A Pilot Study of an Artificial Intelligence System as a Diagnostic Aid to Improve Skin Cancer Management (04.17 SMARTI)
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 200
- 试验地点
- 4
- 主要终点
- Diagnostic accuracy of the device when compared prospectively to a teledermatologist assesment
研究概览
简要总结
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.
详细描述
This is a pilot study which aims to establish whether artificial intelligence can be used as a diagnostic aid to improve diagnostic accuracy and outcomes in the specialist setting prior to conducting a much larger trial of the intervention in primary care.
Objectives:
- To establish whether the diagnostic accuracy of an artificial intelligence system is on par with teledermatologists' clinical assessment.
- To establish the safety and feasibility of offering artificial intelligence as a diagnostic aid prior to conducting a large trial of the intervention in primary care.
Hypotheses:
- The AI algorithm will have diagnostic accuracy comparable with a teledermatologists' assessment.
- The AI algorithm will have a diagnostic accuracy more conservative (i.e. more false positives) than dermatologists in the clinical setting.
- The AI algorithm will have greater diagnostic accuracy than the registrar.
- The AI algorithm will lead to a reduction in the number of biopsies performed by the registrar the likely impact of which will be reduced cost to patients and the healthcare system.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Sequential
- 主要目的
- Diagnostic
- 盲法
- Single (Outcomes Assessor)
盲法说明
Teledermatologist will be blinded to the Artificial Intelligence algorithm diagnosis.
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients attending the specialist dermatology clinics for skin cancer assessment or surveillance.
- •Patients may or may not have a lesion of concern.
- •Patients must have at least two lesions imaged during full skin examination by a dermatologist.
- •Age greater than 18 years.
- •Participant is willing and able to undertake investigation of suspicious lesion (e.g. skin biopsy).
排除标准
- •Patient does not give informed consent.
- •Patient is unable or unwilling to have a full skin examination
- •Patient has a known past or current diagnosis of cognitive impairment
结局指标
主要结局
Diagnostic accuracy of the device when compared prospectively to a teledermatologist assesment
时间窗: 12 months
Sensitivity and specificity of the algorithm compared to the teledermatologist.
次要结局
- Appropriate selection of lesions by registrar compared to specialist dermatologists(12 months)
- Appropriateness of management by registrar compared to specialist dermatologists and impact AI might have on this.(12 months)
- Diagnostic accuracy of the device when used prospectively as compared to a dermatologist assessment(12 months)
- Diagnostic accuracy of the device compared to teledermatologist, dermatologist and registrar using histopathology as 'gold standard' for any lesions biopsied.(12 months)