Abstract B27: Influence of fluorescence visualization on screening decisions in the general dental office
Bibliographic record
Abstract
Abstract Oral cancer is a substantial, often unrecognized issue globally, with close to 300,000 new cases reported annually. It is a management conundrum: a cancer site that is easily examined, yet >40% of oral cancers are diagnosed at a late stage when prognosis is poor and treatment can be devastating. Opportunistic screening within the dental office could lead to earlier diagnosis and intervention with improved survival. With an increasing number of screening tools commercially available it is vital to validate these tools within the general dental office amongst clinicians who are not as experienced as specialists in high-risk clinics. One such tool, fluorescence visualization (FV), is used to assess alterations to tissue fluorescence. The goal of this study was to determine how clinicians made decisions about referral based on the risk classification of the lesion, how FV was integrated and how it affected the decision to refer. Information on FV rates in private practice and how FV affects decision making is vital to determine the feasibility of using this tool in a general practice setting. Methods: 15 dental offices participated in a 1-day workshop on oral cancer screening, including an introduction to and use of FV. Participants then screened patients (medical history, convention oral exam, fluorescent visualization exam) in-office for 11 months. Participants were asked to triage lesions by apparent risk: low, intermediate and high. Low-risk (LR) lesions were common and benign conditions including geographic tongue, candidiasis and known trauma. Intermediate risk (IR) lesions were lichenoid in appearance and high-risk (HR) lesions were white or red lesions or ulcers without apparent cause. Clinicians then made the decision on which lesions to reassess in 3 weeks based on risk assessment and clinical judgment. Lesions of concern were seen by a community facilitator or referred to an oral medicine specialist. Results: 2542 patients were screened with 389 (15%) low, intermediate or high-risk lesions detected. Of the 389 lesions, FV data was available for 357. Of 325 LR lesions, 175 (54%) were FV+. 93 were recalled (primarily trauma), 86 complied and at 3 weeks only 18 were FV+ and 2 were FVE (equivocal). 22 lesions were seen by a facilitator/referred resulting in 2 biopsies with benign findings. 89% of low-risk FV+ lesions were transient. Eight of the 16 IR lesions were FV+, 10 lesions were recalled (6 FV+, 1 FVE, 3 FV−) and all complied. 4 of 6 FV+ lesions remained positive and were referred. Status of FV− and FVE lesions remained the same and were referred/seen by a facilitator. One FV− IR lesion was reassessed as FV+ and referred for biopsy (lichenoid mucositis). Of the 16 lesions assessed HR at baseline, 9 were FV+, 1 FVE and 6 FV−; 1 FV+ lesion was referred directly, biopsied -> low grade dysplasia. Of the 8 FV+ lesions, 5 were FV+ and 1 FVE at follow-up, 4 were referred resulting in 1 biopsy of low grade dysplasia. 1 FVE lesion was FV− at recall. 4 of the 6 FV− lesions were recalled, 1 was FV+ at recall and referred. 25 FV+ sites had no visible clinical lesion. 9 were recalled, 8 complied and 1 was referred directly to a specialist with no reassessment. None were found to be of concern; FV+ was associated with denture sore spots, scar tissue, vascularities, etc. Conclusions: A 3 week reassessment appointment is invaluable to reduce the proportion of FV+ lesions attributed to trauma and prevent the unnecessary referral due to confounders. Patient compliance for the 3 week reassessment was high. Not surprisingly, FV status of intermediate and high risk lesions did not alter as much at reassessment. FV played a role in the decision to reassess and refer lesions as lesions with persisting FV+ were more apt to be referred. Clinicians relied on their own judgment and referred if a lesion was FV− if they were concerned. Citation Information: Cancer Prev Res 2011;4(10 Suppl):B27.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".