Health-Related Quality of Life in the Cartitude-1 Study of Ciltacabtagene Autoleucel for Relapsed/Refractory Multiple Myeloma
Bibliographic record
Abstract
Background: Multiple myeloma (MM) negatively affects health-related quality of life (HRQoL), and with each relapse, patients with MM experience further declines in HRQoL. Patient-reported HRQoL is therefore an important treatment outcome, in addition to clinical response to therapy. CARTITUDE-1 (NCT03548207) is a phase 1b/2 study evaluating the safety and efficacy of ciltacabtagene autoleucel (cilta-cel; JNJ-68284528; LCAR-B38M CAR-T cells), a chimeric antigen receptor T (CAR-T) cell therapy with 2 B-cell maturation antigen-targeting single-domain antibodies, in patients with relapsed/refractory (R/R) MM. We evaluated symptoms, functioning, and overall HRQoL through patient-reported outcome measures, which is a secondary objective of CARTITUDE-1. Methods: Patients were ≥18 years of age with a diagnosis of MM per International Myeloma Working Group criteria, measurable disease, and Eastern Cooperative Oncology Group performance status ≤1. Patients had received ≥3 prior regimens for MM or were double-refractory to a proteasome inhibitor and immunomodulatory drug, and had received an anti-CD38 antibody. Cilta-cel was given as a single infusion on Day 1 (target dose: 0.75×106 [range: 0.5-1.0×106] CAR+ viable T cells/kg) 5-7 days after start of lymphodepletion (cyclophosphamide 300 mg/m2 + fludarabine 30 mg/m2 daily for 3 days). In the phase 2 portion of CARTITUDE-1, HRQoL was assessed at baseline, on Days 7, 28, 56, 78, and 100, and every 28 days thereafter using 3 patient-reported instruments: the European Organization for Research and Treatment of Cancer QoL Questionnaire Core 30 (EORTC QLQ-C30), 4 items from the EORTC QLQ-Multiple Myeloma (MY20) module, and the 5-level EuroQol Five Dimension (EQ-5D-5L) measure. Raw EORTC QLQ-C30 and EORTC QLQ-MY20 scores were linearly transformed to a scale ranging from 0 to 100; the EQ-5D-5L visual analog scale (VAS) score ranges from 0 to 100. Clinically meaningful changes in EORTC QLQ-C30 symptoms, physical functioning, and overall HRQoL were based on anchor-based methods using a patient global impression of change item. Repeated-measures mixed-effects models were used to analyze mean changes in HRQoL from baseline to subsequent assessment time points in patients in the modified intent-to-treat population with ≥1 post-baseline assessment. Median time to event of HRQoL scores was calculated descriptively, using a change in score ≥0.5×standard deviation of values prior to cilta-cel infusion as improvement/worsening with death due to progression defined as worsening. Results: For the 68 patients in the phase 2 portion of CARTITUDE-1 (63.2% male; median age: 62.0 years [range: 43-78]), questionnaire completion rates at baseline and Day 100, respectively, were 92.6% and 69.2% for both the EORTC QLQ-C30 and EORTC QLQ-MY20 items and 92.6% and 70.8% for the EQ-5D-5L. For EORTC QLQ-C30 subscales, clinically meaningful improvements at Day 100 were seen for 71.1% of patients for pain, 62.2% for fatigue, 72.1% for physical functioning, and 51.1% for global health status. Mean changes in pain and fatigue showed a reduction in these symptoms over time (following an initial worsening of fatigue at Day 7; Figure). This trend of improvements over time was also observed for overall HRQoL and EORTC QLQ-MY20 single items. Clinically meaningful improvements at Day 100, defined by a literature-based minimal important difference of 10 points in mean score, were observed for the EORTC QLQ-MY20 single items: thinking about illness and worries about dying or future health. Approximately 50% of the population reported an event of improvement or worsening in EORTC QLQ-C30 and EQ-5D-5L scales, with the rest censored in this early data cut; among these patients, median time to improvement was approximately 1-2 months (with median time to worsening occurring less than 1 month after cilta-cel treatment). There was a trend for an improvement in mean EORTC QLQ-C30 global health status, physical functioning, pain, and fatigue, and EQ-5D-5L VAS