Effectiveness of second-line therapies following upfront daratumumab plus bortezomib, cyclophosphamide and dexamethasone: A new benchmark
Bibliographic record
Abstract
Abstract Background Daratumumab plus bortezomib, cyclophosphamide and dexamethasone (D-VCd) is the only FDA-approved treatment regimen for newly diagnosed light chain (AL) amyloidosis. For patients (pts) who do not respond or relapse after D-VCd, there are no approved second-line therapies (L2). Small series have described a range of treatments and responses to L2 following upfront D-VCd but there is significant variability among subgroups and no standard of care. Defining responses under real-world conditions to currently available treatments in non-responders and relapsed patients establishes a benchmark to improve upon when studying novel agents, assists regulatory agencies evaluating new treatments, and was the aim of the current study. Methods This multicenter retrospective cohort study included all consecutive AL amyloidosis pts treated with upfront D-VCd or daratumumab, bortezomib and dexamethasone (D-Vd) no later than 12/31/2023 at 5 academic medical centers. Hematologic responses were based on the International Society of Amyloidosis response criteria. An optimal hematologic response was defined as a very good partial response (VGPR), a complete response (CR), or in cases where the baseline difference between the involved and uninvolved free light chains (dFLC) was less than 5mg/dL, a low dFLC partial response (PR). Renal and cardiac responses were determined by validated criteria [Palladini, JCO 2012; Palladini, Blood 2014; Lilleness, Blood, 2019]. Logistic regression was used to determine predictors of L2, 12 months after initiation of first line treatment (L1). Pearson's Chi-Squared and Fisher's exact tests were used to test associations between cytogenetics, type and response to L2. Results One hundred ninety-five pts received frontline D-VCd and 5 received D-Vd with a median follow-up of 37 months [1-98]. Amongst the 190 pts with available cytogenetic results, 78 (45%) had t(11;14), 36 (20%) 1q gain, 33 (20%) del 13q and 16 (9%) hyperdiploidy. Consolidative high dose melphalan and autologous stem cell transplant (HDM/ASCT) after achieving an optimal hematologic response to L1 (N=17) was included in L1. HDM/ASCT for pts with suboptimal response to L1 was categorized as L2. The following responses were achieved to L1: 61 (32%) CR, 82 (43%) VGPR, 15 (8%) low-dFLC PR and 32 (17%) PR or less. Fifty-six (28%) pts required L2, at a median of 11 [2-63] months following initiation of L1. On multivariate analysis, baseline bone marrow plasma cell percentage was predictive of need for 2L at 12 months following L1 initiation (odds ratio 1.04; 95% confidence interval, 1.01-1.07; p=0.014). For 2L, 19 (34%) pts received a venetoclax (VEN)-based regimen including VEN monotherapy, VEN-daratumumab, VEN-pomalidomide, VEN-bortezomib or VEN-bortezomib-daratumumab. Sixteen of the 19 pts treated with VEN had t(11;14). Thirty-seven (66%) pts, including 11 with t(11;14), were treated with alternative non-VEN 2L regimens. Four received HDM/ASCT, while others had various combinations of daratumumab, bortezomib, ixazomib, carfilzomib, lenalidomide, pomalidomide, cyclophosphamide, elotuzumab, dapagliflozin and bendamustine. Hematologic responses to L2 included 15 (31%) CR, 12 (25%) VGPR, 8 (17%) low dFLC PR and 13 (27%) PR or less. Presence of 1q gain was associated with a lower likelihood of achieving an optimal hematologic response L2 (p=0.024). Among pts with hematologic response data, 17/18 (94%) treated with VEN achieved an optimal hematologic response (39% CR, 33% VGPR, 22% low dFLC PR), compared to 18/30 (60%) treated with alternative regimens (27% CR, 20% VGPR, 13% low dFLC PR) (p=0.017). Among 21 pts with evaluable organ disease, 12/19 (61%) achieved cardiac response and 5/10 (50%) a renal response with L2. Eighteen pts (32%) required a third line (3L) therapy, at a median of 5 [1-39] months from L2. Conclusion This represents the largest dataset of pts treated with upfront D-VCd requiring 2L. While >90% of pts treated with VEN-based regimens had an optimal response to L2, almost half treated with non-VEN regimens had poor responses, highlighting a therapeutic gap in this pt population. Presence of 1q gain was associated with worse response to L2. Data from two additional sites will be added to the dataset by 09/2025. These multicenter data will serve as a benchmark for new drug approval in the non-responder and relapsed setting.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".