Predictors of toxicity to concurrent chemoradiation (CRT) in patients (pts) with locally advanced head and neck squamous cell cancer (HNSCC)
Bibliographic record
Abstract
16540 Background: A number of studies have evaluated the impact of prognostic factors on survival but very few have studied their role as determinants of toxicity, especially outside of the context of clinical trials. We set out to identify patient characteristics that are likely to predict toxicity to chemotherapy (CT) with daily cisplatin 6mg/m2 and radiation therapy (RT) in pts with locally advanced HNSCC. Methods: Retrospective chart review of above pts at the Juravinski Cancer Center from 2000 through 2004. A number of pt characteristics were analysed. Toxicity outcomes evaluated were completion of CT and of RT, rise in serum Cr , hematologic suppression, need for extra hydration, and need for extra antiemetics. Results: The charts of 108 pts were reviewed. Median follow-up was 36 months. Five year projected OS and PFS were 78% and 57% in our study compared to 53% and 47% in a published EORTC trial (NEJM, 2004). Median duration of PFS was 64 months in our study compared to 55 months in the EORTC trial. Median OS was not reached in our study. Nineteen percent completed CT and 81% completed RT, 17% had full course of CRT. Thirty-nine percent required extra hydration and 50% required extra antiemetics. Twenty four percent had elevated creatinine levels and 20.4% had hematologic suppression. Logistic regression was used to search for significant correlations between pt characteristics and outcomes. Pts with occasional alcohol intake were more likely to complete RT than heavy alcohol abusers (OR 8.9; P 0.04). Pts with occasional alcohol intake were more likely to get extra hydration than heavy alcohol abusers (OR 5.1; P 0.008).Hematologic suppression was more likely with increasing age (OR 1.08;P 0.015).No significant difference in toxicity outcomes was observed between males and females. Conclusions: This review demonstrated that CRT with daily cisplatin is associated with significant toxicity and most pts are unable to receive full treatment . A number of pt variables might predict increased susceptibility to toxicity. This should be validated in a prospective study. Median PFS in our series appear to be at least as good as previously published reports of CRT using daily cisplatin as well as dose schedules but toxicity does not appear greatly reduced. No significant financial relationships to disclose.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".