Age Subgroup Analysis of Health-Related Quality of Life of Blinatumomab Versus Standard-of-Care Chemotherapy in Patients with Relapsed or Refractory Philadelphia Chromosome-Negative B-Cell Precursor Acute Lymphoblastic Leukemia in a Randomized, Open-Label, Phase 3 Study (TOWER)
Bibliographic record
Abstract
Abstract Background: Despite the availability of new therapies for acute lymphoblastic leukemia (ALL), older patients have historically poor responses to treatment and poor outcomes versus younger patients, with 5-year survival rates of approximately 20% or less. Blinatumomab is a bispecific T-cell engager (BiTE®) antibody construct that redirects cytotoxic T cells to lyse CD19-positive B cells and is approved for the treatment of relapsed or refractory (r/r) B-cell precursor (BCP) ALL and for minimal residual disease-positive ALL in the US. In the phase 3 TOWER study in patients with r/r Philadelphia chromosome-negative (Ph-) BCP ALL who received blinatumomab compared with standard-of-care (SOC) chemotherapy, overall survival was improved (median, 7.7 vs 4.0 months; P=0.01; Kantarjian H, et al. N Engl J Med. 2017;376:836-847), and posttreatment health-related quality of life (HRQoL) across all EORTC QLQ-C30 scales was better (Topp MS, et al. Blood. 2018;131:2906-2914). TOWER efficacy results did not differ by age group. In this subgroup analysis of TOWER, we assessed the HRQoL of older patients versus younger patients who received blinatumomab or SOC chemotherapy. Methods: Patients (N=405) with r/r Ph- BCP ALL were randomized 2:1 to receive 2 cycles of induction blinatumomab by continuous intravenous infusion (n=271) or SOC (n=134). Patients could receive transplant at any time following cycle 1. Those in remission could receive up to 3 consolidation cycles; 12 months of maintenance was allowed for those who received up to 3 consolidation cycles and had bone marrow response. HRQoL was assessed using the EORTC QLQ-C30 Questionnaire on days 1 (baseline), 8, and 15, on day 29 of cycle 1; day 1, 15, and 29 of each consolidation cycle; and at the safety follow-up. The questionnaire included 1 global health status scale, 5 functioning scales, 3 symptom scales, and 6 single-symptom items. For global health status and functioning scales, a higher score indicates better HRQoL; for symptom scales/items, a lower score indicates better HRQoL. A 10-point change was viewed as the minimum clinically important difference in EORTC QLQ-C30 (Zikos E, et al. EORTC. 2016). In this analysis, HRQoL in TOWER was assessed using two different age cutoffs: <35 versus ≥35 years (the randomization stratification in TOWER) and <55 versus ≥55 years (the stratification factor for INO-VATE, a phase 3 trial for another therapy in r/r ALL). Analyses included patients with baseline and ≥1 postbaseline result of any multi-item scale or single-item measure. Mean change from baseline in scores for each scale/item were summarized for cycle 1. Time to deterioration (TTD) analyses assessed the treatment effect based on timing from the initiation of treatment to a ≥10-point decrease for the functional scales and/or a ≥10-point increase for the symptom scales respectively. Conclusions: Consistent with the efficacy results, compared with SOC, blinatumomab improved HRQoL and delayed the deterioration in HRQoL regardless of the age group in patients with r/r Ph- BCP ALL. Disclosures Topp: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Research Funding; Boehringer Ingelheim: Research Funding; F. Hoffmann-La Roche Ltd: Membership on an entity's Board of Directors or advisory committees, Research Funding; Regeneron Pharmaceuticals, Inc.: Honoraria, Research Funding. Zimmerman:Amgen Inc.: Employment, Equity Ownership. Dombret:Cellectis: Consultancy, Honoraria, Other: Travel expenses; Servier: Consultancy, Honoraria; Immunogen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Other: Travel expenses, Speakers Bureau; Ambit (Daiichi Sankyo): Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Menarini: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Shire-Baxalta: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Otsuka: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Kite Pharma: Consultancy, Honoraria, Research Funding; Jazz Pharma: Consultancy, Honoraria, Research Funding; Ariad (Incyte): Consultancy, Honoraria, Other: Travel expenses, Research Funding, Speakers Bureau; Roche/Genentech: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Other: Travel expenses, Research Funding, Speakers Bureau. Stein:Celgene: Speakers Bureau; Amgen Inc.: Speakers Bureau. Franklin:Amgen Inc.: Employment, Equity Ownership. Cong:Amgen, Inc.: Employment, Equity Ownership. Zhang:Amgen Inc.: Employment, Equity Ownership. Schuh:Amgen Inc.: Consultancy; Pfizer: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Otsuka: Consultancy; Shire: Consultancy; Teva: Consultancy; Jazz: Consultancy.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".