Methods, Detection Rates, and Survival Outcomes of Screening for Head and Neck Cancers
Bibliographic record
Abstract
Importance: Head and neck cancers (HNCs) are often diagnosed at advanced clinical stages during their symptomatic phase, leading to a reduced treatment window and poor survival. Screening programs have been suggested as a mitigation strategy. Objective: To examine the effectiveness of current HNC screening programs in improving diagnosis and survival in adults. Evidence Review: This Preferred Reporting Items for Systematic Reviews and Meta-analyses-guided systematic review involved use of peer-reviewed, English-language journal articles identified from MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials between January 1, 2001, and July 15, 2022. Snowballing was applied to retrieve more studies. Eligible articles were original clinical trials and observational studies presenting a universal or risk-targeted screening program of primary HNC in the adult population. Reporting quality was assessed using the JBI's critical appraisal tools. Findings: Database searches yielded 3646 unique citations with an additional 8 studies found via snowballing. Five reviewers assessed the full text of 106 studies. Sixteen articles were ultimately included in the review, involving 4.7 million adults (34.1%-100% male; median age, 30-59 years). Fifteen studies were based in Asia and 1 in Europe (Portugal). Five reported data from randomized clinical trials. An oral inspection conducted once or once every 2 to 3 years was described in 11 studies for screening oral cancer, while multistep screening involving Epstein-Barr virus serologic testing for nasopharyngeal carcinoma delivered every 1 to 4 years was presented in 5. In 4 trials and 6 observational studies, screening significantly increased the detection of localized (stage I/II) tumor or was associated with an increased proportion of diagnoses, respectively, regardless of the population and cancer subsites. Universal screening of asymptomatic adults improved 3- to 5-year overall survival but did not increase cancer-specific survival in 4 trials. Targeted screening improved overall and cancer-specific survival or was associated with improved survival outcomes in 2 trials and 2 observational studies, respectively. Studies had low to medium risks of bias. Conclusions and Relevance: Evidence from the existing literature suggests that a risk-targeted screening program for oral and nasopharyngeal cancers could improve diagnosis and patient survival. Screening adherence, societal cost-effectiveness, and optimal risk stratification of such a program warrant future research, especially in low-incidence settings outside Asia.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".