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The proposed study is a pivotal, multi-center retrospective reader study designed to determine whether the use of DermDx as a concurrent reading aid improves the performance of primary care physicians (PCPs) in diagnosing skin cancers.
The proposed study is a pivotal, multi-center retrospective reader study designed to determine whether the use of DermDx as a concurrent reading aid improves the performance of primary care physicians (PCPs) in diagnosing skin cancers.
DermDx is a deep learning-based algorithm that analyzes lesion images to detect skin cancer. The software does not have dedicated hardware and can accept as input any dermoscopic images taken with commercial dermoscopes.
Because the study is designed to investigate the change in the performance of the PCPs before and after seeing the device output, a single-arm study design has been used.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Double reading of all cases with and without software output | Double reading of all cases with and without software output |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| DermDx | Device | DermDx is a computer-aided diagnosis (CADx) software product that uses an AI-based algorithm to evaluate non-invasively captured images of skin lesions obtained from any commercially available dermoscopes. DermDx uses state-of-the-art deep neural network models that have been trained on a large database of dermoscopy images. DermDx analyzes the image of a new skin lesion and provides an output. |
| Measure | Description | Time Frame |
|---|---|---|
| The change in the diagnostic sensitivity of Primary Care Physicians (PCPs) with and without the use of DermDx in the diagnosis of lesions suspicious of skin cancer | The change in the diagnostic sensitivity of the PCPs with the use of DermDx results than without the use of DermDx results in the diagnosis of lesions suspicious of skin cancer, in comparison to the ground truth. | 6 months |
| The change in the diagnostic accuracy of Primary Care Physicians (PCPs) with and without the use of DermDx in the diagnosis of lesions suspicious of skin cancer | The change in the Area Under the Curve for the diagnosis of skin cancer lesions by PCPs with the use of DermDx results than without the use of DermDx results, in comparison to the ground truth. | 6 months |
| Measure | Description | Time Frame |
|---|---|---|
| The change in sensitivity of management decision of the Primary Care Physicians (PCPs) with and without the use of DermDx in the management of lesions suspicious of skin cancer. | The change in the sensitivity of the disease management decision of the PCPs with the use of DermDx results than without the use of DermDx results in the management of lesions suspicious of skin cancer, in comparison to the ground truth. |
| Measure | Description | Time Frame |
|---|---|---|
| The mean change in the confidence of the Primary Care Practitioners (PCPs) in their management decision for benign and malignant lesions respectively, with and without the DermDx results. | The mean change in the confidence of the PCPs in their management decision for benign and malignant lesions respectively, with and without DermDx results. This measure will show the mean change in confidence of the PCPs with and without the device for benign and malignant lesions respectively. |
Inclusion criteria:
Exclusion criteria:
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The study population will be selected from patients with lesions suspected of skin cancer
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| Name | Affiliation | Role |
|---|---|---|
| Majid Razmara, PhD | MetaOptima Technology Inc. | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Remote | North Augusta | South Carolina | 29860 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 27892996 | Background | Katragadda C, Finnane A, Soyer HP, Marghoob AA, Halpern A, Malvehy J, Kittler H, Hofmann-Wellenhof R, Da Silva D, Abraham I, Curiel-Lewandrowski C; International Society of Digital Imaging of the Skin (ISDIS)-International Skin Imaging Collaboration (ISIC) Group. Technique Standards for Skin Lesion Imaging: A Delphi Consensus Statement. JAMA Dermatol. 2017 Feb 1;153(2):207-213. doi: 10.1001/jamadermatol.2016.3949. | |
| 20231499 |
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The study protocol, documentation, data, and all other information generated will be held in strict confidence. No information concerning the study or the data will be released to any unauthorized third party without prior written approval of the sponsor. Cases will be assigned with a unique case identifier, which will be visible on each image and clinical information pertaining to the case, for tracking purposes.
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| ID | Term |
|---|---|
| D012878 | Skin Neoplasms |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |
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|
| 6 months |
| The accuracy of the disease management decision of the Primary Care Physicians (PCPs) with and without the use of DermDx in the management of lesions suspicious of skin cancer. | The change in the Area Under the Curve (AUC) for the disease management decision of the PCPs with the use of DermDx results than without the use of DermDx results for lesions suspicious of skin cancer, in comparison to the ground truth. | 6 months |
