Comparison of toxicity experienced by elderly (E) and younger (Y) patients in breast cancer (BC) clinical trials.
Bibliographic record
Abstract
9542 Background: E patients (pts), age 65 and older, form a large percent of BC pts, but are under-represented in trials, due to actual/perceived frail health, or actual/perceived greater potential toxicity from therapy (rx). With ethics approval, we examined whether E pts had more toxicity than Y pts (< 65 years) in clinical trials. Methods: All BC phase II and III drug trials open from 1999 to 2012 at British Columbia Cancer Agency Vancouver Center were reviewed, excluding trials with only premenopausal pts. Adverse events (AE) were captured from case report forms and charts. The primary endpoint was meaningful toxicity (MTOX), defined as any grade 3 or 4 AE; any AE with dose delay or reduction; or premature discontinuation of rx. Frequencies of MTOX were compared using chi-square tests, means were compared with T-tests. Results: Among 46 trials enrolling 799 pts, rx types were chemotherapy ([CT], 18% of pts), hormone ([HT] 40%), skeletal ([ST] 14%), targeted ([T] 14%]) and CT + T (14%). Pts were 19% E (age range 65-84) and 81% Y (age range 25-64). E pts were more likely to enroll in HT and ST trials; Y pts were evenly distributed among all rx types. Toxicity data (Table) was available for 778 pts (97%). Conclusions: In non CT trials, E and Y pts had similar frequency and number of MTOX. Few E (5%) enrolled in CT trials, but with no more MTOX than Y pts. Discontinuation of rx was equal in E and Y, considering all rx types. Appropriate selection of E pts by eligibility criteria, self selection, and/or clinician assessment allows safe participation of E pts in BC trials. Fear of increased MTOX should not exclude fit E pts from trial participation. [Table: see text]
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".