AI-Augmented Skin Cancer Diagnosis in Teledermatoscopy

NCT06080711 | Unknown

• 1 other identifier: 960024
• Study Type: interventional
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

In this study an artificial intelligence (AI) tool for skin cancer diagnosis is implemented in a teleldermatoscopy platform. The aim is to study the effects on clinician diagnostic accuracy, management decisions, and confidence. Furthermore, this prospective randomized study investigates the role of human factors in determining clinician reliance on AI tools and the consequent accuracy in a real-world setting.

Conditions

Skin Cancer; Melanoma

Keywords

melanoma; artificial intelligence; AI augmentation; deep learning; teledermatoscopy; dermatoscopy; skin cancer

Outcome Measures

Primary Outcomes (4)

• Diagnostic accuracy

  Determine sensitivity, specificity, accuracy and AUROC in terms of diagnostic accuracy for dermatologists with vs without AI advice. Further, to investigate the role of the different workflows (diagnosis with or without AI with varying sequencing) and the influence of demographics and human factors (e.g. level of experience) on diagnostic accuracy

  1 year

• Accuracy of management decisions

  Determine sensitivity, specificity, accuracy and AUROC in terms of accuracy for management decisions for dermatologists with vs without AI and investigate the role of the different workflows (with or without AI with varying sequencing) and the influence of demographics and human factors (e.g. level of experience) on management decisions (biopsy/surgery, no intervention, or follow-up)

  1 year

• Tendency to change initial diagnosis or management decision

  Evaluate which factors affect the likelihood of a physician changing their evaluation after receiving algorithmic input

  1 year

• Self-reported confidence in diagnosis and management decisions

  Investigate whether AI or other factors affect the physician's confidence in their diagnosis and management decisions

  1 year

Study Arms (3)

Workflow 1

NO INTERVENTION

Standard of care

Workflow 2

EXPERIMENTAL

Consult with AI assistance

Other: AI assistance

Workflow 3

EXPERIMENTAL

First workflow 1, then workflow 2

Other: AI assistance

Interventions

AI assistance OTHER

Participants will be informed of the diagnostic probabilities for each of ten differential diagnoses according to the AI tool

Workflow 2; Workflow 3

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Licensed physician
• Working at a dermatology clinic
• Sufficient knowledge in Swedish
• Written consent to participate

You may not qualify if:

• No experience of using dermatoscopy
• Does not wish to participate
• Incomplete answers
• Physicians that are involved in the patients' clinical care relating to the teledermoscopical consult

Sponsors & Collaborators

• Karolinska University Hospital: lead
• Karolinska Institutet: collaborator
• Medical University of Vienna: collaborator
• Stockholm School of Economics: collaborator

Study Sites (1)

Karolinska University Hospital

Stockholm, Sweden

Location

MeSH Terms

Conditions

Skin Neoplasms; Melanoma

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Skin Diseases; Skin and Connective Tissue Diseases; Neuroendocrine Tumors; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms by Histologic Type; Neoplasms, Nerve Tissue; Nevi and Melanomas

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: CROSSOVER
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: MD, PhD

Study Record Dates

• First Submitted: August 30, 2023
• First Posted: October 12, 2023
• Study Start: February 15, 2023
• Primary Completion: June 30, 2024
• Study Completion: October 30, 2024
• Last Updated: October 12, 2023

Record last verified: 2023-10

Data Sharing

• IPD Sharing: Will not share

Locations

SE (1)