Impact of early discontinuation of adjuvant endocrine therapy on survival in breast cancer: A target trial emulation
Bibliographic record
Abstract
BACKGROUND: Early discontinuation of adjuvant endocrine therapy (AET) among patients with estrogen receptor-positive (ER+) breast cancer (BC) is common. Observational studies reported inconsistent effects of early AET discontinuation on survival outcomes, with limited causal evidence. METHODS: We identified women aged 50-80, diagnosed with first primary ER+ BC between 2010-2015, who underwent surgery in Alberta, Canada. The average effect of early AET discontinuation on survival outcomes was estimated by emulating a target trial. Risk factors for early AET discontinuation were evaluated. RESULTS: Of 6823 eligible patients, 21.8 % did not receive AET, 27.3 % discontinued AET within early, and 50.9 % adhered to the 5-year AET. Compared to adhering to 5-year AET, early discontinuation increased the hazard of overall death and recurrence, with greater effects in higher tumor stages. Early discontinuation also significantly increased the risk of breast cancer-specific death (HR=3.92, 95 % CI: 2.96-5.20), but no interaction with tumor stage was observed. No significant difference in survival outcomes was observed between patients discontinuing AET at 4-5 years and those completing 5 years. Older age (>70 years) at diagnosis, lower-stage disease, HER2-negative status, and absence of chemotherapy or radiotherapy were associated with early discontinuation. CONCLUSIONS: Over one-third of ER+ BC patients in our cohort discontinued AET early, which was associated with increased risks of recurrence and mortality. The impact of early discontinuation varied by tumor stage, and one-year reduction in AET duration did not appear to compromise effectiveness. Implementing targeted interventions for ER+ patients may help improve adherence and survival outcomes.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".