Artificial Intelligent Decision Support for Skin Cancer Diagnostics in Primary Care

Official title

Artificial Intelligent Decision Support for Skin Cancer Diagnostics in Primary Care - a Multicentre Randomized Controlled Trial.

Overview

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

• Device Artificial 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.

Primary outcome measures

• Proportion of skin cancers [Time frame: 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.]

Eligibility criteria

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)

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation

Randomized

Model

Crossover

Masking

Open label

Primary purpose

Diagnostic

Study locations

Sweden · 8 centers

• Finspång Primary Healthcare Centre — Finspång
• Valla Primary Healthcare Centre — Linköping
• Kärna Primary Care Centre — Linköping
• Mjölby Primary Care Centre — Mjölby
• Vikbolandet Primary Care Centre — Norrköping
• Åby Primary Healthcare Centre — Norrköping
• Skärvet Primary Healthcare Centre — Vaxjo
• Ekholmen Primary Healthcare Centre — Linköping

Publications

• Helenason J, Ekstrom C, Falk M, Papachristou P. Exploring the feasibility of an artificial intelligence based clinical decision support system for cutaneous melanoma detection in primary care - a mixed method study. Scand J Prim Health Care. 2024 Mar;42(1):51-60. doi: 10.1080/02813432.2023.2283190. Epub 2024 Feb 7. PMID 37982736
• Papachristou P, Soderholm M, Pallon J, Taloyan M, Polesie S, Paoli J, Anderson CD, Falk M. Evaluation of an artificial intelligence-based decision support for the detection of cutaneous melanoma in primary care: a prospective real-life clinical trial. Br J Dermatol. 2024 Jun 20;191(1):125-133. doi: 10.1093/bjd/ljae021. PMID 38234043

Identifiers

NCT: NCT06932172 · CIV-23-03-042574 · 2023-05996

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