Health-related quality of life of postmenopausal women with hormone receptor–positive, HER2- advanced breast cancer treated with ribociclib + letrozole: Results from MONALEESA-2.
Bibliographic record
Abstract
133 Background: In the MONALEESA-2 trial, ribociclib + letrozole significantly improved progression-free survival and showed higher overall response rates vs placebo + letrozole in hormone receptor–positive, HER2– advanced breast cancer. Here, we present key patient-reported outcomes including health-related quality of life (HRQoL). Methods: Six hundred sixty-eight patients were randomized (n = 334 for each treatment group). Patient-reported outcomes were evaluated during treatment and at progression using the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 and QLQ-BR23. Changes from baseline in all subscales were analyzed using a linear mixed-effects model, and time to 10% deterioration was compared between treatment arms using the stratified log-rank test. Results: Questionnaire adherence rates were high ( > 90%). During treatment, HRQoL (global health status/QoL score) was maintained and similar in both treatment arms. At progression/end of treatment, HRQoL worsened numerically in both arms. Time to definitive 10% deterioration of HRQoL was similar between treatment groups, slightly favoring the ribociclib + letrozole arm (hazard ratio, 0.944; 95% confidence interval, 0.720–1.237). No statistically or clinically relevant differences were observed for key symptoms using EORTC QLQ-C30 including fatigue, nausea, and vomiting. There was clinically relevant improvement ( > 5 points) in pain from baseline to post baseline (through cycle 15) in the ribociclib + letrozole arm, but only mild improvement (≤5 points) in the placebo + letrozole arm. Conclusions: Ribociclib + letrozole maintained HRQoL, and a numerical trend favoring ribociclib + letrozole was observed for pain reduction and delay. Clinical trial information: NCT01958021.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".