Meaningful Changes in Patient-Reported Outcomes in Relation to Best Clinical Response and Disease Progression: <i>Post Hoc</i> Analyses from MAIA
Bibliographic record
Abstract
Abstract Introduction: In oncology clinical trials, overall survival (OS) is considered the gold standard efficacy endpoint. However, in multiple myeloma, the prolonged survival times and availability of multiple salvage therapies render it difficult to rely on OS as a primary endpoint. Instead, progression-free survival (PFS) or clinical response can be a relevant biomarker. At the same time, some health technology assessment bodies will only consider evidence based on patient-relevant endpoints, such as morbidity, mortality, and health-related quality of life (HRQoL), within their benefit assessments. Patient-reported outcomes (PROs) provide insights into how a treatment affects HRQoL, including symptoms and functioning. In the phase 3 MAIA trial, daratumumab, lenalidomide, and dexamethasone (D-Rd) demonstrated a significantly prolonged PFS and rapid and sustained improvements in PROs compared with lenalidomide and dexamethasone (Rd) alone at a median follow-up of 28 months. Updated results with longer follow-up confirmed a continued PFS benefit, deepening best clinical responses, and a significant OS benefit with D-Rd. Here, we report the results of analyses exploring the relationship between clinical efficacy endpoints and PROs in the MAIA trial. Methods: In MAIA (NCT02252172), TIE patients with NDMM were randomized to D-Rd or Rd until disease progression (PD) or unacceptable side effects. Clinical response and PD were defined per the International Myeloma Working Group uniform response criteria. PROs were assessed at baseline, on day 1 of cycles 3, 6, 9, and 12 for year 1, every 6 months thereafter until PD, or at end of treatment and at 8 and 16 weeks post-progression using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30-item (EORTC QLQ-C30). The current analyses were conducted on patients with a baseline PRO assessment and ≥1 post-baseline PRO assessment using a clinical cutoff date of February 19, 2021. Patients from both treatment groups were pooled and stratified by best clinical response. For PROs, the threshold for clinically meaningful change from baseline was defined a priori as ≥10 points based on published literature. Analyses were conducted for the global health status (GHS), fatigue, and pain scales of the EORTC QLQ-C30. The proportions of patients with clinically meaningful improvement in these PROs from baseline at any time while on treatment were calculated for and compared across best clinical response subgroups. For this analysis, patients were censored at the time of PD or discontinuation of therapy. Results were summarized with odds ratios and 95% confidence intervals. Additionally, the proportions of patients with clinically meaningful worsening in PROs from baseline at the time of and post-progression were also calculated for those who had PD. No adjustments were made for multiplicity. Nominal P-values are presented. Results: Best clinical response at a median follow-up of 56.2 months for the 710 patients included in this analysis is shown in the Table. For GHS, fatigue, and pain, the proportion of patients who reported clinically meaningful improvement from baseline increased with increasing depth of best clinical response. Odds ratios comparing best clinical response vs stable disease reflect this relationship and are shown in the Figure. Of the 264 patients who experienced PD and had PRO data at the time of or post-progression, 38.6%, 54.9%, and 39.4% reported meaningful worsening of GHS, pain, and fatigue, respectively, at the time of or post-progression. Conclusions: Patients with deeper best clinical response were more likely to report meaningful improvements in PROs. Patients who experienced PD reported worsening of GHS and symptoms at the time of or following progression. These analyses provide evidence of the association between key clinical efficacy endpoints and PROs and demonstrate the patient relevance of these clinical endpoints. Figure 1 Figure 1. Disclosures Perrot: Abbvie: Honoraria; BMS Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kumar: Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Beigene: Consultancy; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Plesner: Takeda: Research Funding; Genentech: Other: Advisor, Research Funding; Oncopeptides: Other: Advisor, Research Funding; AbbVie: Other: Advisor, Research Funding; CSL Behring: Other: Advisor; Janssen: Other: Advisor, Research Funding; Celgene: Other: Advisor, Research Funding; Genmab: Research Funding. Orlowski: Asylia Therapeutics, Inc., BioTheryX, Inc., and Heidelberg Pharma, AG.: Other: Laboratory research funding; CARsgen Therapeutics, Celgene, Exelixis, Janssen Biotech, Sanofi-Aventis, Takeda Pharmaceuticals North America, Inc.: Other: Clinical research funding; Amgen, Inc., BioTheryX, Inc., Bristol-Myers Squibb, Celgene, EcoR1 Capital LLC, Genzyme, GSK Biologicals, Janssen Biotech, Karyopharm Therapeutics, Inc., Neoleukin Corporation, Oncopeptides AB, Regeneron Pharmaceuticals, Inc., Sanofi-Aventis, and Takeda P: Consultancy, Honoraria; Asylia Therapeutics, Inc.: Current holder of individual stocks in a privately-held company, Patents & Royalties; Amgen, Inc., BioTheryX, Inc., Bristol-Myers Squibb, Celgene, Forma Therapeutics, Genzyme, GSK Biologicals, Janssen Biotech, Juno Therapeutics, Karyopharm Therapeutics, Inc., Kite Pharma, Neoleukin Corporation, Oncopeptides AB, Regeneron Pharmaceuticals, I: Membership on an entity's Board of Directors or advisory committees. Moreau: Abbvie: Honoraria; Oncopeptides: Honoraria; Celgene BMS: Honoraria; Sanofi: Honoraria; Amgen: Honoraria; Janssen: Honoraria. Bahlis: Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Genentech: Consultancy; GlaxoSmithKline: Consultancy, Honoraria. Nahi: XNK Therapeutics AB: Consultancy. Hulin: abbvie: Honoraria; Celgene/BMS: Honoraria; Sanofi: Honoraria; Takeda: Honoraria; Janssen: Honoraria. Quach: Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; CSL: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen/Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Goldschmidt: GSK: Honoraria; Incyte: Research Funding; Janssen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Amgen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; BMS: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Adaptive Biotechnology: Consultancy; Celgene: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Chugai: Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Novartis: Honoraria, Research Funding; Dietmar-Hopp-Foundation: Other: Grant; Sanofi: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Takeda: Consultancy, Research Funding; Johns Hopkins University: Other: Grant; Mundipharma: Research Funding; MSD: Research Funding; Mo
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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 | 0.027 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".