scholarly journals Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies

BMJ ◽  
2020 ◽  
pp. m645
Keyword(s):  
Systematic Review ◽  
Skin Cancer ◽  
Diagnostic Accuracy ◽  
Smartphone Apps

scholarly journals Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies

BMJ ◽  
2020 ◽  
pp. m127 ◽  
Author(s):  
Karoline Freeman ◽  
Jacqueline Dinnes ◽  
Naomi Chuchu ◽  
Yemisi Takwoingi ◽  
Sue E Bayliss ◽  
...  
Keyword(s):  
Systematic Review ◽  
Skin Cancer ◽  
Diagnostic Accuracy ◽  
Test Performance ◽  
Skin Lesions ◽  
Premalignant Lesions ◽  
Cochrane Central Register ◽  
Smartphone Apps ◽  
Expert Recommendations

Abstract Objective To examine the validity and findings of studies that examine the accuracy of algorithm based smartphone applications (“apps”) to assess risk of skin cancer in suspicious skin lesions. Design Systematic review of diagnostic accuracy studies. Data sources Cochrane Central Register of Controlled Trials, MEDLINE, Embase, CINAHL, CPCI, Zetoc, Science Citation Index, and online trial registers (from database inception to 10 April 2019). Eligibility criteria for selecting studies Studies of any design that evaluated algorithm based smartphone apps to assess images of skin lesions suspicious for skin cancer. Reference standards included histological diagnosis or follow-up, and expert recommendation for further investigation or intervention. Two authors independently extracted data and assessed validity using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2 tool). Estimates of sensitivity and specificity were reported for each app. Results Nine studies that evaluated six different identifiable smartphone apps were included. Six verified results by using histology or follow-up (n=725 lesions), and three verified results by using expert recommendations (n=407 lesions). Studies were small and of poor methodological quality, with selective recruitment, high rates of unevaluable images, and differential verification. Lesion selection and image acquisition were performed by clinicians rather than smartphone users. Two CE (Conformit Europenne) marked apps are available for download. No published peer reviewed study was found evaluating the TeleSkin skinScan app. SkinVision was evaluated in three studies (n=267, 66 malignant or premalignant lesions) and achieved a sensitivity of 80% (95% confidence interval 63% to 92%) and a specificity of 78% (67% to 87%) for the detection of malignant or premalignant lesions. Accuracy of the SkinVision app verified against expert recommendations was poor (three studies). Conclusions Current algorithm based smartphone apps cannot be relied on to detect all cases of melanoma or other skin cancers. Test performance is likely to be poorer than reported here when used in clinically relevant populations and by the intended users of the apps. The current regulatory process for awarding the CE marking for algorithm based apps does not provide adequate protection to the public. Systematic review registration PROSPERO CRD42016033595.

scholarly journals Development of Smartphone Apps for Skin Cancer Risk Assessment: Progress and Promise (Preprint)

2019 ◽  
Author(s):  
Tiago M de Carvalho ◽  
Eline Noels ◽  
Marlies Wakkee ◽  
Andreea Udrea ◽  
Tamar Nijsten
Keyword(s):  
Health Care ◽  
Skin Cancer ◽  
Diagnostic Accuracy ◽  
General Practitioners ◽  
Mobile Health ◽  
Smartphone Apps ◽  
Screening Programs ◽  
Cancer Management ◽  
Health Apps ◽  
Mobile Health Apps

UNSTRUCTURED Skin cancer is a growing public health problem. Early and accurate detection is important, since prognosis and cost of treatment are highly dependent on cancer stage at detection. However, access to specialized health care professionals is not always straightforward, and population screening programs are unlikely to become implemented. Furthermore, there is a wide margin for improving the efficiency of skin cancer diagnostics. Specifically, the diagnostic accuracy of general practitioners and family physicians in differentiating benign and malignant skin tumors is relatively low. Both access to care and diagnostic accuracy fuel interest in developing smartphone apps equipped with algorithms for image analyses of suspicious lesions to detect skin cancer. Based on a recent review, seven smartphone apps claim to perform image analysis for skin cancer detection, but as of October 2018, only three seemed to be active. These apps have been criticized in the past due to their lack of diagnostic accuracy. Here, we review the development of the SkinVision smartphone app, which has more than 900,000 users worldwide. The latest version of the SkinVision app (October 2018) has a 95% sensitivity (78% specificity) for detection of skin cancer. The current accuracy of the algorithm may warrant the use of this app as an aid by lay users or general practitioners. Nonetheless, for mobile health apps to become broadly accepted, further research is needed on their health impact on the health system and the user population. Ultimately, mobile health apps could become a powerful tool to reduce health care costs related to skin cancer management and minimize the morbidity of skin cancer in the population.

scholarly journals Diagnostic value of transcranial ultrasonography for selecting subjects with large vessel occlusion: a systematic review

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Daria Antipova ◽  
Leila Eadie ◽  
Ashish Stephen Macaden ◽  
Philip Wilson
Keyword(s):  
Systematic Review ◽  
Diagnostic Accuracy ◽  
Acute Stroke ◽  
Clinical Assessment ◽  
Assessment Tools ◽  
Large Vessel ◽  
Cochrane Library ◽  
Direct Transfer ◽  
Large Vessel Occlusion ◽  
Vessel Occlusion

Abstract Introduction A number of pre-hospital clinical assessment tools have been developed to triage subjects with acute stroke due to large vessel occlusion (LVO) to a specialised endovascular centre, but their false negative rates remain high leading to inappropriate and costly emergency transfers. Transcranial ultrasonography may represent a valuable pre-hospital tool for selecting patients with LVO who could benefit from rapid transfer to a dedicated centre. Methods Diagnostic accuracy of transcranial ultrasonography in acute stroke was subjected to systematic review. Medline, Embase, PubMed, Scopus, and The Cochrane Library were searched. Published articles reporting diagnostic accuracy of transcranial ultrasonography in comparison to a reference imaging method were selected. Studies reporting estimates of diagnostic accuracy were included in the meta-analysis. Results Twenty-seven published articles were selected for the systematic review. Transcranial Doppler findings, such as absent or diminished blood flow signal in a major cerebral artery and asymmetry index ≥ 21% were shown to be suggestive of LVO. It demonstrated sensitivity ranging from 68 to 100% and specificity of 78–99% for detecting acute steno-occlusive lesions. Area under the receiver operating characteristics curve was 0.91. Transcranial ultrasonography can also detect haemorrhagic foci, however, its application is largely restricted by lesion location. Conclusions Transcranial ultrasonography might potentially be used for the selection of subjects with acute LVO, to help streamline patient care and allow direct transfer to specialised endovascular centres. It can also assist in detecting haemorrhagic lesions in some cases, however, its applicability here is largely restricted. Additional research should optimize the scanning technique. Further work is required to demonstrate whether this diagnostic approach, possibly combined with clinical assessment, could be used at the pre-hospital stage to justify direct transfer to a regional thrombectomy centre in suitable cases.

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