Time toxicity of nivolumab in metastatic head and neck squamous cell carcinoma patients: a single-institution experience
Bibliographic record
Abstract
BACKGROUND: Treatment of platinum-refractory recurrent and metastatic head and neck squamous cell carcinoma (r/mHNSCC) involves immune-checkpoint inhibitors. Time toxicity (TT) is an emerging metric with implications for patient quality of life and decision-making. We sought to evaluate TT associated with nivolumab in these patients. METHODS: This is a retrospective single-institution review of patients with platinum-refractory r/mHNSCC seen at an academic cancer center between 1 January 2018 to 31 December 2022 in Ontario, Canada. Primary outcome is TT, defined as any number of days spent undergoing cancer-related activities. RESULTS: Of 56 patients evaluated, median age was 63 years (33-85) and 84% were male. Median overall survival (OS) and grade 3 immune-toxicities were 7.6 months and 6.2%, respectively. Median TT was 24 days (1-109), accounting for 7.6% of OS. TT accounted for 14.9% of OS in poor responders. TT accounted for only 4-6% for patients who survived more than a year. CONCLUSIONS: Our study provides an important and underexplored patient-centered metric in TT, especially in the context of incurable HNSCC with abysmal survival outcome. Our findings suggest that TT varies significantly between responders and non-responders. Duration of TT should be discussed with patients in shared decision-making when discussing palliative nivolumab.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".