Explore the Prognostic Factors of Survival Outcomes in Newly Diagnosed Multiple Myeloma Who Are Not Transplant Eligible
Author(s)
Xiwu Lin, PhD1, Eric M. Ammann, PhD2, MARJORIE NOBREGA, BA, MBA2, Annette Lam, MS3, Jianming He, PhD2.
1Johnson & Johnson, Horsham, PA, USA, 2Johnson & Johnson, Raritan, NJ, USA, 3Johnson & Johnson, Toronto, ON, Canada.
1Johnson & Johnson, Horsham, PA, USA, 2Johnson & Johnson, Raritan, NJ, USA, 3Johnson & Johnson, Toronto, ON, Canada.
Presentation Documents
OBJECTIVES: Traditionally, a few baseline covariates have been considered potential prognostic factors (PFs) associated with progression free survival (PFS) and overall survival (OS) in transplant ineligible patients (TIE) with newly diagnosed multiple myeloma (NDMM). However, empirical evidence is lacking. This study aims to identify PFs based on individual patient level data (IPD) from randomized controlled trials (RCTs).
METHODS: The pooled IPD of MAIA, CEPHEUS, and ALCYONE were included. A frailty Cox model was used to examine the relationship between each potential PF with outcomes one at a time; PFs included age, gender, International Staging System score (ISS), cytogenetic risk, type of MM, ECOG performance score, simplified frailty score (frailty), extramedullary disease (EMD), bone disease, race, time from diagnosis, and lab value, e.g., creatinine clearance, hemoglobin, albumin, lactate dehydrogenase (LDH), serum calcium levels, and hepatic function (ALT & AST). The model considered study as a random effect, and the potential PF as a fixed effect. Potential PFs were included as categorical variables.
RESULTS: A total of 1,731 patients from ALCYONE 706, MAIA 737 and CEPHEUS 288 were analyzed. Mean (std. dev.) age was 72.6 (5.78), 50.4% of patients were male, and 10.2% of patients were from the US. Age, ECOG, ISS, type of myeloma, cytogenetic risk, hemoglobin, albumin, LDH, AST, calcium, frailty, and EMD significantly predicted PFS. In addition, sex, baseline creatinine clearance, and ALT were significant for OS. Race, bone disease, and time from diagnosis were not significant for either outcome.
CONCLUSIONS: Findings from this study confirms the prognostic value of many baseline covariates traditionally considered to be prognostic of PFS and OS in the TIE NDMM setting. Those results can be considered in future subgroup analyses or indirect treatment comparisons.
METHODS: The pooled IPD of MAIA, CEPHEUS, and ALCYONE were included. A frailty Cox model was used to examine the relationship between each potential PF with outcomes one at a time; PFs included age, gender, International Staging System score (ISS), cytogenetic risk, type of MM, ECOG performance score, simplified frailty score (frailty), extramedullary disease (EMD), bone disease, race, time from diagnosis, and lab value, e.g., creatinine clearance, hemoglobin, albumin, lactate dehydrogenase (LDH), serum calcium levels, and hepatic function (ALT & AST). The model considered study as a random effect, and the potential PF as a fixed effect. Potential PFs were included as categorical variables.
RESULTS: A total of 1,731 patients from ALCYONE 706, MAIA 737 and CEPHEUS 288 were analyzed. Mean (std. dev.) age was 72.6 (5.78), 50.4% of patients were male, and 10.2% of patients were from the US. Age, ECOG, ISS, type of myeloma, cytogenetic risk, hemoglobin, albumin, LDH, AST, calcium, frailty, and EMD significantly predicted PFS. In addition, sex, baseline creatinine clearance, and ALT were significant for OS. Race, bone disease, and time from diagnosis were not significant for either outcome.
CONCLUSIONS: Findings from this study confirms the prognostic value of many baseline covariates traditionally considered to be prognostic of PFS and OS in the TIE NDMM setting. Those results can be considered in future subgroup analyses or indirect treatment comparisons.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
MSR45
Topic
Methodological & Statistical Research
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference
Disease
SDC: Oncology