Quality of life (QOL) with ribociclib (RIB) plus aromatase inhibitor (AI) versus abemaciclib (ABE) plus AI as first-line (1L) treatment (tx) of hormone receptor-positive/human epidermal growth factor receptor–negative (HR+/HER2−) advanced breast cancer (ABC), assessed via matching-adjusted indirect comparison (MAIC).
Bibliographic record
Abstract
1015 Background: The combination of a cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) + endocrine therapy is the recommended 1L tx for HR+/HER2− ABC. A statistically significant overall survival (OS) benefit with RIB + AI was recently reported for MONALEESA-2 (ML-2); final OS results for the MONARCH 3 (MON-3) trial of ABE + AI are pending. QoL is an important end point that affects tx decisions. Understanding the impact of CDK4/6i on QoL is of increasing importance given use in earlier tx lines for ABC and an emerging role in treating early breast cancer, where QoL considerations may be more relevant. MAIC analysis allows for comparative effectiveness in the absence of head-to-head trial data. In this analysis, patient (pt)-reported QoL for the Phase III ML-2 (RIB + AI) and MON-3 (ABE + AI) trials were compared using MAIC with a focus on individual domains; the PALOMA-2 trial could not be considered for this analysis because of the different pt-reported outcome measures evaluated in the trial compared to ML-2 and MON-3. Methods: An anchored MAIC of QoL with RIB + AI vs ABE + AI was performed using data from EORTC QLQ-C30 and BR-23 questionnaires, individual participant data from ML-2 (data cutoff: 6/10/2021), and published data from MON-3 (data cutoff: 11/3/2017). All available QoL data were used in this analysis; the median follow-up for ML-2 was 79.7 months, and the median duration of follow-up at which QoL data were reported for MON-3 was 26.73 months. Inclusion and exclusion criteria were generally similar. Pts in both arms of ML-2 were weighted to match baseline characteristics in the corresponding arms of MON-3. Cox proportional hazards model was used to generate hazard ratios (HRs); anchored HRs were calculated using the Bucher method. 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: 205 and 149 pts from the ML-2 arms of RIB/PBO were matched to 328 and 165 pts from the ABE/PBO arms of MON-3. After weighting, pt characteristics were well balanced. TTSD significantly favored RIB vs ABE in appetite loss (HR, 0.46; 95% CI, 0.27-0.81), diarrhea (HR, 0.42; 95% CI, 0.23-0.79), and fatigue (HR, 0.63; 95% CI, 0.41-0.96) as measured by QLQ-C30 and arm symptoms (HR, 0.49; 95% CI, 0.30-0.79) as assessed by BR-23. TTSD did not significantly favor ABE vs RIB in any functional or symptom scale of the QLQ-C30 or BR-23. Conclusions: This MAIC suggests that RIB + AI is associated with better symptom-related QoL vs ABE + AI for postmenopausal pts with HR+/HER2− ABC in the 1L setting. QoL differences between CDK4/6i and their associated adverse event profiles may impact clinical decisions in HR+/HER2− ABC.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".