Abstract
Introduction Multiple Myeloma (MM) is a malignancy of plasma cells most commonly diagnosed in older adults. Overall survival has improved in patients diagnosed with MM over the last two decades; however, there remains a paucity of data on the causes of death among MM patients and whether this changes during the disease trajectory. Understanding the relative rates of MM-specific versus non-MM cause of deaths is critical in guiding decisions regarding treatment options, monitoring strategies, supportive care, and patient counselling to enable shared decision making. Thus, we conducted a population-based study with following objectives: 1) to evaluate the rates of MM-specific vs non-MM cause of death and 2) to identify prognostic factors associated with cause specific death among patients with MM.
Methods We conducted a retrospective population-based study using data from Institute for Clinical Evaluative Sciences (ICES), an administrative database, that captures all health records in the publicly funded health care system in Ontario, Canada. Adult patients treated for newly diagnosed MM between 2007-2018 were identified using ICD-O-3 code 9732/3 (MM) and stratified into autologous stem cell transplant (ASCT) and non-ASCT cohorts. The primary cause of death was identified as the underlying cause of death registered in the Ontario General Death database (ORGD). We estimated the cumulative incidence of MM-specific and non-MM cause of death. To identify the association of prognostic factors on the probability of MM-specific and non-MM cause of death, we performed competing risks regression and estimated the multivariate sub distribution hazard ratios adjusted for covariates.
Results A total of 6677 patients were identified, 2576 in the ASCT group and 4101 in the non-ASCT group, with median age at diagnosis of 59 and 75 years respectively. Eight hundred and seventy-three (34%) in the ASCT group and 2787 (68%) in the non-ASCT group died during the study follow-up period. The median overall survival for the ASCT cohort was 8.4 years (95% CI 7.9-9.2) and for the non-ASCT cohort was 3.0 years (95% CI 2.8-3.1).
The cumulative incidence of MM-specific death was higher than for non-MM cause of death for both the ASCT (24.9%: MM-specific and 7.9 %: non-MM cause of death at 5 years) and non-ASCT cohort (47.6 %: MM-specific and 22.5%: non-MM cause of death at 5 years) throughout the disease trajectory. Cause of death stratified by time from MM diagnosis (<3 yrs, 3-5 yrs and >5 yrs) for both the ASCT and non-ASCT cohort is shown in Figure 1. MM cancer was the most frequent underlying cause of death throughout the disease trajectory in both the ASCT (74%) and non-ASCT cohorts (67%). Other cancers accounted for 6% of deaths in the ASCT group and 7% in the non-ASCT group. In total 2.5% and 5.8% of patients died from heart disease and 6.2% and 4.3% from infectious diseases in the ASCT and non-ASCT group respectively. Other underlying causes of death (including but not limited to dementia related, kidney and liver disease, non cardiac vascular diseases and respiratory diseases) accounted for 10.1% and 16.6% of the deaths in the ASCT and non-ASCT cohort respectively.
Multivariable analysis showing factors associated with MM and non-MM cause of death is shown in Table 1. Key findings include an improving MM specific mortality in more recent years in both ASCT and non-ASCT. Novel drugs were associated with a decreased risk of MM specific death among non-ASCT patients. CRAB features at diagnosis were associated with an increased risk of both MM-specific and non-MM causes of death. History of previous cancer was associated with an increased risk of non-MM cause of death among both the ASCT and non-ASCT cohort.
Conclusion This study represents one of the largest cohort studies in the real-world to examine MM-specific vs non-MM cause of death among MM patients. Our data suggests that while MM-specific mortality has improved in more recent years, MM remains the greatest threat to survival for MM patients including among the older non-ASCT cohort. Future advances in the delivery of effective MM therapeutic agents in both ASCT and non-ASCT cohort is needed to further improve outcomes in this disease.
Disclosures
McCurdy:Sanofi: Honoraria; Janssen: Honoraria; BMS: Honoraria, Research Funding; Forus: Honoraria; GSK: Honoraria; Amgen: Honoraria; Takeda: Honoraria. Pond:Roche Canada: Current Employment, Other: Family member currently employed; Roche Ltd.: Other: Family member owns stock; Merck, Astra-Zeneca, Profound Medical: Consultancy; Takeda: Honoraria. Chakraborty:Janssen, Sanofi Pasteur, Adaptive Biotech: Consultancy; Genentech Inc.: Research Funding. Kaedbey:BMS. Janssen: Honoraria; Jewish General Hospital, Montreal, QC, Canada: Current Employment; Pfizer: Other: Advisory boards; Beigene: Other: Advisory boards; FORUS Therapeutics: Other: Advisory boards; Sanofi: Other: Advisory boards; BMS: Honoraria, Other: Advisory boards; Janssen: Honoraria, Other: Advisory boards; Janssen, BMS, Sanofi, FORUS, Beigene, Pfizer: Membership on an entity's Board of Directors or advisory committees; BMS. Janssen: Honoraria; Janssen, BMS, Sanofi, FORUS, Beigene, Pfizer: Membership on an entity's Board of Directors or advisory committees. D'Souza:Pfizer, Janssen Oncology, Bristol-Myers Squibb/Celgene, Prothena: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda, Sanofi, TeneoBio, Prothena, Caelum Biosciences, Janssen Oncology, Regeneron, Abbvie: Research Funding. Fonseca:Amgen, BMS, Celgene, Takeda, Bayer, Janssen, Novartis, Pharmacyclics, Sanofi, Merck, Juno, Kite, Aduro, OncoTracker, GSK, AbbVie, Pfizer, Karyopharm.: Consultancy; Adaptive Biotechnologies: Divested equity in a private or publicly-traded company in the past 24 months; Adaptive Biotechnologies, Caris Life Sciences, OncoMyx and OncoTracker: Other: Scientific Advisory Board; AbbVie, Amgen, Bayer, BMS/Celgene, GSK, H3 Therapeutics, Janssen, Juno, Karyopharm, Kite, Merck, Novartis, Oncopeptides, OncoTracker, Pfizer, Pharmacyclics, Regeneron, Sanofi, Takeda: Consultancy; Adaptive Biotechnologies, Caris Life Sciences, Oncomyx and OncoTracker: Membership on an entity's Board of Directors or advisory committees; Genentech, Pfizer, Sanofi: Honoraria, Research Funding; FIH prognostication in myeloma: Patents & Royalties. Mian:GSK, Janssen, BMS/Celgene, Forus therapeutics, Amgen, Takeda, Sanofi: Honoraria; Janssen: Research Funding.
