Quality of Life in Early‐Stage Oral Cancer: Interim Results from the COOLS Trial
Bibliographic record
Abstract
Objectives: 1) Describe the quality of life experienced by oral cancer patients over time. 2) Explore subdimensions of quality of life over time. Methods: The pan‐Canadian Optically‐guided Oral Lesions Surgical (COOLS) Trial is a multi‐center randomized control trial evaluating a novel surgical staging method for the treatment of early‐stage oral cancer. Surveys were given to 92 participants at baseline, 6 weeks, and 3 months after surgery, collecting data on self‐reported quality of life (QoL). Results: Aggregate survey scores (EQ‐5D, FACT H&N) did not show much difference before or after surgery. Subscale analyses, however, revealed important differences in self‐reported pain, anxiety, and head/neck specific symptoms over time. Results are indicative of a recovery that happens over time, but it remains to be seen if this effect extends to the 12‐month follow‐up stage. QoL trajectory differs by surgical site, and the presence/absence of neck dissection. Selected relevant comparisons will be presented. Conclusions: At an aggregate level, surgery does not either improve or worsen QoL in early‐stage oral cancer patients; however, deeper examination of the data suggests that there are trends that will be clinically meaningful to patients and their families. These findings may help clinicians to better prepare their patients before surgery. Recovery to baseline QoL is achieved around 3 months, which suggests that surgery may improve long‐term (>12 month) QoL.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".