The Natural History of Patients With Squamous Cell Carcinoma of the Hypopharynx
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To provide the baseline information on the natural history of patients with squamous cell carcinoma of the hypopharynx to help clinicians, researchers, and patients assess the relative effectiveness of treatment options when the best treatment is not known and newer treatments are being proposed. STUDY DESIGN: Retrospective population-based design. METHODS: The patient descriptors, treatments, and outcomes for 595 patients across the province of Ontario, Canada from January 1990 to December 31, 1999 based on electronic data and chart review. RESULTS: The typical patient is 65 years old, male, unemployed, and poor. They are heavy drinkers with significant comorbidity compromising functional status. The tumors are advanced (over 50% stage 4). After curative treatment 20% had residual disease, recurrences tended to appear in the first year and 50% of first recurrences included metastases. Overall, 47% of patients were disease free at 3 years but eventually 64% of patients died of their cancer. CONCLUSIONS: This information can be used by clinicians and researchers to understand the natural history of the patient group to critically assess both the selection bias and effectiveness of treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.001 |
| 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".