at Day 100 with increased depth of response. Conclusions: Some patients with heavily pretreated MM showed rapid and clinically meaningful improvements in pain, fatigue, physical functioning, overall HRQoL, and future perspectives, consistent with their clinical outcomes. With additional follow-up, it is possible that these early improvements in symptoms will translate into greater improvement in overall HRQoL in the long term. Disclosures Martin: Janssen: Research Funding; Sanofi: Research Funding; AMGEN: Research Funding; Seattle Genetics: Research Funding; GSK: Consultancy. Lin:Vineti: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Legend BioTech: Consultancy; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees. Cohen:Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: 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; Takeda,: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Novartis: Other: Patents/Intellectual property licensed, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Genentech/Roche: Membership on an entity's Board of Directors or advisory committees. Htut:City of Hope Medical Center: Current Employment. Stewart:Janssen, BMS, Sanofi-Aventis, GSK: Honoraria; Tempus, Inc., Genomics England LLC: Membership on an entity's Board of Directors or advisory committees. Hari:GSK: Consultancy; BMS: Consultancy; Takeda: Consultancy; Amgen: Consultancy; Incyte Corporation: Consultancy; Janssen: Consultancy. Berdeja:Teva: Research Funding; Cellularity: Research Funding; Kesios: Research Funding; BMS: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; CURIS: Research Funding; EMD Sorono: Research Funding; Genentech, Inc.: Research Funding; Karyopharm: Consultancy; Poseida: Research Funding; Novartis: Research Funding; Lilly: Research Funding; Amgen: Consultancy, Research Funding; Acetylon: Research Funding; Glenmark: Research Funding; Janssen: Consultancy, Research Funding; Vivolux: Research Funding; Takeda: Consultancy, Research Funding; Servier: Consultancy; CRISPR Therapeutics: Consultancy, Research Funding; Constellation: Research Funding; Bluebird: Research Funding; Abbvie: Research Funding; Prothena: Consultancy; Bioclinica: Consultancy; Kite Pharma: Consultancy; Legend: Consultancy. Madduri:Foundation Medicine: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; AbbVie: Consultancy, Honoraria; Legend: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Kinevant: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Celgene: Consultancy, Honoraria. Usmani:Takeda: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; SkylineDX: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Merck: Consultancy, Research Funding; Incyte: Research Funding; Pharmacyclics: Research Funding; Janssen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; GSK: Consultancy, Research Funding; Abbvie: Consultancy; Array Biopharma: Research Funding; Celgene: Other; Amgen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; BMS, Celgene: Consultancy, Honoraria, Other: Speaking Fees, Research Funding. Yeh:Janssen: Current Employment. Allred:Janssen: Current Employment. Olyslager:Janssen: Current Employment. Banerjee:Janssen: Current Employment. Goldberg:Johnson & Johnson: Current Employment, Current equity holder in publicly-traded company. Schecter:Janssen: Current Employment. Jackson:Janssen: Current Employment; Memorial Sloan Kettering Cancer Center: Consultancy. Deraedt:Janssen: Current Employment, Current equity holder in publicly-traded company. Gries:Janssen: Current Employment, Current equity holder in publicly-traded company. Fastenau:Janssen: Current Employment, Current equity holder in publicly-traded company. Wu:Legend Biotech USA Inc.: Current Employment. Carrasco:Legend Biotech USA Inc.: Current Employment. Akram:Legend Biotech USA Inc.: Current Employment. Hossain:Legend Biotech USA Inc.: Current Employment. Jakubowiak:AbbVie, Amgen, BMS/Celgene, GSK, Janssen, Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive, Juno: Consultancy, Honoraria. Jagannath:BMS, Janssen, Karyopharm, Legend Biotech, Sanofi, Takeda: Consultancy.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".