Assessing the usefulness of three adjunctive diagnostic devices for oral cancer screening: a probabilistic approach
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Visually distinguishing oral cancer from noncancerous oral lesions is problematic. Currently, commercial diagnostic devices are being marketed to dentists as effective screening devices to use in general practice. The purpose of this study is to evaluate the probabilistic performance of VELscope®, Oral CDx® and toluidine blue staining as clinical adjunctive diagnostic procedures in routine screening for oral cancer in dental practice. MATERIALS AND METHODS: Sensitivity and specificity information for each device was taken from the literature. The positive predictive value (PPV) and false positive rate, based on three clinical screening scenario, were calculated using Bayes' Theorem. RESULTS: Under three clinical scenarios (screening the general population, screening only adults (≥40 years) and screening adults (≥40 years) that present with intra-oral visible lesions), VELscope produced the highest PPV's of 1.27%, 2.53% and 8.11%, respectively. This indicates a false positive rate of between 91.89% and 98.73%. CONCLUSION: VELscope, OralCDx and toluidine blue staining have high false positive rates when they are used to screen routinely for oral cancer. It would be inefficient to allocate scarce healthcare resources to the routine use of these devices for oral cancer screening. These devices may be beneficial in opportunistic screening programmes or in cancer referral clinics when the pretest probability of oral cancer is likely to be above 10%. Further research is needed to determine at which pretest probabilities these adjunctive diagnostic devices would be cost-beneficial for the screening of oral cancer.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".