Background: Renal impairment (RI) is associated with substantial clinical and economic burden in patients with multiple myeloma (MM), but real-world data reporting on healthcare resource utilization (HRU) and outcomes in these patients are lacking. We assessed treatment patterns, overall survival (OS), HRU and associated costs across lines of therapy (LoT) in patients with MM who had baseline RI.

Methods: We identified patients (aged ≥18 years) with continuous Part A, B and D coverage who initiated pharmacologic therapy for MM between January 1, 2012 and December 31, 2016. Baseline demographics, disease characteristics, and treatment patterns from first-line to fourth-line (1L-4L) were reported for all eligible patients (main cohort). Within this cohort, a subgroup of patients diagnosed with RI at baseline (RI subgroup) were identified using appropriate International Classification of Diseases (ICD)-9 and ICD-10 codes. Treatment regimens were identified during the first 60 days following start of each LoT; stem cell transplantation (SCT) in 1L was considered part of the 1L regimen. The end of each LoT was indicated by treatment augmentation, treatment switching (after >60 days), discontinuation of all agents (for >90 days), or death. Overall survival (Kaplan-Meier analysis) was defined as time from start of each LoT until death or censoring (end of data/Medicare coverage). All-cause HRU categories were identified during each LoT and reported as incidence rate per patient per month (PPPM); associated all-cause healthcare costs during LoT were reported in 2017 US$. Results are presented using standard descriptive statistics.

Results: A main cohort of 10,026 patients was identified; of these, a RI subgroup of 714 patients with baseline RI was identified (7.1% of main cohort). At 1L initiation, the RI subgroup was generally younger (71.9 vs. 74.6 years), had a lower proportion of females (47.8% vs. 53.1%) and had a higher proportion of Medicare coverage for end-stage renal disease (62.9% vs. 6.3%) than the main cohort. Patients with RI had a higher mean Charlson Comorbidity Index score (excluding MM; 4.8 vs. 3.3) and a higher proportion of patients with comorbidities (anemia: 72.5% vs. 57.9%; diabetes with chronic complications: 38.7% vs. 27.1%; cardiovascular diseases: 97.2% vs. 82.5%) than the main cohort. In the RI subgroup, among patients who received SCT in 1L (n=76), bortezomib-dexamethasone (Vd) was the most frequent 1L regimen (39.5%), followed by bortezomib-lenalidomide-dexamethasone (VRd; 17.1%) and bortezomib-cyclophosphamide-dexamethasone (VCd; 15.8%). In patients who had no SCT in 1L, Vd was the most frequent 1L regimen (59.5%), followed by VCd (12.7%) and lenalidomide-dexamethasone (Rd; 12.1%). Among patients in the RI subgroup who progressed to 2L therapy, 61.7% received lenalidomide-based regimens in 1L. Newer MM therapies such as carfilzomib, pomalidomide, ixazomib, daratumumab, and elotuzumab were used more frequently in later LoTs (2L: 25.6%; 3L: 50.0%; 4L: 68.8%). Median OS from start of 1L was shorter in the RI subgroup than in the main cohort (29.9 vs. 46.5 months; Table), and this difference was consistent across each subsequent LoT. Incidence of HRU during 1L (Table) was generally higher in the RI subgroup than the main cohort, particularly for inpatient days (1.3 vs. 0.7 PPPM) and home health services (0.9 vs. 0.5 PPPM); this pattern was consistent between cohorts across each subsequent LoT. Total costs in the 1L RI subgroup vs. main cohort (Table) were $14,782 vs. $12,451; the cost differential was maintained across each subsequent LoT. The key driver of this difference was the additional medical service costs ($12,047 vs. $7,459 in 1L) incurred by patients with RI.

Conclusion: Patients with MM who had baseline RI were shown to experience higher clinical and economic burden in real-world clinical practice than the overall MM population. This burden was maintained across LoTs. Efficacious regimens that help improve renal function with minimal toxicity would enable patients with MM and RI to persist with treatment and may help address unmet need in this subgroup of patients.

Disclosures

Hari:BMS: Consultancy; GSK: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Incyte Corporation: Consultancy. Araujo:Sanofi Genzyme: Current Employment. Latremouille-Viau:Sanofi Genzyme: Consultancy, Other: Dominique Latremouille-Viau is an employee of Analysis Group, Inc. which received consultancy fees from Sanofi Genzyme.; Novartis Pharmaceutical Corporation: Consultancy, Other: Dominique Latremouille-Viau is an employee of Analysis Group, Inc. which received consultancy fees from Novartis.. Lin:Sanofi Genzyme: Current Employment. Davidson:Sanofi Genzyme: Other: Mikhail Davidson is an employee of Analysis Group, Inc which received consultancy fees from Sanofi Genzyme.. Guerin:Sanofi Genzyme: Consultancy, Other: Annie Guerin is an employee of Analysis Group, Inc. which received consultancy fees from Sanofi Genzyme.; Abbvie: Consultancy, Other; Novartis Pharmaceuticals Corporation: Consultancy, Other: Annie Guerin is an employee of Analysis Group, Inc. which received consultancy fees from Novartis.. Sasane:Sanofi Genzyme: Current Employment.

Author notes

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Asterisk with author names denotes non-ASH members.

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