Two-step-7-Pink Rule: A Practical Tool for the Dermoscopic Evaluation of Fully Amelanotic Skin Lesions
Keywords:
melanoma, fully-amelanotic skin tumours, pink lesions, dermoscopyAbstract
Introduction: The diagnosis of fully amelanotic skin tumors is difficult on clinical and dermoscopic examination.
Objective: We sought to identify an accurate and user-friendly dermoscopic algorithm to differentiate between benign and malignant pink lesions.
Methods: The database of 1 referral center was retrospectively reviewed for images of non-inflammatory fully amelanotic skin lesions. Two dermatologists jointly assessed a validation set of images for dermoscopic criteria and constructed a diagnostic algorithm, the 2-step 7-pink rule (2S-7PR). Two external clinicians, with different skills in dermoscopy and blinded to the final diagnosis, separately evaluated images from the validation test sets using the prevalent criterion method and the new 2S-7PR algorithm.
Results: A total of 763 lesions from 652 patients were included in the validation set database, of which 68.3% were malignant and 31.7% were benign. Three suspicious dermoscopic criteria were included in the first step of the 2S-7PR: polymorphous or sharply focused vessels, scales or crusts, and erosions or ulcerations; and 4 non-suspicious criteria were included in the second: white collarette, white scar-like area, vascular lacunae, and necklace pinpoint vessels. High levels of specificity and sensitivity were calculated in the validation and test phases for both the expert and non-expert evaluators, the former achieving higher levels of both sensitivity and specificity by employing the 2S-7PR compared to the prevalent method, and the latter only improved specificity.
Conclusions: The present study showed that an algorithm focused on a few reproducible and easily recognizable criteria could improve diagnostic accuracy in the management of amelanotic lesions.
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Copyright (c) 2025 Riccardo Pampena, Stefano Migliorati, Giovanni Paolino, Michela Lai, Nicola Lippolis, Stefania Guida, Stefania Borsari, Sebastiano Pellerone, Sofia Maria Di Ciaccio, Elvira Moscarella, Giovanni Pellacani, Giuseppe Argenziano, Caterina Longo

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