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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT05004792
Other study ID # AISC-DAHT, RCT
Secondary ID
Status Not yet recruiting
Phase N/A
First received
Last updated
Start date April 2025
Est. completion date December 2026

Study information

Verified date June 2024
Source Herlev Hospital
Contact Louisa Bønløkke Nervil
Phone 28356465
Email LouisaBoenloekke@gmail.com
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

Pathologists provide the current gold standard in skin lesion diagnostics, most often primarily based on the interpretation of histological slides. Still, it has been suggested that pathologists' diagnostic accuracy and confidence could be improved if they gained access to additional clinical information and in-vivo clinical and dermoscopic images of melanocytic tumors. This study examines the effect of digital training for pathologists in interpreting dermoscopic and clinical skin tumor images. Aim: To examine how case-based online training in interpreting clinical and dermoscopic images affects a pathologist's ability to diagnose skin tumors. Data collection of DAHT cases: Department of plastic surgery, Herlev hospital, year 2020-2021, DAHT platform: Made in 2021-2023 by Melatech, Consensus agreement: Four dermatopathologists assess all DAHT cases, year 2023-2024 Enrollment of pathologists: Randomization and assessment DAHT cases, year 2025.


Description:

Background Several publications suggest that the increasing melanoma incidence may partly be caused by histopathological overdiagnosis. Pathologists provide the current gold standard in skin lesion diagnostics, most often primarily based on the interpretation of histological slides. Still, it has been suggested that pathologists' diagnostic accuracy and confidence could be improved if they gained access to additional clinical information and in-vivo clinical and dermoscopic images of melanocytic tumors. However, it can be challenging to interpret clinical and dermoscopic images, and mastery typically requires more than six years of clinical experience. This learning journey can be significantly shortened if the trainee receives comprehensive training in pattern recognition for dermoscopy and clinical images, including immediate, accurate, and individualized feedback and access to a library with a large selection of skin lesion cases. This study examines the effect of digital training for pathologists in interpreting dermoscopic and clinical skin tumor images. Former studies have only focused on melanocytic lesions. Still, most pathologists will receive both melanocytic and pigmented non-melanocytic lesions (seborrheic keratoses, dermatofibromas, etc.) due to clinical suspicion of melanoma. This study includes an un-filtered selection of 211 clinically melanoma-suspect skin lesions excised at a specialized surgical department; this material is named the DAHT cases. Aim: To examine how case-based online training in interpreting clinical and dermoscopic images affects a pathologist's ability to diagnose skin tumors. Method Case Database Lesion data were collected from patients between 02.11.2020 and 22.01.2021 at the Department of Plastic Surgery, Herlev Hospital. Requirements for eligibility for the current study are: The patient was referred through the clinical cancer pathways for melanoma. The lesion was excised upon evaluation by the plastic surgeon. Patients received oral and written information about the project and were asked to sign a consent form before participation. The participation did not affect the included patients' treatment, diagnostics, or follow-up. Upon consent, the following information was collected for each lesion: Clinical image Dermoscopic image Patients´ CPR-number (personal ID-number) Sex and age of the patient Location of skin tumor (on a 3D avatar) Medical history (former treatment, congenital nevi, if pregnant, time of appearance of skin lesion, change in appearance, symptoms, former melanoma or other skin diseases, family history of melanoma, sun exposure within the last six months) After excision, the specimen was prepared for pathological examination and a representative hematoxylin-eosin stain and, if available, a MelanA stain for each skin lesion was chosen for the study by an experienced dermatopathologist. These stains were subsequently digitized and coupled with the relevant information (dermoscopic and clinical image, tumor location, sex, age, lesion information, etc.). The CPR number was deleted, rendering the case anonymous. Each case is stored in a database under a random anonymous ID number. Web-based IT platform To maximize the number of pathologists that can be included in the study, the investigators have developed an IT platform for the trial (The DAHT platform). The platform enables the following features: Sign-in Automated randomization Login Case presentation Diagnosis of cases and subquestions Tracking The diagnostic options will be based on the standardized MPATH-Dx version 2.0 with additional non-melanocytic options based on the most common diagnoses to be excised due to suspicion of malignancy. After diagnosing the lesion, participating pathologists will rate their confidence and difficulty in the chosen diagnosis on a 6-step Likert scale similar to the one used in the MPATH-Dx system. They will also be asked whether they want a second opinion, if they need additional stains or tests, and which tests/stains. All cases will be presented in a randomized order unique to each participant. The tracking feature will enable search pattern analysis, including time per diagnosis and percentage of time spent looking at the histology stain, dermoscopic image, clinical image, and clinical information. Executive phase General pathologists and dermatopathologists from Denmark, Australia, and other countries will be enrolled between 1.09.2023 and 1.12.2023. All participants will be sent an email informing them about the trial and the handling of their data before signing a digital consent. Upon inclusion, each enrolled pathologist will be asked to fill out a digital sign-in form with the following variables: Name E-mail address (including verification) Age Sex Country Subspecialization (general pathologist or dermatopathologist) Number of years interpreting skin lesions Caseload from melanocytic lesions per month Percentage of caseload from melanocytic lesions Number of second opinion assessments per month Number of second opinion referrals per month Former training in dermoscopy (yes/no) Perceived relevance of dermoscopic images during histopathological evaluation on a 5-step Likert scale Routine with the use of digitized slides Following the sign-in, all participants will be asked to answer a dermoscopy test consisting of 25 formerly validated test items. They will automatically be randomized (allocation ratio 1:1) to either the intervention or control group. Participants in the intervention group will receive immediate access to a previously developed digital (tablet or smartphone) educational platform for the dermoscopy of melanocytic lesions, watch educational videos on the correlation between dermoscopy and histology, and then answer the dermoscopy test again before diagnosing the lesions in this study. Participants in the control group will not be given access to the learning intervention but will diagnose the lesions from this study immediately after signing up and taking the dermoscopy test. Each participant will be asked to assess a minimum of 50 cases within 21 days, preferably all 211 cases. Statistics: The accuracy will be measured as the number of correct answers (validated by a former DAHT study: AISC-DAHT, consensus agreement) divided by the total number of answers. Inter-rater reliability will be measured using generalizability theory that allows calculations in nested and unbalanced designs. Mean time spent per diagnosis, perceived difficulty, and diagnostic confidence during the evaluation will be compared between the study groups using independent t-tests. A post hoc ANOVA will compare the time spent per diagnosis and the confidence of pathologists grouped by time spent training in dermoscopy.


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 300
Est. completion date December 2026
Est. primary completion date December 2025
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group N/A and older
Eligibility Inclusion Criteria: - Pathologists are required to evaluate melanocytic lesions routinely - Doctors must be registered authorized health personnel - Access to a smartphone/tablet/computer with internet Exclusion Criteria: - Assessment of less than 50 DAHT cases

Study Design


Related Conditions & MeSH terms


Intervention

Other:
DermLoop Learn
DermLoop Learn is our AI-augmented digital educational platform with case training on a library of 18,000+ benign and malignant skin lesions, educational videos on the correlation between dermoscopy and histology, as well as written learning modules for the most common skin lesion diagnosis. The education platform will give the user feedback on the image-based case training in dermoscopic diagnostic accuracy and adjust the cases depending on the user's progression.

Locations

Country Name City State
n/a

Sponsors (1)

Lead Sponsor Collaborator
Herlev Hospital

References & Publications (9)

Badertscher N, Tandjung R, Senn O, Kofmehl R, Held U, Rosemann T, Hofbauer GF, Wensing M, Rossi PO, Braun RP. A multifaceted intervention: no increase in general practitioners' competence to diagnose skin cancer (minSKIN) - randomized controlled trial. J Eur Acad Dermatol Venereol. 2015 Aug;29(8):1493-9. doi: 10.1111/jdv.12886. Epub 2014 Dec 10. — View Citation

Barnhill RL, Elder DE, Piepkorn MW, Knezevich SR, Reisch LM, Eguchi MM, Bastian BC, Blokx W, Bosenberg M, Busam KJ, Carr R, Cochran A, Cook MG, Duncan LM, Elenitsas R, de la Fouchardiere A, Gerami P, Johansson I, Ko J, Landman G, Lazar AJ, Lowe L, Massi D, Messina J, Mihic-Probst D, Parker DC, Schmidt B, Shea CR, Scolyer RA, Tetzlaff M, Xu X, Yeh I, Zembowicz A, Elmore JG. Revision of the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis Classification Schema for Melanocytic Lesions: A Consensus Statement. JAMA Netw Open. 2023 Jan 3;6(1):e2250613. doi: 10.1001/jamanetworkopen.2022.50613. — View Citation

