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Artificial Intelligence Augmented Training in Skin Cancer Diagnostics for General Practitioners (AISC-GP)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04576416
Recruitment Status : Not yet recruiting
First Posted : October 6, 2020
Last Update Posted : March 16, 2022
Sponsor:
Information provided by (Responsible Party):
Gustav Gede Nervil, Herlev Hospital

Brief Summary:

Background:

The worldwide incidence of skin cancer has been rising for 50 years, in particular the incidence of malignant melanoma has increased approx. 2-7% annually and is the most common cancer amongst Danes aged 15-34. Currently there is a significant amount of misdiagnosis of skin cancer and mole cancer. Our aim is to improve general practitioners' diagnostic skills and accuracy of skin and mole cancer.

Research questions:

In a population of Danish General Practitioners (GPs) what is the dose/response effect of hours spent with an educational platform that offers AI augmented training and clinical feedback on their diagnostic accuracy and accurate clinical management (treatment, dismissal, referral)? Does access to an educational platform that offers AI augmented training and clinical feedback increase the number of malignant skin lesions referred by Danish GPs without simultaneously increasing the number of incorrect benign referrals? Can the participating GPs clinical accuracy be predicted from the MCQ-score by comparing their quiz answers and diagnostic accuracy on their registered lesions with their score on the MCQ?

Method:

90 Danish GPs will at baseline, 1 month and end of trial answer a Multiple Choice Questionnaire (MCQ). There is no change to current clinical practice, but all participating doctors will be asked to register a clinical picture and a dermoscopic image as well as basic information about the lesion and patient (age, gender, location and diagnosis) of all skin lesions examined due to a suspicion for non-melanoma or melanoma skin cancer, raised by the GP or patient.

GPs in the intervention group are besides the registration application (R-app) given access to an AI augmented training and clinical feedback through an educational smartphone app (E-app). Within the E-app the doctor can access quizzes on a library of 10,000+ skin lesions, written articles about the 40 most common skin lesions, and a clinical feedback module that gives the GP feedback on their registered skin lesions.

Feedback on skin lesions with the registered clinical management of referred/excised/biopsied will be provided continuously by independent experts in skin cancer diagnostics (>10 years of experience) through a web-based review system developed by our group. Feedback on the remaining registered cases are withheld until the end of the study period. This is done to simulate a realistic clinical setting during the study.


Condition or disease Intervention/treatment Phase
Melanoma Skin Cancer Other: AI augmented training and clinical feedback Not Applicable

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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 90 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Intervention Model Description: A randomized superiority clinical trial. Participating doctors are stratified and randomized to either intervention or control in a 3:1 allocation ratio.
Masking: Single (Outcomes Assessor)
Masking Description:

Participating doctors are either given access to an AI augmented digital educational platform or not. During the study period, both doctors of the intervention and control arm are registering skin lesions they encounter in their daily practice.

The expert dermatologists that evaluate the registered skin lesions are unaware of the registering doctors allocation.

Primary Purpose: Diagnostic
Official Title: Artificial Intelligence Augmented Training of Danish General Practitioners in Skin Cancer Diagnostics - A Randomized Superiority Clinical Trial
Estimated Study Start Date : August 1, 2022
Estimated Primary Completion Date : December 15, 2022
Estimated Study Completion Date : May 31, 2023

Resource links provided by the National Library of Medicine

MedlinePlus Genetics related topics: Melanoma
MedlinePlus related topics: Skin Cancer

Arm Intervention/treatment
Experimental: Intervention
During the three months the intervention group will receive access to the AI augmented digital educational platform and its two modules (Training Module and Clinical Feedback Module). They will receive continuous clinical feedback on their registered lesions.
Other: AI augmented training and clinical feedback

The educational platform has two modules:

The training module includes AI enhanced case training on a library of 10,000+ benign and malignant skin lesion cases each coupled to written learning modules. Participants will be able to track their progression through automatically generated performance statistics and discuss difficult cases with peers within the application.

Clinical feedback is defined as diagnostic feedback on all cases registered in the registration module. Feedback during the trial will be based on either histopathology or the consensus agreement of domain experts (if no biopsy is taken). Feedback on referred or dismissed skin lesions will be provided by independent experts in skin cancer diagnostics ( >10 years of experience) through a web-based review system developed by our group.


No Intervention: Control
The control group continues its standard clinical practice without access to the E-app, but does register skin lesions throughout the full 3 month period.



Primary Outcome Measures :
  1. Time spent on educational materials [ Time Frame: Participants are assessed over a period of 5 months. ]
    The participants time spend with the digital educational platform is measured by the platform.

  2. Change in diagnostic accuracy [ Time Frame: Participants are assessed over a period of 5 months. ]
    The change in diagnostic accuracy is measured as percentage of correctly diagnosed skin lesions.

  3. Benign/Malignant Ratio [ Time Frame: Participants are assessed over a period of 5 months. ]
    All registered lesions will be evaluated by a expert dermatologist. Using the expert opinion as golden standard a ratio of the benign and malignant skin lesions forwarded by the General Practitioner is calculated.


Secondary Outcome Measures :
  1. Multiple-Choice-Questionnaire predictability of diagnostic accuracy [ Time Frame: Participants are assessed over a period of 5 months. ]
    Participants will answer a 12-item multiple choice test at baseline, after 1 and 3 months. The multiple-choice-questionnaire is validated and descriped here: https://doi.org/10.1007/s00403-020-02097-8 A correlation between the participants MCQ score and their clinical diagnostic accuracy is calculated. A high score correlates to high diagnostic accuracy (better).



Information from the National Library of Medicine

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Ages Eligible for Study:   Child, Adult, Older Adult
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Criteria

Inclusion criteria:

  • Participating doctors are required to have a danish doctors authorization and work at least 4 days a week in a general practitioners office.
  • The participating doctors may register skin lesions on patients of all ages with skin lesions suspected of skin cancer. A skin lesion is for the purpose of this study defined as a mole or tumor that either patient or GP raises suspicion of skin cancer about.

Exclusion criteria:

  • Doctors that have participated in a small qualitative pilot study are excluded.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04576416


Contacts
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Contact: Gustav G Nervil, MD 004538689236 gustav.gede.nervil@regionh.dk

Sponsors and Collaborators
Herlev Hospital
Investigators
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Principal Investigator: Gustav G Nervil, MD Research Unit of Plastic Surgery, Herlev Hospital
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Responsible Party: Gustav Gede Nervil, Principal Investigator, Herlev Hospital
ClinicalTrials.gov Identifier: NCT04576416    
Other Study ID Numbers: AISC-GP
First Posted: October 6, 2020    Key Record Dates
Last Update Posted: March 16, 2022
Last Verified: March 2022

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Gustav Gede Nervil, Herlev Hospital:
Artificial Intelligence
Education
Diagnostic Accuracy
Skin Cancer
Additional relevant MeSH terms:
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Skin Neoplasms
Neoplasms
Neoplasms by Site
Skin Diseases