Real-World Systemic Therapy Treatment Patterns for Squamous Cell Carcinoma of the Head and Neck in Canada
Bibliographic record
Abstract
Background: In the present study, we examined real-world treatment patterns for squamous cell carcinoma of the head and neck (scchn) in Canada, which are largely unknown. Methods: Oncologists across Canada provided data for disease history, characteristics, and treatment patterns during May-July 2016 for 6-8 consecutive patients receiving first-line or second-line drug treatment for scchn (including locally advanced and recurrent or metastatic disease). Results: Information from 16 physicians for 109 patients receiving drug treatment for scchn was provided; 1 patient was excluded from the treatment-pattern analysis. Median age in the cohort was 63 years [interquartile range (iqr): 57-68 years], and 24% were current smokers, with a mean exposure of 26.2 ± 12.7 pack-years. The most common tumour site was the oropharynx (48%). Most patients (84%) received platinum-based regimens as first-line treatment (44% received cisplatin monotherapy). Use of cetuximab-based regimens as first-line treatment was limited (17%). Of 53 patients receiving second-line treatment, 87% received a first-line platinum-based regimen. Median time between first-line treatment with a platinum-based regimen and initiation of second-line treatment was 55 days (iqr: 20-146 days). The most common second-line regimen was cetuximab monotherapy (43%); platinum-based regimens were markedly infrequent (13%). Conclusions: Our analysis provides real-world insight into scchn clinical practice patterns in Canada, which could inform reimbursement decision-making. High use of platinum-based regimens in first-line drug treatment was generally reflective of treatment guidelines; cetuximab use in the second-line was higher than anticipated. Additional real-world studies are needed to understand the effect of novel therapies such as immuno-oncology agents on clinical practice and outcomes, particularly for recurrent or metastatic scchn.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".