Patient Characteristics, Treatment Patterns and Early Outcomes of Patients with Relapsed or Refractory Multiple Myeloma (RRMM) Initiated on Talquetamab: An Electronic Medical Record and Chart Review Study
Bibliographic record
Abstract
Introduction: Talquetamab (TAL), the first-in-class GPRC5D-targeted bispecific antibody, was granted accelerated US approval in August 2023 for adult patients with RRMM. Pivotal phase 2 trial data showed >70% overall response rate (ORR), with adverse events including cytokine release syndrome (CRS; 76%) and dysgeusia (70%). To mitigate the risk of CRS, TAL is initiated with step-up dosing (SUD) including 2-3 step-up doses prior to the first full treatment dose, each 2-4 days apart. Given its recent approval, real-world evidence related to TAL is limited. Thus, this study aimed to describe the real-world characteristics, SUD patterns, dosing schedule, and early data on safety and effectiveness in patients with RRMM receiving TAL. Methods: A retrospective analysis of patients with RRMM initiating TAL on or after the date of Food and Drug Administration (FDA) approval was conducted using Loopback Analytics (formerly Acentrus), an electronic medical records (EMR) database from both academic and non-teaching hospitals in the US. For patients with available data from physician notes in patient charts, a chart review was conducted to supplement information from structured EMR data. Adult patients were included if they received TAL (first date of administration defined as index date), had ≥2 diagnostic codes for MM on separate dates, and had ≥6 months of clinical activity prior to the index date. Patients were excluded if they had a clinical trial enrollment record during the SUD period. Patients were followed until the earliest of death or end of data availability (March 31, 2024). Results: Overall, 92 patients were included (median age: 68.5 years [≥75 years: 19.6%]; female: 46.7%; White: 69.6%; mean Quan-Charlson Comorbidity Index: 2.9). A majority of these patients started TAL between 08/2023-12/2023 (60.9%) and had been exposed to prior B-cell maturation antigen (BCMA) targeted therapies (59.8%) including bispecifics (41.3%), chimeric antigen receptor T-cell (CAR-T) therapies (28.3%), and belantamab mafodotin (12.0%). Chart review data was available for 50 patients, of which 14 (28.0%) had an Eastern Cooperative Oncology Group (ECOG) score of ≥2, 24 (48.0%) had high-risk cytogenetic abnormalities, and 10 (20.0%) had extramedullary disease. With a median duration of follow-up of 3.4 months, 77 of the 92 patients (83.7%) had complete SUD data, of which 25 (32.5%) and 52 (67.5%) patients had weekly (QW) and biweekly (Q2W) administration schedules, respectively. Overall, the SUD phase was completed within 7-8 days for 61 (79.2%) patients. Following the SUD phase, 44 (57.1%) patients received ≥3 treatment doses of TAL, with 14 (31.8%) and 28 (63.6%) patients initially on QW and Q2W, respectively. Overall, 14 (31.8%) switched to every 4 weeks (Q4W) or less frequent dosing (median time to switching not reached). Of 50 patients with chart review data, 23 (46.0%) patients had reported CRS; 10 (20.0%) had grade 1 CRS, 10 (20.0%) had grade 2 CRS, 1 (2.0%) had grade 3 CRS, and 2 (4.0%) had CRS of unknown grade. CRS was managed using tocilizumab in 14 (28.0%) patients and dexamethasone in 9 (18.0%) patients. Dysgeusia was reported in 34 (68.0%) patients, of which 21 (61.8%) had an improvement in dysgeusia within a median of 77.5 days. Weight loss was reported in 24 (48.0%) patients, with a median loss of 6.5% of body weight from TAL initiation; 9 (18.0%) had <5% weight loss, 12 (24.0%) had 5-<10% weight loss, and 3 (6.0%) had 10-<20% weight loss. A total of 33 (66.0%) patients had evaluable response data and 88% of them started TAL during 08/2023-12/2023 (first few months after TAL launch). With a median duration of follow-up of 5.3 months, the ORR was 81.8%. Conclusion: This retrospective study using EMR and chart review data provides real-world evidence of a heavily pretreated patient population who initiated TAL in the first few months after FDA approval. Most patients were able to complete TAL SUD within 1 week and some patients switched to Q4W or less frequent dosing during the treatment phase. The early safety profile was overall consistent with the trial with most CRS events being mild, most dysgeusia events seen to improve, and most weight loss <10%. Together with the observed real-world response rates to TAL, these early findings support the use of TAL as an effective treatment option for patients with RRMM.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".