Valid and reliable techniques for measuring fibrosis in patients with head and neck cancer postradiotherapy: A systematic review
Bibliographic record
Abstract
BACKGROUND: Fibrosis is a common side effect of radiotherapy for head and neck cancer. Although treatments for fibrosis have been developed, valid and reliable measurement tools are needed to verify their efficacy. The purpose of this review was to identify and appraise tools used to measure head and neck fibrosis. METHODS: Electronic databases were searched for primary research published through April 2014. Main search terms included head and neck cancer, radiotherapy, fibrosis, validity, and reliability. Methodological quality was assessed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Two blinded raters conducted all assessments. Discrepancies were resolved by consensus. RESULTS: The search retrieved 534 unique citations. Nine studies met our inclusion criteria, representing 9 different tools. Only 1 tool was assessed for reliability and validity. QUADAS-2 revealed that all studies were at risk for bias. CONCLUSION: To date, there are no valid and reliable techniques for measuring fibrosis postradiotherapy for head and neck cancer, especially within the suprahyoid and pharyngeal regions. © 2015 Wiley Periodicals, Inc. Head Neck 38: E2322-E2334, 2016.
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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 | 0.022 | 0.120 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".