Evaluation of toxicities related to novel therapy in clinical trials for women with gynecologic cancer
Bibliographic record
Abstract
BACKGROUND: Women with gynecologic cancer may be at increased risk for adverse events (AEs) due to peritoneal disease burden and prior treatment (surgery, chemotherapy, and pelvic radiotherapy). This study compared the toxicity profiles of patients with and without gynecologic cancer enrolled in phase 1 trials. METHODS: This was a retrospective analysis of the National Cancer Institute phase 1 database for all trials enrolling 1 or more patients with gynecologic cancer over 2 decades (1995-2015). Clinical parameters collected included demographics, cancer history, trial information, AEs, and responses. AEs (according to the Common Terminology Criteria for Adverse Events) were documented for each patient during treatment, and they were counted once and analyzed on the basis of the highest grade and drug attribution. Multiple regression models were used to compare AEs at the baseline and during treatment. RESULTS: A total of 4269 patients enrolled in 150 trials were divided into 3 groups: 1) women with gynecologic cancer (n = 685), 2) women with nongynecologic cancer (n = 1698), and 3) men with cancer (n = 1886). The median age was 58 years. The mean number of total AEs reported during treatment was highest for women with gynecologic cancer (17.1 vs 14.7 vs 13.5; P < .001), even though they were similar at the baseline (7.0 vs 7.4 vs 7.0; P = .09). The mean number of drug-related AEs was also highest for women with gynecologic cancer (8.3 vs 6.9 vs 6.2; P < .001). Grade 3 to 5 AEs were similar (2.3 vs 2.3 vs 2.1); however, grade 2 AEs were more frequent in women with gynecologic cancer (4.6 vs 3.9 vs 3.5). Treatment discontinuations due to AEs were similar (9% vs 9% vs 10%). CONCLUSIONS: Women with gynecologic cancer experienced more frequent low-grade AEs during treatment, and this warrants attention to support their symptom burden. Study dose management should be considered for recurrent grade 2 AEs, particularly during continuous therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.068 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".