Skin Cancer
Conditions
Keywords
Artificial Intelligence (AI), Primary care, Diagnostics
Brief summary
Background: Artificial intelligence has in numerous studies shown high accuracy in detecting skin cancer when trained on various databases of dermatoscopic images. However, there are very few prospective studies conducted in real clinical settings directed at patients seeking healthcare for assessment of skin lesions, and nosuch studies at all in primary care, where the majority of patients are managed. Project aim: To study the accuracy, reliability, and clinical utility of an AI-based decision support system (Dermalyser), developed for primary care, in distinguishing skin cancer from benign lesions. Method: Cluster-randomized controlled trial at approx. 30 primary care centers in Sweden, Germany, Scotland, the Netherlands and Australia. At study start, the participating primary care centres in each country are equally randomised to either be enabled to use the Dermalyser (intervention phase) or to assess patients according to the standard clinical procedure (control phase). When half of the intended sample size (i.e. 1500 of 3000 participants) have been included, the primary care centres switch phase from intervention to control, or vice versa. During the intervention phase, the physicians may use (if found indicated) Dermalyser as a part of their clinical evaluation, whereas during the control phase the physicians follow their ordinary diagnostic routine without support from Dermalyser. This will direct the participants to either an intervention or a control cohort. Both groups will be followed for up to 5 years, with regard to the tumour diagnoses, proportions of skin cancer/benign lesions, and morbidity and mortality in skin cancer. Possible between-group differences will be investigated statistically. Potential benefits: If the Dermalyser prooves to be safe and diagnotically reliability, it could enhance the chance of detecting skin cancer in early stage in primary care, and to reduce the proportion of benign skin lesion unnecessarily excised or referred to dermatologist.
Interventions
DEVICEArtificial inteligence based decision support to detect skin cancer
When assessing skin lesions in patients seeking primary care, the primary care physician may use the device to be evaluated in the study (Dermalyser) as a complementary diagnostic doecision support to differentiate skin cancers from benign skin lesions. However, the decision on clinical management of the lesion remains with the physician.
Sponsors
Karolinska Institutet
Göteborg University
Region Östergötland
Linkoeping University
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
DIAGNOSTIC
Masking
NONE
Intervention model description
Cross-over cluster-randomized clinical trial
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Patients attending a primary care facility in order to have one or more skin lesions checked for skin cancer, or patients presenting with one or more skin lesions raising suspicion of skin cancer when noticed by the primary care physician. * Willingness and ability to provide informed consent.
Exclusion criteria
* Individuals with skin type V and VI according to the Fitzpatrick's scale (darker brown or black coloured skin)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Proportion of skin cancers | From enrollment until all included lesions have been diagnosed following standard clinical investigation procedure, which we consider in the normal case will not exceed 6 months from inclusion. | Proportion of skin cancers (melanoma, SCC or BCC) excised or referred to dermatologists, as described in percentage of total number of skin lesions included. |
Countries
Sweden
Contacts
Primary ContactMagnus Falk, Professor
Backup ContactPanos Papachristou, MD, PhD
Outcome results
None listed