The use of teledermatology for the diagnosis of skin cancer in adults - Chuchu, Naomi; Dinnes, Jacqueline; Takwoingi, Yemisi; Matin, Rubeta N.; Bayliss, Susan E.; Davenport, Clare; Moreau, Jacqueline F.; Bassett, Oliver; Godfrey, Kathie; O'Sullivan, Colette; Walter, Fiona M.; Motley, Richard; et al. (Wiley, 2018)
Background: Early accurate detection of all skin cancer types is essential to guide appropriate management and to improve morbidity and survival. Melanoma and squamous cell carcinoma (SCC) are high risk skin cancers which have the potential to metastasise and ultimately lead to death, whereas basal cell carcinoma (BCC) is usually localised with potential to infiltrate and damage surrounding tissue. Anxiety around missing early curable cases needs to be balanced against inappropriate referral and unnecessary excision of benign lesions. Teledermatology provides a way for generalist clinicians to access the opinion of a specialist dermatologist for skin lesions that they consider to be suspicious without referring the patients concerned through the normal referral pathway. Teledermatology consultations can be ‘store-and-forward’ with electronic digital images of a lesion sent to a dermatologist for review at a later time, or can be live and interactive consultations using video conferencing to connect the patient, referrer and dermatologist in real time. Objectives: To determine the diagnostic accuracy of teledermatology for the detection of any skin cancer (melanoma, BCC or cSCC) in adults, and to compare its accuracy with that of in-person diagnosis. Search methods: We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; MEDLINE; EMBASE; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles. Selection criteria: Studies evaluating skin cancer diagnosis for teledermatology alone, or in comparison with face-to-face diagnosis by a specialist clinician, compared with a reference standard of histological confirmation or clinical follow-up and expert opinion. Studies evaluating the referral accuracy of teledermatology compared with a reference standard of face-to-face diagnosis by a specialist clinician were also included. Data collection and analysis: Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition of any skin cancer was missing. Data permitting, we estimated summary sensitivities and specificities using the bivariate hierarchical model. Due to scarcity of data, no covariate investigations were undertaken for this review. For illustrative purposes, estimates of sensitivity and specificity were plotted on coupled forest plots for diagnostic threshold and target condition under consideration. Main results: Twenty-two studies were included reporting diagnostic accuracy data for 4057 lesions and 879 malignant cases (16 studies) and referral accuracy data for reported data for 1449 lesions and 270 ‘positive’ cases as determined by the reference standard face-to-face decision (six studies). Methodological quality was variable with poor reporting hindering assessment. The overall risk of bias was rated as high or unclear for participant selection, reference standard and participant flow and timing in at least half of all studies; the majority were considered at low risk of bias for the index test. The applicability of study findings were of high or unclear concern for the majority of studies in all domains assessed due to the recruitment of study participants from secondary care settings or specialist clinics rather than from the primary or community-based settings in which teledermatology is more likely to be used and due to the acquisition of lesion images by dermatologists or in specialist imaging units rather than by primary care clinicians. Seven studies provided data for the primary target condition of any skin cancer (1588 lesions and 638 malignancies). For the correct diagnosis of lesions as malignant using photographic images, summary sensitivity was 94.9% (95% CI 90.1 to 97.4%) and summary specificity 84.3% (95% CI 48.5 to 96.8%) (from four studies). Individual study estimates using dermoscopic images or a combination of photographic and dermoscopic images generally suggested similarly high sensitivities with highly variable specificities. Limited comparative data suggested similar diagnostic accuracy between teledermatology assessment and in-person diagnosis by a dermatologist; however, data were too scarce to draw firm conclusions. For the detection of invasive melanoma or atypical intraepidermal melanocytic variants both sensitivities and specificities were more variable. Sensitivities ranged from 59% (95% CI 42% to 74%) to 100% (95% CI 54% to 100%) and specificities from 30% (95% CI 22% to 40%) to 100% (95% CI 93% to 100%), with reported diagnostic thresholds including the correct diagnosis of melanoma, classification of lesions as ‘atypical’ or ‘typical as well as the decision to refer or to excise a lesion. Referral accuracy data comparing teledermatology against a face-to-face reference standard suggested good agreement for lesions considered to require some positive action by face to face assessment (sensitivities of over 90%). For lesions considered of less concern when assessed face-to-face (e.g. for those not recommended for excision or referral), agreement was more variable with teledermatology specificities ranging from 57% (95% CI 39 to 73%) to 100% (95% CI 86% to 100%), suggesting that remote assessment is more likely recommend excision, referral or follow-up compared to in-person decisions. Authors' conclusions: Studies were generally small and heterogeneous and methodological quality was difficult to judge due to poor reporting. Bearing in mind concerns regarding the applicability of study participants and of lesion image acquisition in specialist settings, our results suggest that teledermatology can correctly identify the majority of malignant lesions. Using a more widely defined threshold to identify ‘possibly’ malignant cases or lesions that should be considered for excision is likely to appropriately triage those lesions requiring face-to-face assessment by a specialist. Despite the increasing use of teledermatology on an international level, the evidence base to support its ability to accurately diagnose lesions and to triage lesions from primary to secondary care is lacking and further prospective and pragmatic evaluation is needed.