Cutaneous melanoma in patients from western Mexico: Clinical pathology characteristics and their relationship to prognosis

Perez-Aldrete, Berenice; Matildes-Mariscal, Jessica Berenice; Gómez-Padilla, Frania; Guevara‐Gutiérrez, Elizabeth; Barrientos-García, Juan Gabriel; Hernández-Peralta, Sarah Lizette; Tlacuilo‐Parra, Alberto

doi:10.1111/ajd.13054

Cited by 4 publications

(3 citation statements)

References 31 publications

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“…Finally, clinical features such as age, gender, and tumor location seem to influence the prognosis. In this respect, male gender and older age have been associated with a poorer prognosis by some authors [17][18][19], while others found no such correlation [20,21]. Considering the anatomic site of the primary cutaneous melanomas, some authors demonstrated a worse prognosis for palm/sole localization [19], and others for the head and neck [22,23].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Clinical and Histopathological Factors on Disease Progression and Survival in Thick Cutaneous Melanomas

Țăpoi,

Derewicz,

Gheorghișan-Gălățeanu

et al. 2023

Biomedicines

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Thick cutaneous melanomas (Breslow depth > 4 mm) are locally advanced tumors, generally associated with poor prognosis. Nevertheless, these tumors sometimes display unpredictable behavior. This study aims to analyze clinical and histopathological features that can influence the prognosis of thick melanomas. This is a retrospective study on 94 thick primary cutaneous melanomas diagnosed between 2012 and 2018 that were followed-up for at least five years to assess disease progression and survival. We evaluated the age, gender, tumor location, histological subtype, Breslow depth, Clark level, resection margins, mitotic index, the presence/absence of ulceration, necrosis, regression, microsatellites, neurotropism, lymphovascular invasion, and the pattern of tumor-infiltrating lymphocytes, and their association with disease progression and survival. By conducting univariate analysis, we found that progression-free survival (PFS) was significantly associated with female gender, the superficial spreading melanoma (SSM) subtype, mitotic index, necrosis, microsatellites, and perineural invasion. Overall survival (OS) was significantly associated with female gender, Breslow depth, SSM subtype, necrosis, microsatellites, and perineural invasion. Through multivariate Cox proportional hazards regression, we found that the only factors associated with PFS were Breslow depth, necrosis, microsatellites, and perineural invasion, while the factors associated with OS were Breslow depth, necrosis, microsatellites, and perineural invasion. Certain histopathological features such as Breslow depth, necrosis, microsatellites, and perineural invasion could explain differences in disease evolution. This is one of the first studies to demonstrate an association between necrosis and perineural invasion and outcomes in patients with thick melanomas. By identifying high-risk patients, personalized therapy can be provided for improved prognosis.

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Section: Introductionmentioning

confidence: 99%

The Impact of Clinical and Histopathological Factors on Disease Progression and Survival in Thick Cutaneous Melanomas

Țăpoi,

Derewicz,

Gheorghișan-Gălățeanu

et al. 2023

Biomedicines

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“…The incidence of melanoma is on the rise, and in Mexico, it ranks third in frequency among skin cancers (14.1%), following basal cell carcinoma and squamous cell carcinoma, according to estimates from the International Agency for Research on Cancer in 2012 [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Development, Application and Utility of a Machine Learning Approach for Melanoma and Non-Melanoma Lesion Classification Using Counting Box Fractal Dimension

Romero-Morelos,

Herrera-López,

González-Yebra

2024

Diagnostics

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The diagnosis and identification of melanoma are not always accurate, even for experienced dermatologists. Histopathology continues to be the gold standard, assessing specific parameters such as the Breslow index. However, it remains invasive and may lack effectiveness. Therefore, leveraging mathematical modeling and informatics has been a pursuit of diagnostic methods favoring early detection. Fractality, a mathematical parameter quantifying complexity and irregularity, has proven useful in melanoma diagnosis. Nonetheless, no studies have implemented this metric to feed artificial intelligence algorithms for the automatic classification of dermatological lesions, including melanoma. Hence, this study aimed to determine the combined utility of fractal dimension and unsupervised low-computational-requirements machine learning models in classifying melanoma and non-melanoma lesions. We analyzed 39,270 dermatological lesions obtained from the International Skin Imaging Collaboration. Box-counting fractal dimensions were calculated for these lesions. Fractal values were used to implement classification methods by unsupervised machine learning based on principal component analysis and iterated K-means (100 iterations). A clear separation was observed, using only fractal dimension values, between benign or malignant lesions (sensibility 72.4% and specificity 50.1%) and melanoma or non-melanoma lesions (sensibility 72.8% and specificity 50%) and subsequently, the classification quality based on the machine learning model was ≈80% for both benign and malignant or melanoma and non-melanoma lesions. However, the grouping of metastatic melanoma versus non-metastatic melanoma was less effective, probably due to the small sample size included in MM lesions. Nevertheless, we could suggest a decision algorithm based on fractal dimension for dermatological lesion discrimination. On the other hand, it was also determined that the fractal dimension is sufficient to generate unsupervised artificial intelligence models that allow for a more efficient classification of dermatological lesions.

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“…Some studies correlated older age and male gender with decreased survival [3][4][5], while others found no association [6,7]. The primary location of the melanoma also has debatable prognostic value, but it appears location on the lower limbs is associated with a more favorable outcome [8] in comparison to an acral location [9] or head and neck location [10].…”

Section: Introductionmentioning

confidence: 99%

Prognostic Value of the Width of Invasion in pT3 Cutaneous Melanomas

Țăpoi,

Gheorghișan-Gălățeanu,

Gosman

et al. 2023

IJTM

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Intermediate-thickness melanomas display highly variable outcomes influenced by both clinical and histopathological characteristics. This study investigates several clinicopathological prognostic factors for pT3 cutaneous melanomas, focusing on a novel parameter, the width of invasion. This is a retrospective study of 49 patients diagnosed with cutaneous melanoma between 2012 and 2018 who were followed up for at least five years. We evaluated the age, gender, tumor location, Breslow depth of invasion, width of invasion, mitotic index, the presence/absence of ulceration, regression, microsatellites, lymphovascular invasion, and perineural invasion for their association with disease progression and survival. Cox univariate analysis revealed that progression-free survival (PFS) was significantly associated with age, depth of invasion, width of invasion, lymphovascular invasion, microsatellites, and perineural invasion. Overall survival (OS) was significantly associated with age, depth of invasion, width of invasion, microsatellites, and perineural invasion. Through multivariate Cox proportional hazards regression, the only factor associated with both PFS and OS was the width of the invasion. This is one of the few studies to assess the width of invasion and we have demonstrated that this parameter could become an important prognostic factor for cutaneous melanomas.

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Cutaneous melanoma in patients from western Mexico: Clinical pathology characteristics and their relationship to prognosis

Cited by 4 publications

References 31 publications

The Impact of Clinical and Histopathological Factors on Disease Progression and Survival in Thick Cutaneous Melanomas

The Impact of Clinical and Histopathological Factors on Disease Progression and Survival in Thick Cutaneous Melanomas

Development, Application and Utility of a Machine Learning Approach for Melanoma and Non-Melanoma Lesion Classification Using Counting Box Fractal Dimension

Prognostic Value of the Width of Invasion in pT3 Cutaneous Melanomas

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