristina J. organization: Duke University Medical Center – sequence: 4 givenname: Kathleen surname: Toomey fullname: Toomey, Kathleen organization: Steeplechase Cancer Center – sequence: 5 givenname: Brian G. M. surname: Durie fullname: Durie, Brian G. M. organization: Cedars‐Sinai Medical Center – sequence: 6 givenname: James W. surname: Hardin fullname: Hardin, James W. organization: University of South Carolina – sequence: 7 givenname: Sundar surname: Jagannath fullname: Jagannath, Sundar organization: Mount Sinai Hospital – sequence: 8 givenname: Lynne surname: Wagner fullname: Wagner, Lynne organization: Wake Forest School of Medicine – sequence: 9 givenname: Mohit surname: Narang fullname: Narang, Mohit organization: US Oncology Research – sequence: 10 givenname: E. Dawn surname: Flick fullname: Flick, E. Dawn organization: Celgene Corporation – sequence: 11 givenname: Shankar surname: Srinivasan fullname: Srinivasan, Shankar organization: Celgene Corporation – sequence: 12 givenname: Lihua surname: Yue fullname: Yue, Lihua organization: Celgene Corporation – sequence: 13 givenname: Amani surname: Kitali fullname: Kitali, Amani organization: Celgene Corporation – sequence: 14 givenname: Amit surname: Agarwal fullname: Agarwal, Amit organization: Celgene Corporation – sequence: 15 givenname: Robert M. orcidid: 0000-0003-3141-1518 surname: Rifkin fullname: Rifkin, Robert M. organization: Rocky Mountain Cancer Centers US Oncology |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31382320$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1007_s00277_021_04484_1 crossref_primary_10_3389_fonc_2022_922039 crossref_primary_10_1111_ijlh_13717 crossref_primary_10_1002_cam4_2656 crossref_primary_10_3389_fonc_2022_805702 crossref_primary_10_1038_s41375_021_01286_2 crossref_primary_10_1155_2022_3050199 crossref_primary_10_1002_ajh_27207 crossref_primary_10_1021_acsomega_2c04212 crossref_primary_10_1186_s12957_024_03453_y crossref_primary_10_1016_j_clml_2024_05_021 crossref_primary_10_1371_journal_pone_0285947 |
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Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient... Median overall survival (OS) has improved for patients with newly diagnosed multiple myeloma (NDMM), but prognosis varies depending on baseline patient... |
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| SubjectTerms | Clinical trials Creatinine Diabetes mellitus Haematological Malignancy Hematology matrix Medical prognosis Multiple myeloma myeloma Oncology Patients Plasmacytoma prognosis registry Research Paper Survival |
| Title | Development of a prognostic model for overall survival in multiple myeloma using the Connect® MM Patient Registry |
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