Real‐World Outcomes of Transplant Ineligible Older Adults With Multiple Myeloma Treated With Novel Regimens: A Population‐Based Retrospective Cohort Study
Introduction: With improving overall survival among MM patients, there is an increasing need to both understand the absolute risk and identify risk factors for developing a second primary malignancy (SPM). Understanding these risk and potential modulation factors may help guide decisions regarding treatment options, monitoring surveillance strategies, and patient counselling. Furthermore, understanding this baseline SPM risk will help contextualize the future SPM risk associated with newer therapeutics, including chimeric antigen receptor therapies. Thus, we conducted a population-based study with following objectives: 1) to evaluate the rate and distribution of SPMs, and 2) to identify risk factors including a history of prior malignancy associated with an increased risk of SPMs in 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 2007-2022 were identified using ICD-O-3 code 9732/3 (MM). The list of secondary cancers (excluding non-melanoma skin cancers) were identified from pathology codes maintained in the Cancer Care Ontario Registry. Additional risk factors were also collected including a history and type of any pre-existing cancer (at least 1 year prior to MM diagnosis), treatment details including history of autologous stem cell transplantation (ASCT) and lenalidomide usage. The Kaplan-Meier method was used to estimate the median overall survival (OS). We estimated the cumulative incidence of secondary cancer accounting for death as a competing risk. To identify the association of prognostic factors on the risk of developing a SPM, we performed competing risks regression and estimated the subdistribution hazard ratios (sHR) accounting for death as a competing risk. Results: A total of 12123 patients . The median age at diagnosis was 70 (IQR 61-77) years, 6860 (57%) of our cohort had a male sex. In our 4511 (37%) received at least one ASCT, 8062 (67%) were lenalidomide exposed and 6917 (57%) were cyclophosphamide exposed at any time post MM diagnosis, and 3017 (16%) received oral melphalan based induction regimens. The median follow up for cohort was 4.53 (95% CI 4.4-4.7) years. A total of 2079 patients (17%) had a prior cancer diagnosis at least 1 year prior to their MM diagnosis. Of these patients, 665 (32%) had received chemotherapy and 553 (27%) had received radiation to treat their prior malignancy. The three most common prior cancers were: prostate cancer (25%), breast cancer (13%) and heme malignancies (4%).The median time from diagnosis of a prior malignancy to MM diagnosis was 6.4 (IQR 2.04-13.26) years. A total of 1070 (8.8%) of the cohort developed a SPM. The cumulative incidence of SPM post MM diagnosis, accounting for death as a competing risk, was 3.7% at 2 years, 7.6% at 5 years, and 11.5% at 10 years. The three most common SPMs were hematologic (21%), prostate (7%), and lung (7%) cancer. The three most common hematological SPMs were acute myeloid leukemia (37%), B-acute lymphoblastic leukemia (16%), and myelodysplastic syndrome (19%). The median OS following after any SPM diagnosis was 1.64 (95% CI 1.36-1.92) years, was 1.85 (95% CI 1.54-2.28) years for patients that developed a non-hematologic SPM, and was 1.05 (95% CI 0.88-1.40) years for patients that developed a hematologic SPM. Conclusion: This study represents one of the largest real-world cohort studies examining the rates, risk factor and outcomes of MM patients developing secondary cancers. We show that a prior malignancy diagnosis increased the risk of SPM after adjusting for ASCT and lenalidomide exposure, sex, and age at MM diagnosis. These data are important for patients and physicians to understand the risks associated with treatment of MM.
