Quality of life with ribociclib <i>versus</i> abemaciclib as first-line treatment of HR+/HER2− advanced breast cancer: a matching-adjusted indirect comparison
Bibliographic record
Abstract
Background: A cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) + endocrine therapy is recommended as first-line treatment for hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) advanced breast cancer (ABC). Quality of life (QoL) is an important endpoint that affects treatment decisions. Understanding the relevance of CDK4/6i treatment on QoL is gaining importance given use in earlier treatment lines for ABC and an emerging role in treating early breast cancer in which QoL may be more impactful. In the absence of head-to-head trial data, a matching-adjusted indirect comparison (MAIC) permits comparative efficacy between trials. Objective: In this analysis, patient-reported QoL for MONALEESA-2 [ribociclib + aromatase inhibitor (AI)] and MONARCH 3 (abemaciclib + AI) was compared using MAIC with a focus on individual domains. Design: abemaciclib + AI was performed using data from the European Organization for Research and Treatment of Cancer quality of life questionnaire (QLQ)-C30 and BR-23 questionnaires. Methods: Individual patient data from MONALEESA-2 and published aggregated data from MONARCH 3 were included in this analysis. Time to sustained deterioration (TTSD) was calculated as the time from randomization to a ⩾10-point deterioration with no later improvement above this threshold. Results: abemaciclib in appetite loss [hazard ratio (HR), 0.46; 95% confidence interval (CI), 0.27-0.81], diarrhea (HR, 0.42; 95% CI, 0.23-0.79), fatigue (HR, 0.63; 95% CI, 0.41-0.96), and arm symptoms (HR, 0.49; 95% CI, 0.30-0.79). TTSD did not significantly favor abemaciclib compared with ribociclib in any functional or symptom scale of the QLQ-C30 or BR-23 questionnaires. Conclusions: This MAIC indicates that ribociclib + AI is associated with better symptom-related QoL than abemaciclib + AI for postmenopausal patients with HR+/HER2- ABC treated in the first-line setting. Trial registration: NCT01958021 (MONALEESA-2) and NCT02246621 (MONARCH 3).
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".