Artificial Intelligent Decision Support for Skin Cancer Diagnostics in Primary Care

NCT ID: NCT06932172

Last Updated: 2026-01-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

3000 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-11-04

Study Completion Date

2031-12-31

Brief Summary

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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.

Detailed Description

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Conditions

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Skin Cancer

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

Cross-over cluster-randomized clinical trial
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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Possibility to use AI support

The primary care physician may use the AI decision support (Dermalyser) in their assessment of skin lesions.

Group Type EXPERIMENTAL

Artificial inteligence based decision support to detect skin cancer

Intervention Type DEVICE

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.

Control

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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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.

Intervention Type DEVICE

Eligibility Criteria

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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)
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Karolinska Institutet

OTHER

Sponsor Role collaborator

Göteborg University

OTHER

Sponsor Role collaborator

Region Östergötland

OTHER

Sponsor Role collaborator

Linkoeping University

OTHER_GOV

Sponsor Role lead

Responsible Party

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Magnus Falk

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Finspång Primary Healthcare Centre

Finspång, Docent, Sweden

Site Status RECRUITING

Valla Primary Healthcare Centre

Linköping, Docent, Sweden

Site Status RECRUITING

Kärna Primary Care Centre

Linköping, Docent, Sweden

Site Status RECRUITING

Mjölby Primary Care Centre

Mjölby, Docent, Sweden

Site Status RECRUITING

Vikbolandet Primary Care Centre

Norrköping, Docent, Sweden

Site Status RECRUITING

Åby Primary Healthcare Centre

Norrköping, Docent, Sweden

Site Status RECRUITING

Skärvet Primary Healthcare Centre

Vaxjo, Docent, Sweden

Site Status RECRUITING

Ekholmen Primary Healthcare Centre

Linköping, , Sweden

Site Status RECRUITING

Countries

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Sweden

Central Contacts

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Magnus Falk, Professor

Role: CONTACT

+46708106176

Panos Papachristou, MD, PhD

Role: CONTACT

+46702298892

Facility Contacts

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Moa Lundgren, M.D.

Role: primary

+4610105 92 60

Magnus Falk, M.D., Ph.D., Professor

Role: primary

+46708106176

Magnus Falk, M.D., Ph.D., Professor

Role: primary

+46708106176

Emil Kristensen, M.D.

Role: primary

+4610-105 99 10

John Berglund, M.D.

Role: primary

+46101059280

Hanna Skytt, M.D.

Role: primary

+4610105 93 10

Jon Pallon, M.D., Ph.D.

Role: primary

+4647058 97 50

My Söderholm, M.D.

Role: primary

+46768551533

References

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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.

Reference Type BACKGROUND
PMID: 37982736 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 38234043 (View on PubMed)

Other Identifiers

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2023-05996

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

CIV-23-03-042574

Identifier Type: -

Identifier Source: org_study_id

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