Real-world treatment landscape after anti-BCMA CAR T-cell therapy in relapsed/refractory multiple myeloma: An international Study
Bibliographic record
Abstract
Abstract Introduction: Despite significant advances, multiple myeloma (MM) remains largely incurable. The introduction of CD38-targeting agents has dramatically improved 5-year overall survival from 27% to 60%. Most patients now receive more than three lines of therapy and eventually become refractory to proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs), and anti-CD38 antibodies. Novel BCMA-targeted therapies, such as CAR T-cells (cilta-cel from 2nd line, ide-cel from 3rd line) and bispecific T-cell engagers (e.g., teclistamab, elranatamab from 4th line), have become new standards of care. However, the median progression-free survival (PFS) post-CAR T therapy is often less than three years, highlighting an urgent need for defined subsequent treatment strategies. Aims: This real-world study aimed to identify the primary combinations and regimens used after anti-BCMA CAR T-cell therapy in relapsed/refractory MM across EU5 countries (France, Germany, Italy, Spain, UK), the US, and Japan. Methods: Anonymous patient charts (N=100) from onco-hematologists in the EU5, US, and Japan were analyzed (October-December 2022, October-December 2023, January-March 2025). The study focused on patients who had previously received ide-cel or cilta-cel between their 3rd and 5th lines of therapy and subsequently initiated a new treatment. Abbreviations: K=carfilzomib; E=elotuzumab; Pom=pomalidomide; d=dexamethasone; Isa=isatuximab; F=panobinostat; R=lenalidomide; Tec=teclistamab; X=selinexor; Elra=elranatamab; Belamaf=belantamab mafodotin; Ixa=ixazomib. Results: The overall cohort (N=100) had a median age of 63.5 years, with 50% of patients under 65, 43% between 65 and 75, and 7% over 75 years old. Seven patients were in the 3rd line setting (median age 58.9 years), 28 were in the 4th line (median age 64.3 years), and 65 were in the 5th line (median age 63.6 years). Over half of the patients (52%) were lenalidomide-refractory, with the majority in the 5th line (n=41) compared to only 10 in the 4th line and one in the 3rd line. The largest number of patients were treated in France (n=34) and the US (n=34), followed by Germany (n=19). The cohort showed a good performance status (ECOG 0-1: 56%) and varied cytogenetic risk (high: 31%, intermediate: 39%). Patients were categorized as “fit” (41%) or “intermediate-fit” (44%). Frequent comorbidities (77%) included mild renal failure (18%), peripheral neuropathy (32%), hypertension (40%), dyslipidemia (26%), and diabetes (15%). Therapies at Relapse Post-CAR T (N=100): 3rd line (9%, n=7):The most frequent regimens included elotuzumab-based treatments (17%), Kd (14%), isatuximab-based combinations (14%), panobinostat-based therapies (14%), and selinexor-based therapy (14%). 4th line (29%, n=28):Typical regimens were teclistamab (24%), elotuzumab-based combinations (11%), Rd (11%), Xd (8%), Elra (3%), and belamaf (3%). 5th line (63%, n=65):The main options were Tec (23%), Elra (11%), belamaf-based treatments (12%), Ixa-dex (8%), Xd (5%), and Isa-dex (4%). A small percentage of patients (2% for ide-cel, 2% for cilta-cel) were re-challenged with CAR T in the 5th line, although the time interval for sequential CAR T could not be analyzed. Discrepancies emerged between the main countries in the 4th and 5th lines (representing 91% of the cohort): in France and Germany, anti-BCMA agents (especially T-cell engagers) were the most frequent, while treatment strategies were more varied in the US (elotuzumab-based treatments, Rd, teclistamab, Ixa-dex, and Xd). Conclusion: This real-world study of 100 MM patients relapsing after anti-BCMA CAR T-cell treatment shows that 91% were in their 4th or 5th line of therapy. A large majority were triple-class exposed, and 52% were lenalidomide-refractory. In the absence of a clear standard of care, common treatments were identified: elotuzumab- and isatuximab-based regimens in the 3rd line; teclistamab and elotuzumab-based options in the 4th line; and teclistamab, elranatamab, and belantamab mafodotin in the 5th line. Geographic discrepancies reflect variations in drug availability, reimbursement policies, and clinical development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".