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PF591 EFFICACY AND SAFETY OF DARATUMUMAB, LENALIDOMIDE, AND DEXAMETHASONE (D‐RD) IN RELAPSED OR REFRACTORY MULTIPLE MYELOMA (RRMM): UPDATED SUBGROUP ANALYSIS OF POLLUX BASED ON CYTOGENETIC RISK

2019· article· en· W2949734536 on OpenAlexaff
Meletios Α. Dimopoulos, J. San‐Miguel, Darrell White, Lotfi Benboubker, Gordon Cook, Merav Leiba, James Morton, P. Joy Ho, K. Kim, Naoki Takezako, Philippe Moreau, H.J. Sutherland, Hila Magen, Shinsuke Iida, Jin Sung Kim, H. Miles Prince, Tara Cochrane, Albert Oriol, Nizar J. Bahlis, Ajai Chari, Lisa O’Rourke, Sonali Trivedi, Tineke Casneuf, Christopher Chiu, David Soong, Jon Ukropec, Ming Qi, Hervé Avet‐Loiseau, Saad Z. Usmani, Jonathan L. Kaufman

Bibliographic record

VenueHemaSphere · 2019
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsUniversity of CalgaryInstitute of Cancer ResearchLeukemia & Lymphoma Society of CanadaUniversity of British ColumbiaQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsInternal medicineMedicineLenalidomideTolerabilityOncologyMultiple myelomaGastroenterologyAdverse effect

Abstract

fetched live from OpenAlex

Background: High‐risk cytogenetic abnormalities confer poor outcomes in patients (pts) with MM. In POLLUX, D‐Rd demonstrated significant clinical benefit, including prolonged progression‐free survival (PFS) vs lenalidomide and dexamethasone (Rd), and tolerability in RRMM pts. Here, we present a subgroup analysis of POLLUX, based on cytogenetic risk. Aims: The purpose of this analysis was to determine the efficacy and safety of D‐Rd vs Rd in POLLUX, based on cytogenetic risk status. Methods: Eligible pts received ≥1 prior line of therapy. Cytogenetic risk was based on a combined analysis of fluorescence in situ hybridization (FISH)/karyotype testing and next‐generation sequencing (NGS). High‐risk pts had t(4;14), t(14;16), or del17p abnormalities; standard (std)‐risk pts did not meet the high‐risk criteria. Minimal residual disease (MRD; 10 –5 ) was assessed via NGS using clonoSEQ ® assay V2.0. Results: In POLLUX (D‐Rd, n = 286; Rd, n = 283), 17.1% of pts in the D‐Rd group and 20.1% of pts in the Rd group had high cytogenetic risk abnormalities. After 44.3 months (mo) of median follow up, D‐Rd prolonged PFS vs Rd in pts with high‐ (median 26.8 vs 8.8 mo; HR, 0.54 [95% CI, 0.32–0.91]; P = 0.0175) or std‐risk (median not reached [NR] vs 19.9 mo; HR, 0.41 [95% CI, 0.31–0.55]; P <0.0001) disease. Higher ORR was seen with D‐Rd vs Rd in patients with high risk (87.5% vs 69.1%; P = 0.0115) and std risk (93.6% vs 79.2%; P <0.0001) disease. Responses with D‐Rd were deep, including higher rates of ≥CR (high risk: 43.8% vs 9.1%; std risk: 59.3% vs 27.0%) and ≥VGPR (high risk: 70.8% vs 32.7%; P = 0.0003; std risk: 82.8% vs 55.1%; P <0.0001). Rates of MRD negativity (high risk: 28.6% vs 0%; P <0.0001; std risk: 32.9% vs 8.2%; P <0.0001) and sustained MRD negativity for ≥6 mo (high risk: 12.2% vs 0%; P = 0.0082; std risk: 17.9% vs 1.1%; P <0.0001) and ≥12 mo (high risk: 10.2% vs 0%; P = 0.0188; std risk: 14.0% vs 0.5%; P <0.0001) were higher with D‐Rd vs Rd. D‐Rd significantly prolonged PFS vs Rd in pts after first relapse (high risk: median 46.0 vs 7.3 mo; HR, 0.26 [95% CI, 0.11–0.59]; P = 0.0005; std risk: median NR vs 20.6 mo; HR, 0.43 [95% CI, 0.28–0.66]; P <0.0001; Figure ). Additionally, D‐Rd significantly prolonged PFS2 vs Rd in high‐ (median 38.3 vs 22.1 mo; HR, 0.53 [95% CI, 0.30–0.93]; P = 0.0249) or std‐risk (median NR vs 33.8 mo; HR, 0.53 [95% CI, 0.39–0.72]; P <0.0001) pts. Additional data including safety analyses will be presented. Summary/Conclusion: D‐Rd demonstrates significant efficacy in both high‐risk and standard risk RRMM with a median PFS of 26.8 mo and median not reached, respectively. In addition, more patients achieved a sustained MRD response which translates into better patient outcomes regardless of cytogenetic risk. These data suggest D‐Rd is an effective regimen regardless of cytogenetic risk. NCT02076009 image

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.843

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.258
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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