Prognostic factors in advanced incurable HNSCC patients on palliative-intent immunotherapy-based regimen
Bibliographic record
Abstract
BACKGROUND: Locally advanced unresectable or metastatic head and neck squamous cell carcinoma carries a poor prognosis with limited palliative systemic treatment options. We sought to evaluate clinic-pathological characteristics associated with favorable responses to palliative-intent immunotherapy. METHODS: A retrospective cohort study was conducted of adult patients with recurrent or metastatic head and neck squamous (rmHNSCC) cell carcinoma at the Juravinski Cancer Center from 1 January 2018 to 31 December 2022. Baseline demographic and disease characteristics, treatment delivered, and outcome data were collected. RESULTS: A total of 96 patients were identified. Median age was 61 years (75.9% male). The most common primary was oropharyngeal. The majority of patients were platinum-ineligible or refractory (61.5%). The median overall survival was 12.6 months (95% CI 6.3-15.4), and median PFS was 5.3 months (95% CI 3.8-7.8). After univariate and multivariate analyses, the systemic immune-inflammation index (SII), albumin, and BMI were identified as independently significant prognostic factors for survival. CONCLUSION: SII, albumin, and BMI were the strongest independent prognostic factors of overall survival in rmHNSCC patients treated with palliative immunotherapy. Future validation studies would be important, given these are inexpensive, noninvasive tests and may be potentially modifiable patient factors.
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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 | 0.001 |
| 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".