Health-related quality of life of postmenopausal women with hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer treated with ribociclib + letrozole: results from MONALEESA-2
Bibliographic record
Abstract
PURPOSE: Evaluate patient-reported outcomes (PROs) for postmenopausal women with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer treated with first-line ribociclib plus letrozole. METHODS: In the phase III MONALEESA-2 study (NCT01958021), 668 patients were randomized 1:1 to ribociclib (600 mg/day; 3-weeks-on/1-week-off) plus letrozole (2.5 mg/day) or placebo plus letrozole. PROs were assessed using the European Organisation for Research and Treatment of Cancer core quality-of-life (EORTC QLQ-C30) and breast cancer-specific (EORTC QLQ-BR23) questionnaires. Changes from baseline and time to deterioration in health-related quality of life (HRQoL) were analyzed using linear mixed-effect and stratified Cox regression models, respectively. Exploratory analysis of area-under-the-curve for change from baseline in pain score (AUC-pain) was performed. RESULTS: On-treatment HRQoL scores were consistently maintained from baseline and were similar between arms. A clinically meaningful (> 5 points) reduction in pain score was observed as early as Week 8 and was maintained up to Cycle 15 in the ribociclib arm. A statistically significant increase in mean AUC-pain was also observed in the ribociclib arm. Scores for all other EORTC QLQ-C30 and EORTC QLQ-BR23 domains were maintained from baseline and were similar between arms. CONCLUSIONS: HRQoL was consistently maintained from baseline in postmenopausal women with HR+, HER2- advanced breast cancer receiving ribociclib plus letrozole and was similar to that observed in the placebo plus letrozole arm. Together with the improved clinical efficacy and manageable safety profile, these PRO results provide additional support for the benefit of ribociclib plus letrozole in this patient population.
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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 | 0.001 | 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 | 0.000 |
| 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".