First-Line Treatment Use and Survival Outcomes for Patients With Primary Advanced or Recurrent Endometrial Cancer in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: To describe first-line treatment patterns and factors impacting survival for patients with primary advanced (stage III-IV) or recurrent (A/R) endometrial cancer (EC) in Canada. METHODS: This retrospective cohort study used health administrative data for patients with primary A/R EC (2010-2020) in Alberta, Canada. Characteristics by receipt of first-line systemic therapy were compared. Factors impacting overall survival (OS) after first-line chemotherapy were evaluated using a multivariable Cox proportional hazards model. RESULTS: Of 1185 patients included, 817 (68.9%) received first-line systemic therapy (advanced, n = 679 of 885; recurrent, n = 138 of 300). Patients in this cohort were generally younger, with fewer comorbidities than those who did not receive first-line systemic therapy. Patients with recurrent disease who received previous chemotherapy and who had a longer time to recurrence were more likely to receive first-line systemic therapy. The median OS was 53.5 months (95% CI 37.8-80.1); the OS was shorter with older age (≥75 vs. <65 years, adjusted hazard ratio [aHR] 1.62; 95% CI 1.18-2.23) and high-grade versus low-grade histology (aHR 1.99; 95% CI 1.59-3.67). The OS was longer in patients in stage III who had surgery (aHR 0.35; 95% CI 0.24-0.51). CONCLUSION: Characteristics such as age and comorbidities impacted first-line systemic therapy use in primary A/R EC. Patients who were older, with high-grade histology, stage IV without surgery, and receiving platinum monotherapy had the shortest OS. Effective treatment options are needed to prolong survival for primary A/R EC.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".