Predictive Scoring Model Effectively Differentiates Between Subungual Melanoma in Situ, Longitudinal Melanonychia

Using a predictive scoring model for the detection of characteristic dermoscopic features of subungual melanoma in situ (SMIS) may help to differentiate SMIS from benign longitudinal melanonychia (LM), according to the results of a cohort study conducted at a tertiary referral hospital in Seoul, South Korea, and published in JAMA Dermatology.

The investigators sought to examine the morphologic features of SMIS in order to develop a predictive scoring model for the diagnosis of SMIS in individuals with adult-onset LM that affected only a single digit. A total of 19 patients with biopsy-proven SMIS and 26 patients with benign LM were evaluated between September 1, 2013 and July 31, 2017.

Of the 45 patients with pigmented nails, 14 of 19 with SMIS and 18 of 26 with LM were women. Mean age was 52.0±14.4 in patients with SMIS and 48.1±13.2 in patients with LM. The following features of LM were all significantly associated with SMIS: asymmetry (odds ratio [OR] 34.00; 95% CI, 3.88-297.70; P =.001), border fading (OR 9.33; 95% CI, 2.37-36.70; P =.001), multicolor (OR 11.59; 95% CI, 2.21-60.89; P =.004), width of pigmentation ≥3 mm (OR 5.31; 95% CI, 1.10-28.07; P =.05), and presence of the Hutchinson sign (OR 18.18; 95% CI, 2.02-163.52; P =.01).

A predictive scoring model that incorporated these dermoscopic characteristics of SMIS was evaluated. The model, which ranged from 0 to 8, demonstrated a reliable diagnostic value in distinguishing SMIS from benign LM, with a sensitivity of 89% and a specificity of 62%.

A major limitation of the current study is the fact that it included only patients with adult-onset LM that affected a single digit, thus rendering the scoring model not valid for LM diagnosed in children or LM involving multiple digits.

The investigators concluded that the use of a predictive scoring model for identification of SMIS has the potential to improve the prognosis of the disorder and to promote informed decision-making with respect to the management of patients with LM.

Reference

Ohn J, Jo G, Cho Y, Sheu SL, Cho KH, Mun JH. Assessment of a predictive scoring model for dermoscopy of subungual melanoma in situ [published online June 20, 2018]. JAMA Dermatol. doi:10.1001/jamadermatol.2018.1372