Influence of gender on treatment outcome and toxicity in small cell lung cancer (SCLC)
Bibliographic record
Abstract
7041 Background: Female gender has been shown consistently to be a favourable prognostic factor in SCLC. Studies have shown that women with other tumor types experience greater treatment toxicity, but there have been few studies of gender related toxicity in SCLC. Methods: This was a gender-based retrospective analysis of 4 SCLC trials, which were conducted by the NCIC CTG between 1981 and 1996. All 1006 patients (648 male, 358 female) received similar chemotherapy consisting of cyclophosphamide/ doxorubicin/vincristine and etoposide/ cisplatin . Toxicities examined included myelosuppression, stomatitis, vomiting and infection. Other endpoints included number of dose reductions required, number of omitted cycles, response rates and overall survival. Toxicities between the genders were compared using chi-square test in univariate analyses and logistic regression adjusting for age, BSA, performance status, LDH and individual trial in multivariate analyses. Results: Women experienced significantly more toxicity in both univariate and multivariate analyses (see Table). However, toxic death rates were similar for men and women (1.5% vs 1.1%, p=0.58). Despite increased toxicity, 76% of females vs 73.4% of males received all 6 treatment cycles (p=0.38), but 52% of females vs 43.4% of males had treatment delayed for ≥ 2 weeks (p=0.022). The ORR was 80.3% for females and 66.9% for males (p<0.0001) and the median survival was 1.31 years for females and 0.91 for males (p<0.0001) Conclusions: Women clearly experience more chemotherapy related toxicity in the treatment of SCLC, but this does not result in more toxic deaths or omitted treatment cycles, nor does it compromise outcome. No significant financial relationships to disclose.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".