Dermoscopy as a Tool for Identifying Potentially Metastatic Thin Melanoma: A Clinical-Dermoscopic and Histopathological Case-Control Study.
Vincenzo De GiorgiFlavia SilvestriGiovanni CecchiFederico VenturiBiancamaria ZuccaroGabriella PerilloFederica CossoVincenza MaioSara SimiPietro AntoniniSerena PillozziLorenzo AntonuzzoDaniela MassiLaura DoniPublished in: Cancers (2024)
Despite being early-stage tumors, thin cutaneous melanomas contribute significantly to mortality and have a rising incidence. A retrospective case-control study was performed to identify clinical-dermoscopic and histopathological variables linked to local and distant metastases in melanomas ≤0.8 mm. Data from 1 January 2000 to 22 June 2022 were analyzed from two Italian skin cancer referral centers. Sixteen patients with ≤0.8 mm melanomas developing metastases were studied compared to controls without metastases over 5 years. Statistical analysis involved Pearson's chi-squared test or Fisher's exact test. Of the 1396 cases, 1.1% progressed. The median diagnosis age was 49 (range 28-83), with 56.3% men and 43.7% women. The torso was the primary tumor site (43.7%). Clinically, lesions were pigmented (>10 mm diameter: 73.3%, ≥3 colors: 80%). Dermoscopically, the common features were white patches (73.3%), atypical vascular patterns (66.5%), blue-gray areas (60%) and absent pigment networks (60%). Histopathologically, all cases had adverse features like regression (87.4%), dermal mitoses (50%), a vertical growth phase (62.5%) and ulceration (12.5%). These findings were statistically significant compared to controls ( p < 0.05). In ≤0.8 mm melanomas, specific clinical-dermoscopic traits might indicate higher metastatic potential when paired with adverse histopathological features.
Keyphrases
- early stage
- skin cancer
- small cell lung cancer
- squamous cell carcinoma
- primary care
- machine learning
- type diabetes
- lymph node
- gene expression
- cardiovascular events
- coronary artery disease
- genome wide
- electronic health record
- adverse drug
- density functional theory
- big data
- rectal cancer
- locally advanced
- data analysis
- wound healing