External validation and comparison of four confocal microscopic scores for melanoma diagnosis on a retrospective series of highly suspicious melanocytic lesions

Abstract

Background In vivo reflectance confocal microscopy significantly improves melanoma diagnosis as compared to clinical/dermoscopic examination alone. Several confocal criteria have been described allowing to differentiate melanoma from nevi; by combining different criteria, three pure confocal scores (Pellacani 2005, Segura 2009 and Pellacani 2012) and one mixed dermoscopic/confocal score (Borsari 2018) were constructed. Objective Our aim was to externally validate and compare the performance of these confocal scores. Methods We retrospectively enrolled excised melanocytic lesions which underwent confocal examination in a 2‐year period. Lesions located on the face and acral sites were excluded. Both dermoscopic and confocal criteria considered in the four scores were evaluated by experts. Subsequently, specificity and sensitivity levels for each score were calculated, together with the positive and negative predictive values and likelihood ratios; also, receiver operating characteristic curves were constructed. Results A total of 389 patients with 422 lesions were retrospectively enrolled, of which 162 (38.4%) were melanomas and 260 (61.6%) were nevi (189 common and 71 Spitz/Reed nevi). The highest sensitivity levels were recorded for Segura 2009 with cut‐off ≥−1 (92.0%), while Pellacani 2005 with cut‐off ≥5 achieved the highest specificity (69.6%). The score by Borsari et al. showed the highest levels of positive and negative predictive values (59.8% and 91.5%) and likelihood ratios (2.4 and 0.1) as well as the highest area under the curve values (0.76; 95% CI 0.72–0.81; P < 0.001). Conclusions High levels of accuracy were found for each of the four considered scores. No differences were found among scores in confirming melanoma diagnosis when positive; however, the score by Borsari 2018 was the best in excluding melanoma diagnosis when negative.

In vivo confocal microscopy: The role of comparative approach in patients with multiple atypical nevi

“…Sensitivity and specificity levels of both scores were in line with their validation studies, which further confirms their utility in clinical practice. [2,18,19] In particular, unnecessary excision or short-FUPs of benign lesions further decreased as compared to previous approaches (twothird of benign lesions were scheduled for long-FUP), as well as the NNE (>50% reduction).…”

“…Sensitivity and specificity levels of both scores were in line with their validation studies, which further confirms their utility in clinical practice. [ 2,18,19 ]…”

“…The sequential application of dermoscopy and in vivo reflectance confocal microscopy (RCM) have proven to significantly increase melanoma diagnostic accuracy. [1][2][3][4] In patients with multiple atypical nevi, a classic morphologic approach (individual clinical/dermoscopy/RCM image evaluation only) may lead to an overestimation of atypical melanocytic lesions. [5,6] Comparative strategies, including the dermoscopic comparative approach where multiple atypical lesions of a given patient are analysed to identify the lesions with the most distinct atypical features, [6] and digital dermoscopic monitoring where clinical and dermoscopic images of the same lesion are analysed to detect early atypical changes during follow-up (FUP), [7,8] have shown to reduce unnecessary excision, without affecting sensitivity levels.…”

“…The sequential application of dermoscopy and in vivo reflectance confocal microscopy (RCM) have proven to significantly increase melanoma diagnostic accuracy. [ 1‐4 ]…”

Comparative Analysis of Diagnostic Techniques for Melanoma Detection: A Systematic Review of Diagnostic Test Accuracy Studies and Meta-Analysis

“…In Borsari et al (27) the diagnostic score combines dermoscopy and RCM, while the rest relied exclusively on confocal data. The performances of the four scoring systems have been compared retrospectively by Pampena et al (28), using different thresholds (i.e., number of features that a lesion presented to be considered melanoma using the algorithm) to assess if a lesion belonged to the melanoma class, suggesting that mixed criteria may be the best solution in reducing false positive rate. Another algorithm based on a two-step model was proposed in Guitera et al (16).…”