TY - JOUR
T1 - A new dermoscopic algorithm for the differential diagnosis of facial lentigo maligna and pigmented actinic keratosis
AU - Micantonio, Tamara
AU - Neri, Luca
AU - Longo, Caterina
AU - Grassi, Simone
AU - Di Stefani, Alessandro
AU - Antonini, Ambra
AU - Coco, Valeria
AU - Fargnoli, Maria Concetta
AU - Argenziano, Giuseppe
AU - Peris, Ketty
PY - 2018
Y1 - 2018
N2 - The clinical and dermoscopic diagnosis of facial lentigo maligna (LM) and pigmented actinic keratosis (PAK) remains challenging, particularly at the early disease stages. To identify dermoscopic criteria that might be useful to differentiate LM from PAK, and to elaborate and validate an automated diagnostic algorithm for facial LM/PAK. We performed a retrospective multicentre study to evaluate dermoscopic images of histologically-proven LM and PAK, and assess previously described dermoscopic criteria. In the first part of the study, 61 cases of LM and 74 PAK were examined and a parsimonious algorithm was elaborated using stepwise discriminant analysis. The following eight dermoscopic criteria achieved the greatest discriminative power: (1) light brown colour; (2) a structureless zone, varying in colour from brown to brown/tan, to black; (3) in-focus, discontinuous brown lines; (4) incomplete brown or grey circles; (5) a structureless brown or black zone, obscuring the hair follicles; (6) a brown (tan), eccentric, structureless zone; (7) a blue structureless zone; and (8) scales. The newly developed algorithm was subsequently validated using an additional series of 110 LM and 75 PAK cases. Diagnostic accuracy was 86.5% (κ: 0.73, 95% CI: 0.63-0.83). For the diagnosis of LM vs PAK, sensitivity was 82.7% (95% CI: 75.7-89.8%), specificity was 92.0% (95% CI: 85.9-98.1%), positive predictive value was 93.8% (95% CI: 89.0-98.6%), and negative predictive value was 78.4% (95% CI: 68.4-86.5%). This algorithm may represent an additional tool for clinicians to distinguish between facial LM and PAK.
AB - The clinical and dermoscopic diagnosis of facial lentigo maligna (LM) and pigmented actinic keratosis (PAK) remains challenging, particularly at the early disease stages. To identify dermoscopic criteria that might be useful to differentiate LM from PAK, and to elaborate and validate an automated diagnostic algorithm for facial LM/PAK. We performed a retrospective multicentre study to evaluate dermoscopic images of histologically-proven LM and PAK, and assess previously described dermoscopic criteria. In the first part of the study, 61 cases of LM and 74 PAK were examined and a parsimonious algorithm was elaborated using stepwise discriminant analysis. The following eight dermoscopic criteria achieved the greatest discriminative power: (1) light brown colour; (2) a structureless zone, varying in colour from brown to brown/tan, to black; (3) in-focus, discontinuous brown lines; (4) incomplete brown or grey circles; (5) a structureless brown or black zone, obscuring the hair follicles; (6) a brown (tan), eccentric, structureless zone; (7) a blue structureless zone; and (8) scales. The newly developed algorithm was subsequently validated using an additional series of 110 LM and 75 PAK cases. Diagnostic accuracy was 86.5% (κ: 0.73, 95% CI: 0.63-0.83). For the diagnosis of LM vs PAK, sensitivity was 82.7% (95% CI: 75.7-89.8%), specificity was 92.0% (95% CI: 85.9-98.1%), positive predictive value was 93.8% (95% CI: 89.0-98.6%), and negative predictive value was 78.4% (95% CI: 68.4-86.5%). This algorithm may represent an additional tool for clinicians to distinguish between facial LM and PAK.
KW - dermoscopic algorithm
KW - dermoscopy
KW - lentigo maligna
KW - lentigo maligna melanoma
KW - pigmented actinic keratosis
KW - dermoscopic algorithm
KW - dermoscopy
KW - lentigo maligna
KW - lentigo maligna melanoma
KW - pigmented actinic keratosis
UR - http://hdl.handle.net/10807/119225
U2 - 10.1684/ejd.2018.3246
DO - 10.1684/ejd.2018.3246
M3 - Article
SN - 1167-1122
SP - N/A-N/A
JO - European Journal of Dermatology
JF - European Journal of Dermatology
ER -