Comparison of the Efficacy in Clinical Trials Versus Effectiveness in the Real-World of Treatments for Multiple Myeloma: A Population-Based Cohort Study
Introduction: Improvements in outcomes of patients with multiple myeloma (MM) depend on the use of regimens approved based on results from large phase III randomized controlled trials (RCTs) demonstrating their efficacy. However, many real-world (RW) patients would not have met the stringent RCTs inclusion criteria. Therefore, the effectiveness of these drugs in the RW setting is unknown. Understanding this efficacy-effectiveness gap is important to contextualize the expected outcomes in the current RW setting. Therefore, we conducted a retrospective population-based study to compare the efficacy versus effectiveness of registration RCTs with RW patients using standard of care (SoC) MM regimens for the primary outcomes of 1) progression free survival [PFS]; 2) overall survival [OS] and 3) serious adverse events (AEs). Methods: RW data was obtained from the Institute for Clinical Evaluative Sciences, an administrative database capturing all health records in the publicly funded health care system in Ontario, Canada. Adult patients treated between Jan 2007 to Dec 2020 with SoC regimens were included. Only regimens with corresponding registrational phase III RCTs which led to the public reimbursement in Ontario were included (lenalidomide/dex [Rd] and bortezomib/Rd [VRd] for newly diagnosed transplant ineligible patients, and relapsed MM (RRMM) regimens included carfilzomib/Rd [KRd], carfilzomib/dex [Kd], daratumumab/Rd [DRd], daratumumab/bortezomib/dex [DVd], pomalidomide/dex [Pd]). In the RW cohort, PFS was defined as the time from initiation of index regimen to death, initiation of subsequent MM treatment, or last follow-up, and patients remaining on the index regimen as last follow up were censored. Kaplan-Meier curves from pivotal phase 3 RCTs were manually digitized to provide individual patient-level estimates of PFS and OS. Meta-analyses were performed to compare the gap of PFS and OS outcomes of RW versus RCT patients, and effect estimates were summarized using hazard ratios (HR). The frequency of serious AE data was abstracted from published RCTs. Given that serious AEs in RCTs would have resulted in hospitalization, hospital admission during treatment with the index regimen was used as a surrogate for serious AEs in the RW cohort. Differences in RW and RCT safety outcomes were reported descriptively. Results & Discussion: A total of 3951 RW MM patients, treated with 7 standard of care MM regimens, were included. Baseline characteristics of patients in the RW and RCT cohorts are shown in table 1. Overall, patients in the RW cohort were older than in the RCTs. For relapsed regimens, there was a longer time between MM diagnosis and start of the regimen in the real-world versus RCT. With regards to the efficacy-effectiveness gap, MM patients treated in routine practise in the RW had a worse PFS despite overestimated of RW PFS compared to highly selected RCT patients for 6 of the 7 MM regimens evaluated, with a pooled HR of 1.44 (95% CI 1.34-1.54) in the meta-analysis (Figure 1A). Similarly, RW patients had a worse OS compared to RCT patients treated with 6 of the 7 regimens, with a pooled HR of 1.75 (95% ci 1.63-1.88) in the meta-analysis (Figure 1B). RRMM patients in the RW had higher rates of prior lenalidomide exposure compared to RCT patients. The only regimen which showed a trend towards performing better in the RW as compared to RCTs was Pd. The reason for this is likely multifactorial but perhaps patients included in the MM-003 RCT may have had more refractory MM (given the higher prior immunomodulatory drug exposure and longer time from diagnosis to treatment among Pd RCT patient) compared to RW patients in this study. With regards to safety, the percentage of patients with inpatient hospitalization during treatment in the real-world cohort and reported serious AEs in RCT were comparable (VRD 57% vs not reported [NR]; Rd 64% vs NR; Kd 57% vs 59%; KRd 53% vs 60%; DVd 36% vs NR; DRd 46% vs 49%; Pd 59% vs 61%). Conclusion: This is one the largest population-level studies highlighting the significant efficacy-effectiveness gap between registrational RCTs and RW usage of these regimens, with RW patients experiencing 44% worse PFS and 75% worse OS compared to RCT patients. Our data emphasize the importance of ongoing evaluation of RW data to contextualize effectiveness and toxicity of selected regimens in the clinic, and better inform both clinicians and patients for shared treatment decision making.
Causes of Death Among Patients with Multiple Myeloma: A 10 Year Longitudinal Analysis of a Population-Based Cohort in Ontario, Canada