Adherence to adjuvant endocrine therapy in seniors with breast cancer, predictors and challenges
Bibliographic record
Abstract
BACKGROUND: Nearly one-third of breast cancers (BC) occur in women 65 years and older. Anti-estrogen therapy (AET) significantly reduces BC recurrence and death in these patients, as they more often have hormone receptor positive tumors. However, prior studies suggest that adherence to AET in older women is a challenge. OBJECTIVE: To characterize AET adherence in seniors with BC and identify factors influencing it. METHODS: Cancer registry data and administrative claims for all non-metastatic BC diagnosed in Quebec between 1998 and 2005 were accessed from the provincial health insurance program. Patients ≥ 65 years who started AET (Tamoxifen, Anastrozole, Exemestane or Letrozole) and had 5 years of follow up were studied. Five-year medication possession ratio (MPR) was calculated and multivariate linear regression was used to assess the association between patient, disease, and physician characteristics and MPR. RESULTS: 4,715 women were included. Mean age was 72.9. 66.77% had no other significant comorbidities and only 4.16% had 3 or more comorbidities. Stage distribution was: 6.43% in situ, 74.13%localized and 19.45% regional disease. Mean MPR was 83.5% (SD 26.8%). 1596 (34%) women had AET interruption at some point during the entire period of follow up. The cumulative probability of therapy interruption was 33.8% and the mean time to interrupt was 833.4 days. Among those who had therapy interruptions, 39.1% reinstituted AET (mean time to reinstitute was 185.6 days), of which, 48.2% re-interrupted AET again. 5-year MPR decreased with increasing age (p=0.05) and hospitalizations not related to BC (0.73% per each hospitalization, p-value=0.009). Compared to women with node positive disease, those with in situ disease had on average an MPR lower by 6.5%(p-value=0.0003). Having more active prescriptions at baseline increased the MPR by 0.6% for each medication, (p-value< 0.0001). However, adding further new medications after the start of AET affected the MPR negatively (0.3% decrease in MPR for each new medication added, p-value< 0.0001). Among psychotropes, antidepressants were the only group that did show a significant effect, resulting in a MPR decrease of 4.7% among those who were known to take antidepressants prior to the diagnosis and treatment of breast cancer (p-value= 0.003). Women on Tamoxifen, compared to those on Anastrozole, had on average a MPR that is lower by 6%, (p-value= 0.002). Compared to those who never switched their AET type, those who switched early in their treatment course, during the first year, had lower MPR by 5.3% (p-value=0.003). On the other hand, those who switched later had on average an MPR higher by 7.4% (p-value<0.0001). CONCLUSION: Most seniors with BC had high adherence to AET. Patients with more advanced age, less advanced disease and more non-BC related health service use, and women treated with antidepressants prior to their breast cancer were at higher risk of suboptimal 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".