Marcel Arakaki Asato , Francisco Alves Moares-Neto , Marcelo Padovani de Toledo Moraes , Juliana Polizel Ocanha-Xavier , Luiz Carlos Takita , Mariangela Esther Alencar Marques , José Cândido Caldeira Xavier-Júnior
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引用次数: 0
Abstract
Background
Acral melanoma is a subtype with worse outcomes. The Breslow micrometric measurement is the most critical parameter in planning treatment and predicting outcomes. However, for acral lentiginous melanoma, the value of the Breslow thickness is a matter of debate. Depth of Invasion (DOI) is a well-established measure for staging oral squamous cell carcinoma.
Objective
This study compared DOI and Breslow thickness for predicting acral melanoma outcomes.
Methods
We performed a retrospective cross-sectional study of 71 acral melanoma lesions subjected to sentinel lymph node biopsy at one Brazilian referral center.
Results
Cox model univariate analysis showed that both DOI and Breslow thickness predicted melanoma specific survival (HR 1.12; p = 0.0255 and HR 1.144; p = 0.0006, respectively), although Kaplan Meier curve was only significant for Breslow (χ2 = 5.792; p = 0.0161) and not for DOI (χ2 = 0.2556; p = 0.6132). Sentinel lymph node status and presence or absence of ulceration also predicted specific survival in patients with acral melanoma (χ2 = 6.3514; p = 0.0117 and χ2 = 4.2793; p = 0.0386, respectively). Multivariate analysis, however, demonstrated that Breslow depth was the only independent parameter for predicting acral melanoma specific survival (HR 1.144; p = 0.0006).
Conclusion
Even though Breslow thickness remains the main predictor for survival in acral melanoma, it is not a perfect parameter. The introduction of DOI in this context opens new perspectives for predicting acral melanoma outcomes.
期刊介绍:
A peer-reviewed journal devoted to the publication of articles dealing with traditional morphologic studies using standard diagnostic techniques and stressing clinicopathological correlations and scientific observation of relevance to the daily practice of pathology. Special features include pathologic-radiologic correlations and pathologic-cytologic correlations.