Global treatment patterns and outcomes among patients with recurrent and/or metastatic head and neck squamous cell carcinoma: Results of the GLANCE H&N study
Bibliographic record
Abstract
OBJECTIVES: Given a lack of universally-accepted standard-of-care treatment for patients with recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC), study objectives were to assess treatment utilization and survival outcomes for R/M HNSCC in the real-world setting. MATERIALS AND METHODS: A multi-site retrospective chart review was conducted in Europe (Germany, United Kingdom, Italy, Spain), Asia Pacific (Australia, South Korea, Taiwan), and Latin/North America (Brazil and Canada) to identify patients who initiated first-line systemic therapy for R/M HNSCC between January 2011 and December 2013. Patients were followed through December 2015 to collect clinical characteristics, treatment and survival data. RESULTS: Among 733 R/M HNSCC patients across 71 sites, median age was 60 years (inter-quartile range 54-67), 84% male, and 70% Eastern Cooperative Oncology Group performance status 0-1; 32% had oral cavity and 30% oropharyngeal cancers. The most common first-line regimen across all countries consisted of platinum-based combinations (73%), including platinum + 5-fluorouracil (5-FU) (26%), cetuximab + platinum ± 5-FU (22%), or taxane + platinum ± 5-FU (16%). However, use of different platinum-based combinations varied substantially; administration of cetuximab + platinum ± 5-FU was frequent in Italy (81%), Germany (46%) and Spain (38%), whereas use in other countries was limited. Median follow-up was 22.6 months (95% confidence interval [CI]: 21.5-24.6 months). Median real-world overall survival was only 8.0 months (95% CI: 7.0-8.0), with one-year survival reaching only 30.9% (95% CI: 27.5-34.3). CONCLUSION: Systemic therapies used in clinical practice for patients with R/M HNSCC vary substantially across countries. Prognosis remains poor in this patient population, highlighting the need for newer, more efficacious treatments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".