Accuracy of Store-and-Forward Teledermatology for the Diagnosis of Skin Cancer: The Nouvelle-Aquitaine Experience
Bibliographic record
Abstract
Background In Nouvelle-Aquitaine (a French region with a population of almost 6 million), the density of dermatologists is less than 3.8/100,000 inhabitants. This lack of dermatological care is delaying diagnosis and management, especially for skin cancer. The SmartDerm Project is a store-and-forward (SAF) teledermatology platform for primary care in Nouvelle-Aquitaine providing dermatological counselling to general practitioners (GPs). Objective The main objective was to determine the concordance between the diagnosis of skin cancer made by dermatologists and the pathologists’ diagnosis. Methods GPs in 3 pilot departments of Nouvelle-Aquitaine (Lot-Et-Garonne, Deux-Sèvres, Creuse) sent their dermatology requests using their smartphone, via an app called PAACO/Globule; dermatologists at the University Hospital of Bordeaux answered within 48-72 hours. Consecutive cases of skin cancer suspected by the referent dermatologists during the intervention were included, if the result of biopsy interpreted by a certified pathologist was available at the time of the study. Results Among the 1727 requests, 163 (9%) concerned a possible diagnosis of skin cancer and were eligible. For 61 cases, the histopathological findings were not available. Eventually, 93 patients with a total of 102 skin lesions were included. Median age was 75 years (range 26-97 years), with 53% women. The skin lesions had progressed for 8 months on average (range 0.5-36 months). The median response time was 1 day (range 0-61 days); 65 days (range 1-667 days) elapsed on average between the SAF opinion and the histological sample. Histopathology diagnosed 83 malignant lesions (57 basal cell carcinomas, 69%; 18 squamous cell carcinomas, 22%; 6 melanomas, 7%; 1 cutaneous lymphoma, 1%; 1 secondary location of a primary cancer, 1%), 1 precancerous lesion, and 18 benign lesions. The concordance between the opinion of the referent dermatologist and the final pathological finding was 83% for nonmelanocytic lesions and 67% for melanocytic lesions. Conclusions This study showed the reliability of SAF teledermatology in the diagnosis of skin cancer, comparable to literature data in the absence of dermatoscopy. The median delay of about two months between request and histology was an improvement compared to the delay of usual appointments in the intervention area. The lack of data for 61 patients showed that SAF telemedicine requires better coordination and follow-up, especially for the management of skin cancer. With this reservation in mind, teledermatology offers an alternative answer for the triage of patients with skin cancer residing in areas with low medical density. Conflicts of Interest None declared.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".