Treatment patterns and outcomes according to cytogenetic risk stratification in patients with multiple myeloma: a real-world analysis

Abstract

A clearer understanding of the prognostic implications of t(11;14) in multiple myeloma (MM) is needed to inform current and future therapeutic options. We utilized real-world data from a US database to examine treatment patterns and outcomes in patients by t(11;14) status compared with high- and standard-risk subgroups across different lines of therapy (LoT). This retrospective, observational cohort study used de-identified patient-level information from adults with MM and first-line treatment initiation between January 2011 and January 2020, followed until February 2020. The high-risk cohort comprised patients with high-risk genetic abnormalities per mSMART criteria (including those with co-occurring t(11;14)). Among 6138 eligible patients, 6137, 3160, and 1654 received first-, second-, and third-line treatments, respectively. Of 645 patients who had t(11;14), 69.1% had t(11;14) alone, while 30.9% had co-occurring high-risk abnormalities. Altogether, 1624 and 2544 patients were classified as high- and standard-risk, respectively. In the absence of biomarker-driven therapy, treatment patterns remain similar across LoT in high-risk, t(11;14)+, and standard-risk subgroups. Across all LoT, patient outcomes in the high-risk subgroup were less favorable than those in the t(11;14)+ and standard-risk subgroups. Thus, there is an opportunity for novel therapeutics targeted to t(11;14) and other defined subgroups to personalize MM therapy and optimize patient outcomes.

Fig. 1. Patient disposition.

*Patients who received MM treatment (as captured through unstructured data) >30 days before the start of structured activity within the Flatiron Health network, for whom therapy data may be missing. ^†To ensure that all included patients have been in the database a sufficient duration of time to account for lags in the abstraction of data elements or data linkages to external data sources. L0 line 0, MM multiple myeloma.

Fig. 2. Treatment patterns per line of treatment.

Proportion of patients with treatment regimen by risk subgroup (A), and Sankey plots showing treatment patterns for first-line (B), second-line (C), and third-line (D) treatment. An asterisk symbol represents all other therapies, where < 1% of patients receive a particular treatment regimen. The overall number across each line of therapy includes those patients with undocumented risk who were not included in the analyses. Therefore, the N indicated here is the sum of the t(11;14)+, high-risk and standard-risk subgroups, so does not equal the total number of patients. C cyclophosphamide, d dexamethasone, D daratumumab, E elotuzumab, I ixazomib, K carfilzomib, M melphalan, P pomalidomide, PLD pegylated liposomal doxorubicin, R lenalidomide, t translocation, V bortezomib.

Fig. 3. Kaplan–Meier curves for TTNT by patient risk subgroup.

First-line (A), second-line (B), and third-line (C) therapy. t translocation, TTNT time to next treatment.

Fig. 4. Kaplan–Meier curves for OS by patient risk subgroup.

First-line (A), second-line (B), and third-line (C) treatment. OS overall survival, t translocation.

Fig. 5. Sensitivity analysis in patients who received first-line VRd.

Sankey plot showing treatment patterns (A), and Kaplan–Meier curves for TTNT (B) and OS (C). OS overall survival, t translocation, TTNT time to next treatment, VRd bortezomib lenalidomide dexamethasone.