JOINT RADIATION PLANNING PEER REVIEW IN HEAD AND NECK CANCER: A RETROSPECTIVE ANALYSIS OF QA RECOMMENDATIONS AND PATIENT OUTCOMES
Bibliographic record
Abstract
Head and neck cancer (HNC) radiation planning peer review is considered an essential component of high-quality care, aimed at improving patient outcomes through structured quality assurance (QA) recommendations. This study examines the impact of QA recommendations according to primary sites and stages, compliance rates, and associations with patient outcomes, including metastasis and mortality as we report our experience with a joint peer review model. A retrospective analysis was conducted on 168 HNC patients treated at one cancer centre and had peer review with another institution between January 2020 and December 2022, analyzing demographics, cancer types, stages, treatment modalities, radiation doses, QA recommendations, compliance, local recurrence, metastasis, and mortality. The QA recommendations were grouped into major, minor, and no changes. A major change was defined as target contouring modification while a minor change was defined as organs-at-risk (OAR) contouring that was unlikely to change patient outcome. The study assessed the distribution of weekly QA recommendations across primary sites and stages, compliance rates, and their impact on patient outcomes. The cohort had a median age of 64.8 years, with 80.6% male and 19.4% female. Smoking history was prevalent in 66.7% of patients, and 57.8% had a history of alcohol use. The most common primary site was the oropharynx (36.6%), followed by larynx (18.9%) and oral cavity (16.5%). Squamous Cell Carcinoma (SCC) was the dominant histology (86.1%). 65.1% of patients received “No Change” recommendations, while 20.5% and 14.5% required major and minor changes, respectively. Overall compliance with QA recommendations was high (92.1%), with major changes having 100% compliance and minor changes having 54.5% compliance. 52.3% of compliant plans had local recurrence, compared to 61.5% in non-compliant plans. There is no statistical correlation between the recurrence rate and compliance to peer review recommendations. At a median follow up of 30 months, 31.3% of patients have died, with the highest mortality rate (35.3%) among those requiring major QA changes. Compliant patients had a higher mortality rate (32.5%) compared to non-compliant patients (23.1%). HNC radiation planning peer review remains a critical component of QA, with recommendations influencing patient outcomes. While compliance was high, minor QA changes had the lowest adherence, potentially impacting recurrence and metastasis rates. Patients requiring major QA revisions experienced longer times before metastasis but had the highest mortality rate, suggesting more advanced stages might have caused disagreement in planning. These findings underscore the role of structured peer review in optimizing HNC treatment and improving long-term patient outcomes.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".