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| Name | Class |
|---|---|
| Innovate UK | OTHER_GOV |
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This study aims to provide an initial assessment of the potential impact DERM could have on the number of onward referrals for a face to face dermatologist review and/or biopsy from a teledermatology-based service, and to improve the understanding of the patient pathways that exist.
DERM, an Artificial Intelligence (AI)-based diagnosis support tool, has been shown to be able to accurately identify melanoma, non-melanoma skin cancers (NMSC) and other conditions from historical images of suspicious skin lesions (moles).
This study aims to establish whether the use of DERM in the patient pathway could reduce the number of unnecessary referrals to dermatologist review and/or biopsy.
Suspicious skin lesions that are due to be photographed for a dermatologist to review, will have two additional photographs taken using a commonly available smart phone camera with and without a specific lens attachment. The images will be analysed by DERM, and the results compared to the clinician's diagnosis (all lesions) and histologically-confirmed diagnosis (any lesion that is biopsied).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| All | Patients attending a Medical Photography facility with at least 1 suspicious skin lesion will be approached to participate in the study. Participants will have an additional macro and dermoscopic image of each suspicious skin lesions suitable for photography. Photographs will be taken by a healthcare professional using an iPhone XR smart phone camera with a DL1 dermoscopic lens attachment. The images will be encrypted and electronically transmitted to Skin Analytics' cloud servers for analysis by DERM. The suspected diagnosis determined by DERM will be compared with dermatologist review and histologically confirmed diagnosis, where obtained. Healthcare resource utilization information and patient satisfaction data will also be collected |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Deep Ensemble for the Recognition of Malignancy (DERM) | Device | AI-based decision support tool |
|
| Measure | Description | Time Frame |
|---|---|---|
| Referral rate | The rate of unnecessary referrals for a face to face dermatologist review for the same detection rate between standard of care and DERM of lesions reviewed by teledermatology or DERM | Study completion, on average 5 days |
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity of DERM on biopsied lesions | Sensitivity of DERM on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Specificity of DERM on biopsied lesions |
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Inclusion Criteria:
Exclusion Criteria:
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Adult patients attending Medical Photography for imaging of at least 1 suspicious skin lesion. Patients may have been referred to the teledermatology service or for imaging for monitoring purposes from the dermatology clinic or for virtual teledermatology review.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Chelsea and Westminster Hospital | London | SW10 9NH | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38585154 | Derived | Marsden H, Kemos P, Venzi M, Noy M, Maheswaran S, Francis N, Hyde C, Mullarkey D, Kalsi D, Thomas L. Accuracy of an artificial intelligence as a medical device as part of a UK-based skin cancer teledermatology service. Front Med (Lausanne). 2024 Mar 22;11:1302363. doi: 10.3389/fmed.2024.1302363. eCollection 2024. |
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Research to improve or test the performance of DERM only allowed in consent
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| ID | Term |
|---|---|
| D008545 | Melanoma |
| ID | Term |
|---|---|
| D018358 | Neuroendocrine Tumors |
| D017599 | Neuroectodermal Tumors |
| D009373 | Neoplasms, Germ Cell and Embryonal |
| D009370 | Neoplasms by Histologic Type |
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Specificity of DERM on biopsied lesions, using histopathological confirmed diagnosis as gold-standard
| Study completion, on average 5 days |
| False positive rate of DERM on biopsied lesions | False positive rate of DERM on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| False negative rate of DERM on biopsied lesions | False negative rate of DERM on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Positive predictive value of DERM on biopsied lesions | Positive predictive value of DERM on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Number needed to biopsy by DERM on biopsied lesions | Number needed to biopsy by DERM on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Sensitivity of teledermatologists on biopsied lesions | Sensitivity of teledermatologists on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Specificity of teledermatologists on biopsied lesions | Specificity of teledermatologists on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| False positive rate of teledermatologists on biopsied lesions | False positive rate of teledermatologists on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| False negative rate of teledermatologists on biopsied lesions | False negative rate of teledermatologists on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Positive predictive value of teledermatologists on biopsied lesions | Positive predictive value of teledermatologists on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Negative predictive value of teledermatologists on biopsied lesions | Negative predictive value of teledermatologists on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Number needed to biopsy by teledermatologists on biopsied lesions | Number needed to biopsy by teledermatologists on biopsied lesions, using histopathological confirmed diagnosis as gold-standard | Study completion, on average 5 days |
| Sensitivity of DERM to identify benign conditions | Sensitivity of DERM to identify benign conditions, using clinical diagnosis as gold-standard | Study completion, on average 5 days |
| Specificity of DERM to identify benign conditions | Specificity of DERM to identify benign conditions, using clinical diagnosis as gold-standard | Study completion, on average 5 days |
| False positive rate of DERM to identify benign conditions | False positive of DERM to identify benign conditions, using clinical diagnosis as gold-standard | Study completion, on average 5 days |
| False negative rate of DERM to identify benign conditions | False negative rate of DERM to identify benign conditions, using clinical diagnosis as gold-standard | Study completion, on average 5 days |
| Positive predictive value of DERM to identify benign conditions | Positive predictive of DERM to identify benign conditions, using clinical diagnosis as gold-standard | Study completion, on average 5 days |
| Negative predictive value of DERM to identify benign conditions | Negative predictive value of DERM to identify benign conditions, using clinical diagnosis as gold-standard | Study completion, on average 5 days |
| Number needed to refer by DERM to identify benign conditions | Number needed to refer by DERM to identify benign conditions, using clinical diagnosis as gold-standard | Study completion, on average 5 days |
| Concordance of DERM result with clinical diagnosis | Concordance of DERM result with clinical diagnosis | Study completion, on average 5 days |
| Percent of patients attending teledermatology by referral route | Percentage of patients referred to teledermatology through 2-week wait referral, general referral, direct to teledermatology, routine follow-up (etc) referral routes | Study completion, on average 5 days |
| Time taken from general practitioner (GP) referral to diagnosis | Time taken (days) from GP referral to either histopathology-confirmed or clinical diagnosis | Study completion, on average 5 days |
| Estimated cost impact associated with introducing DERM into the patient pathway | The cost of the number of referrals for face to face dermatologist review and/or biopsy that would have been saved / charged if DERM had been used to decide whether to refer the patient onwards | Study completion, on average 5 days |
| Proportion of images submitted to DERM that cannot be analysed | Proportion of images submitted to DERM that cannot be analysed | Study completion, on average 5 days |
| Patient satisfaction survey | Patient feedback on their experience of the service. Patients will rate whether they agree, or don't agree, with statements that assess their acceptance of having a computer involved in their diagnosis pathway | Study completion, on average 5 days |
| D009369 | Neoplasms |
| D009380 | Neoplasms, Nerve Tissue |
| D018326 | Nevi and Melanomas |
| D012878 | Skin Neoplasms |
| D009371 | Neoplasms by Site |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |