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Trial details imported from ClinicalTrials.gov
For full trial details, please see the original record at
https://clinicaltrials.gov/study/NCT04040114
Registration number
NCT04040114
Ethics application status
Date submitted
29/07/2019
Date registered
31/07/2019
Titles & IDs
Public title
Improving Skin Cancer Management With Artificial Intelligence (04.17 SMARTI)
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Scientific title
A Pilot Study of an Artificial Intelligence System as a Diagnostic Aid to Improve Skin Cancer Management (04.17 SMARTI)
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Secondary ID [1]
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04.17
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Universal Trial Number (UTN)
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Trial acronym
SMARTI
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Skin Cancer
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Melanoma (Skin)
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Condition category
Condition code
Cancer
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Malignant melanoma
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Cancer
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Non melanoma skin cancer
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Intervention/exposure
Study type
Interventional
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Description of intervention(s) / exposure
Treatment: Devices - Molemap Skin Cancer Triage Artificial Intelligence Device
No intervention: Lead-in phase - During the lead-in phase treating clinicians will not be given the Molemap artificial intelligence diagnosis in real-time (i.e. in clinic with the patient).
Active comparator: Active phase - During the active phase treating clinicians will be given the Molemap artificial intelligence diagnosis in real-time.
Treatment: Devices: Molemap Skin Cancer Triage Artificial Intelligence Device
This device/software incorporates artificial intelligence to provide a diagnostic aide for clinicians of patients with potentially malignant skin lesions. The software is supported by the use of cameras for acquisition of images.
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Intervention code [1]
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Treatment: Devices
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Comparator / control treatment
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Control group
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Outcomes
Primary outcome [1]
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Diagnostic accuracy of the device when compared prospectively to a teledermatologist assesment
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Assessment method [1]
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Sensitivity and specificity of the algorithm compared to the teledermatologist.
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Timepoint [1]
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12 months
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Secondary outcome [1]
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Diagnostic accuracy of the device when used prospectively as compared to a dermatologist assessment
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Assessment method [1]
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Sensitivity and specificity of the algorithm compared to the dermatologist.
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Timepoint [1]
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12 months
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Secondary outcome [2]
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Diagnostic accuracy of the device compared to teledermatologist, dermatologist and registrar using histopathology as 'gold standard' for any lesions biopsied.
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Assessment method [2]
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Sensitivity and specificity of the algorithm compared to histopathology of any lesions biopsied.
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Timepoint [2]
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12 months
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Secondary outcome [3]
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Appropriate selection of lesions by registrar compared to specialist dermatologists
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Assessment method [3]
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This will be assessed by comparing the lesions selected for review by the registrar with the lesions selected by the dermatologist.
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Timepoint [3]
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12 months
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Secondary outcome [4]
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Appropriateness of management by registrar compared to specialist dermatologists and impact AI might have on this.
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Assessment method [4]
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This will be assessed by comparing the registrars clinical assessment with the dermatologists clinical assessment and if providing the AI assessment in real time has an impact.
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Timepoint [4]
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12 months
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Eligibility
Key inclusion criteria
1. Patients attending the specialist dermatology clinics for skin cancer assessment or surveillance.
2. Patients may or may not have a lesion of concern.
3. Patients must have at least two lesions imaged during full skin examination by a dermatologist.
4. Age greater than 18 years.
5. Participant is willing and able to undertake investigation of suspicious lesion (e.g. skin biopsy).
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Minimum age
18
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
No
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Key exclusion criteria
1. Patient does not give informed consent.
2. Patient is unable or unwilling to have a full skin examination
3. Patient has a known past or current diagnosis of cognitive impairment
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Study design
Purpose of the study
Diagnosis
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Allocation to intervention
Non-randomised trial
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Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
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Methods used to generate the sequence in which subjects will be randomised (sequence generation)
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Masking / blinding
Blinded (masking used)
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Who is / are masked / blinded?
The people assessing the outcomes
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Intervention assignment
Other
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Other design features
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Phase
NA
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Type of endpoint/s
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Statistical methods / analysis
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Recruitment
Recruitment status
Completed
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Data analysis
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Reason for early stopping/withdrawal
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Other reasons
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Date of first participant enrolment
Anticipated
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Actual
1/10/2019
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Date of last participant enrolment
Anticipated
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Actual
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Date of last data collection
Anticipated
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Actual
30/05/2021
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Sample size
Target
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Accrual to date
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Final
200
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Recruitment in Australia
Recruitment state(s)
VIC
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Recruitment hospital [1]
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The Alfred- Victorian Melanoma Service - Melbourne
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Recruitment hospital [2]
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Skin Health Institute - Melbourne
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Recruitment postcode(s) [1]
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3004 - Melbourne
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Recruitment postcode(s) [2]
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3053 - Melbourne
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Funding & Sponsors
Primary sponsor type
Other
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Name
Melanoma and Skin Cancer Trials Limited
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Address
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Country
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Other collaborator category [1]
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Other
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Name [1]
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Monash University
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Address [1]
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Country [1]
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Ethics approval
Ethics application status
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Summary
Brief summary
The study is designed to be able to prove if the Molemap Artificial Intelligence (AI) algorithm can be used as a diagnostic aid in a clinical setting. This study will determine whether the diagnostic accuracy of the Molemap AI algorithm is comparable to a specialist dermatologist, teledermatologist and registrar (as a surrogate for a general practitioner). The study patient population will be adult patients who require skin cancer assessment. The use of AI as a diagnostic aid may assist primary care physicians who have variable skill in skin cancer diagnosis and lead to more appropriate referrals (rapid referral for lesions requiring treatment and fewer referrals for benign lesions), thereby improving access and reducing waiting times for specialist care.
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Trial website
https://clinicaltrials.gov/study/NCT04040114
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Trial related presentations / publications
Felmingham C, MacNamara S, Cranwell W, Williams N, Wada M, Adler NR, Ge Z, Sharfe A, Bowling A, Haskett M, Wolfe R, Mar V. Improving Skin cancer Management with ARTificial Intelligence (SMARTI): protocol for a preintervention/postintervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a specialist dermatology setting. BMJ Open. 2022 Jan 4;12(1):e050203. doi: 10.1136/bmjopen-2021-050203.
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Public notes
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Contacts
Principal investigator
Name
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Victoria Mar, A/Prof
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Address
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Monash University, Australia
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Country
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Phone
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Fax
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Email
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Contact person for public queries
Name
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Address
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Country
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Phone
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Fax
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Email
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Contact person for scientific queries
Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
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No/undecided IPD sharing reason/comment
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What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
No documents have been uploaded by study researchers.
Results not provided in
https://clinicaltrials.gov/study/NCT04040114