Bedlow AJ, Cliff S, Melia J, Moss SM, Seyan R, Harland CC. Impact of skin cancer education on general practitioners' diagnostic skills. Clin Exp Dermatol. 2000 Mar;25(2):115-8. doi: 10.1046/j.1365-2230.2000.00590.x. — View Citation

Elmore JG, Barnhill RL, Elder DE, Longton GM, Pepe MS, Reisch LM, Carney PA, Titus LJ, Nelson HD, Onega T, Tosteson ANA, Weinstock MA, Knezevich SR, Piepkorn MW. Pathologists' diagnosis of invasive melanoma and melanocytic proliferations: observer accuracy and reproducibility study. BMJ. 2017 Jun 28;357:j2813. doi: 10.1136/bmj.j2813. Erratum In: BMJ. 2017 Aug 8;358:j3798. — View Citation

Ferrara G, Argenyi Z, Argenziano G, Cerio R, Cerroni L, Di Blasi A, Feudale EA, Giorgio CM, Massone C, Nappi O, Tomasini C, Urso C, Zalaudek I, Kittler H, Soyer HP. The influence of clinical information in the histopathologic diagnosis of melanocytic skin neoplasms. PLoS One. 2009;4(4):e5375. doi: 10.1371/journal.pone.0005375. Epub 2009 Apr 30. Erratum In: PLoS One. 2009;4(6). doi: 10.1371/annotation/512cb17b-934c-4a06-9dbb-114d43052a2b. — View Citation

Glasziou PP, Jones MA, Pathirana T, Barratt AL, Bell KJ. Estimating the magnitude of cancer overdiagnosis in Australia. Med J Aust. 2020 Mar;212(4):163-168. doi: 10.5694/mja2.50455. Epub 2019 Dec 19. Erratum In: Med J Aust. 2020 Apr;212(6):253. — View Citation

Scolyer RA, Soyer HP, Kelly JW, James C, McLean CA, Coventry BJ, Ferguson PM, Rawson RV, Mar VJ, de Menezes SL, Fishburn P, Stretch JR, Lee S, Thompson JF. Improving diagnostic accuracy for suspicious melanocytic skin lesions: New Australian melanoma clinical practice guidelines stress the importance of clinician/pathologist communication. Aust J Gen Pract. 2019 Jun;48(6):357-362. doi: 10.31128/AJGP-11-18-4759. — View Citation

Ternov NK, Vestergaard T, Holmich LR, Karmisholt K, Wagenblast AL, Klyver H, Hald M, Schollhammer L, Konge L, Chakera AH. Reliable test of clinicians' mastery in skin cancer diagnostics. Arch Dermatol Res. 2021 May;313(4):235-243. doi: 10.1007/s00403-020- — View Citation

Whiteman DC, Green AC, Olsen CM. The Growing Burden of Invasive Melanoma: Projections of Incidence Rates and Numbers of New Cases in Six Susceptible Populations through 2031. J Invest Dermatol. 2016 Jun;136(6):1161-1171. doi: 10.1016/j.jid.2016.01.035. Ep — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Diagnostic value Diagnostic accuracy according to specific diagnoses and sensitivity and specificity according to correct classification of malignant vs. benign lesions 1 month
Secondary Inter-rater reliability comparison of diagnosis between participants 1 month
Secondary time/case Average time spent on each case 1 month
Secondary Average time spent on each image Average time spent looking at the clinical image, dermoscopic image and histopathological image 1 month
Secondary use of clinical information Whether the participants use the clinical information and when they decide to do so (before/after looking at the images) 1 month
Secondary Self-rated diagnostic confidence participants average self-rated confidence on the cases 1 month
Secondary Perceived diagnostic difficulty participants average perceived diagnostic difficulty on the cases 1 month
Secondary Dermoscopy test results Difference between pre and post-dermoscopy tests 1 month
Secondary Second opinion Number of requested second opinions and the underlying reason 1 month
Secondary Needs for stains Needs for additional stains, including which stains 1 month
Secondary Needs for tests Needs for additional tests (NGS, etc.), including which tests 1 month
Secondary training time vs time spent/DAHT case Correlation between time spent training and time spent diagnosing DAHT cases. 1 month
Secondary MPATH-Dx specificity Specificity according to MPATH-Dx classifications 1 month
Secondary MPATH-Dx sensitivity Sensitivity according to MPATH-Dx classifications 1 month
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