Identifying Patient-Reported Outcome Measures (PROMs) for Routine Surveillance of Physical and Emotional Symptoms in Head and Neck Cancer Populations: A Systematic Review
Bibliographic record
Abstract
The aims of this review were to identify symptoms experienced by head and neck cancer (HNC) patients and their prevalence, as well as to compare symptom coverage identified in HNC specific patient-reported outcome measures (PROMs). Searches of Ovid Medline, Embase, PsychInfo, and CINAHL were conducted to identify studies. The search revealed 4569 unique articles and identified 115 eligible studies. The prevalence of reported symptoms was highly variable among included studies. Variability in sample size, timing of the assessments, and the use of different measures was noted across studies. Content mapping of commonly used PROMs showed variability and poor capture of prevalent symptoms, even though validation studies confirmed satisfactory reliability and validity. This suggests limitations of some of the tools in providing an accurate and comprehensive picture of the patient's symptoms and problems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".