| Diagnostic specificity of Primary Care Physicians (PCPs) with and without the use of DermDx in the diagnosis of lesions suspicious of skin cancer | The diagnostic specificity of the PCPs with the use of DermDx results and without the use of DermDx results in the diagnosis of lesions suspicious of skin cancer, in comparison to the ground truth. | 6 months |
| The specificity of the disease management decision of the Primary Care Physicians (PCPs) with and without the use of DermDx in the management of lesions suspicious of skin cancer. | The specificity of the disease management decision of the PCPs with the use of DermDx results and without the use of DermDx results in the management of lesions suspicious of skin cancer, in comparison to the ground truth. | 6 months |
| 6 months |
| Background |
| Rogers HW, Weinstock MA, Harris AR, Hinckley MR, Feldman SR, Fleischer AB, Coldiron BM. Incidence estimate of nonmelanoma skin cancer in the United States, 2006. Arch Dermatol. 2010 Mar;146(3):283-7. doi: 10.1001/archdermatol.2010.19. |
| 11684447 | Background | Armstrong BK, Kricker A. The epidemiology of UV induced skin cancer. J Photochem Photobiol B. 2001 Oct;63(1-3):8-18. doi: 10.1016/s1011-1344(01)00198-1. |
| 22251204 | Background | Lomas A, Leonardi-Bee J, Bath-Hextall F. A systematic review of worldwide incidence of nonmelanoma skin cancer. Br J Dermatol. 2012 May;166(5):1069-80. doi: 10.1111/j.1365-2133.2012.10830.x. |
| 31896400 | Background | Gupta V, Sharma VK. Skin typing: Fitzpatrick grading and others. Clin Dermatol. 2019 Sep-Oct;37(5):430-436. doi: 10.1016/j.clindermatol.2019.07.010. Epub 2019 Jul 17. |
| 25320835 | Background | US Department of Health and Human Services. The Surgeon General's Call to Action to Prevent Skin Cancer. Washington (DC): Office of the Surgeon General (US); 2014. Available from http://www.ncbi.nlm.nih.gov/books/NBK247172/ |
| 12876486 | Background | Carlson JA. Tumor doubling time of cutaneous melanoma and its metastasis. Am J Dermatopathol. 2003 Aug;25(4):291-9. doi: 10.1097/00000372-200308000-00003. |
| 24516469 | Background | Hajdarevic S, Hornsten A, Sundbom E, Isaksson U, Schmitt-Egenolf M. Health-care delay in malignant melanoma: various pathways to diagnosis and treatment. Dermatol Res Pract. 2014;2014:294287. doi: 10.1155/2014/294287. Epub 2014 Jan 5. |
| 24204060 | Background | Roetzheim RG, Lee JH, Ferrante JM, Gonzalez EC, Chen R, Fisher KJ, Love-Jackson K, McCarthy EP. The influence of dermatologist and primary care physician visits on melanoma outcomes among Medicare beneficiaries. J Am Board Fam Med. 2013 Nov-Dec;26(6):637-47. doi: 10.3122/jabfm.2013.06.130042. |
| 28784330 | Background | Ehrlich A, Kostecki J, Olkaba H. Trends in dermatology practices and the implications for the workforce. J Am Acad Dermatol. 2017 Oct;77(4):746-752. doi: 10.1016/j.jaad.2017.06.030. Epub 2017 Aug 4. |
| 30193349 | Background | Feng H, Berk-Krauss J, Feng PW, Stein JA. Comparison of Dermatologist Density Between Urban and Rural Counties in the United States. JAMA Dermatol. 2018 Nov 1;154(11):1265-1271. doi: 10.1001/jamadermatol.2018.3022. |
| 28146246 | Background | Glazer AM, Farberg AS, Winkelmann RR, Rigel DS. Analysis of Trends in Geographic Distribution and Density of US Dermatologists. JAMA Dermatol. 2017 Apr 1;153(4):322-325. doi: 10.1001/jamadermatol.2016.5411. No abstract available. |
| 31201137 | Background | Tschandl P, Codella N, Akay BN, Argenziano G, Braun RP, Cabo H, Gutman D, Halpern A, Helba B, Hofmann-Wellenhof R, Lallas A, Lapins J, Longo C, Malvehy J, Marchetti MA, Marghoob A, Menzies S, Oakley A, Paoli J, Puig S, Rinner C, Rosendahl C, Scope A, Sinz C, Soyer HP, Thomas L, Zalaudek I, Kittler H. Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study. Lancet Oncol. 2019 Jul;20(7):938-947. doi: 10.1016/S1470-2045(19)30333-X. Epub 2019 Jun 12. |
| 37775188 | Background | Menzies SW, Sinz C, Menzies M, Lo SN, Yolland W, Lingohr J, Razmara M, Tschandl P, Guitera P, Scolyer RA, Boltz F, Borik-Heil L, Herbert Chan H, Chromy D, Coker DJ, Collgros H, Eghtedari M, Corral Forteza M, Forward E, Gallo B, Geisler S, Gibson M, Hampel A, Ho G, Junez L, Kienzl P, Martin A, Moloney FJ, Regio Pereira A, Ressler JM, Richter S, Silic K, Silly T, Skoll M, Tittes J, Weber P, Weninger W, Weiss D, Woo-Sampson P, Zilberg C, Kittler H. Comparison of humans versus mobile phone-powered artificial intelligence for the diagnosis and management of pigmented skin cancer in secondary care: a multicentre, prospective, diagnostic, clinical trial. Lancet Digit Health. 2023 Oct;5(10):e679-e691. doi: 10.1016/S2589-7500(23)00130-9. |
| 32182298 | Background | Madeja J, Kelsberg G, Safranek S. Does screening by primary care providers effectively detect melanoma and other skin cancers? J Fam Pract. 2020 Mar;69(2):E10-E12. No abstract available. |
| 37933569 | Background | Jaklitsch E, Thames T, de Campos Silva T, Coll P, Oliviero M, Ferris LK. Clinical Utility of an AI-powered, Handheld Elastic Scattering Spectroscopy Device on the Diagnosis and Management of Skin Cancer by Primary Care Physicians. J Prim Care Community Health. 2023 Jan-Dec;14:21501319231205979. doi: 10.1177/21501319231205979. |
| 38143790 | Background | Manolakos D, Patrick G, Geisse JK, Rabinovitz H, Buchanan K, Hoang P, Rodriguez-Diaz E, Bigio IJ, Cognetta AB. Use of an elastic-scattering spectroscopy and artificial intelligence device in the assessment of lesions suggestive of skin cancer: A comparative effectiveness study. JAAD Int. 2023 Oct 11;14:52-58. doi: 10.1016/j.jdin.2023.08.019. eCollection 2024 Mar. |