Trajectories of adherence to adjuvant endocrine therapy for 5 years in women with breast cancer
Bibliographic record
Abstract
Abstract Background Adjuvant endocrine therapy (AET) is a daily oral medication prescribed for women with hormone-sensitive breast cancer (BC) to reduce recurrence and mortality risks. However, many women do not take AET daily or do not persist with AET for the recommended duration of at least 5 years. Our aims were to identify: 1) trajectories of AET adherence for the 5 years; 2) factors associated with these trajectories. Methods The French Cancer Cohort includes data on hospitalizations, ambulatory care and drug claims for all cancers diagnosed in France (SNDS database). Women diagnosed with a 1st non-metastatic BC in 2011 who had ≥ 1 AET claim within 12 months of surgery were included. For each woman, we estimated the monthly proportion of days covered (PDC) by an AET for 5 years after the first AET. Monthly PDCs were used to model AET adherence trajectories using group-based trajectory modeling. Statistical criteria were used to assess the suitability of the selected model. The factors associated with the trajectories were identified using multinomial logistic regressions. Results 33,260 women were included. A 6-trajectory model was selected: 1) Stop of AET in the 1st year (6.6%), 2) Adherence for 1 year and stop (5.7%), 3) Adherence for 2.5y and stop (6.3%), 4) High adherence for 4.5y and stop (8.3%), 5) Sub-optimal adherence for 5y (4.3%), 6) Very high adherence for 5y (68.8%). Factors associated with non-adherence trajectories are mainly extreme age (>70y) and switch in AET. Conclusions About 70% of women had an optimal adherence for 5 years. Our results showed that women who changed AET during the treatment course were at higher risk of non-adherence. Among non-adherent women, the switch in AET is frequent and probably often related to the management of side effects. Interventions to detect and manage these side effects may help to support women with AET use. Effective management of these effects during all the 5 years could be needed to maintain adherence. Key messages About 70% of women had an optimal adherence for 5 years. Women who changed AET during the treatment course were at higher risk of non-adherence.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".