Prognostic factors for metastasis in cutaneous melanoma

Cherobin, Ana Carolina Figueiredo Pereira; Wainstein, Alberto Julius Alves; Colosimo, Enrico A.; Goulart, Eugênio Marcos Andrade; Bittencourt, Flávia Vasques

doi:10.1590/abd1806-4841.20184779

Cited by 43 publications

(36 citation statements)

References 47 publications

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“…The American Joint Committee on Cancer (AJCC) staging system has been widely used to determine treatment strategies for lip squamous cell carcinoma (LSCC) patients. This system is commonly used alone to predict the prognosis for an ensemble population of patients, and it has some crucial limitations since the prognosis of LSCC patients is influenced by many other factors such as race, marital status, and age . Ignoring these significant prognostic factors may decrease the accuracy of survival predictions, including since the survival outcomes of patients at the same AJCC stage can be vary widely.…”

Section: Introductionmentioning

confidence: 99%

“…This system is commonly used alone to predict the prognosis for an ensemble population of patients, and it has some crucial limitations since the prognosis of LSCC patients is influenced by many other factors [4][5][6] such as race, marital status, and age. 7 Ignoring these significant prognostic factors may decrease the accuracy of survival predictions, including since the survival outcomes of patients at the same AJCC stage can be vary widely. The clinical uniqueness of LSCC means that new prognostic tools are needed to increase the accuracy of survival predictions in LSCC patients.…”

Section: Introductionmentioning

confidence: 99%

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Nomograms for predicting long‐term overall survival and cancer‐specific survival in lip squamous cell carcinoma: A population‐based study

Pan

Yang

et al. 2019

Cancer Medicine

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Background The goal of this study was to establish and validate two nomograms for predicting the long‐term overall survival (OS) and cancer‐specific survival (CSS) in lip squamous cell carcinoma (LSCC). Methods This study selected 4175 patients who were diagnosed with LSCC between 2004 and 2015 in the SEER (Surveillance, Epidemiology, and End Results) database. The patients were allocated randomly to a training cohort and validation cohort. Variables were selected using a backward stepwise method in a Cox regression model. Based on the predictive model with the identified prognostic factors, nomograms were established to predict the 3‐, 5‐, and 8‐year survival OS and CSS rates of LSCC patients. The accuracy of the nomograms was evaluated based on the consistency index (C‐index), while their prediction accuracy was evaluated using calibration plots. Decision curve analyses (DCAs) were used to evaluate the performance of our survival model. Results The multivariate analyses demonstrated that age at diagnosis, marital status, sex, race, American Joint Committee on Cancer stage, surgery status, and radiotherapy status were risk factors for both OS and CSS. The C‐index, area under the time‐dependent receiver operating characteristic curve, and calibration plots demonstrated the good performance of the nomograms. DCAs of both nomograms further showed that they exhibited good 3‐, 5‐, and 8‐year net benefits. Conclusions We have developed and validated LSCC prognosis nomograms for OS and CSS for the first time. These nomograms can be valuable tools for clinical practice when clinicians are helping patients to understand their survival risk for the next 3, 5, and 8 years.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nomograms for predicting long‐term overall survival and cancer‐specific survival in lip squamous cell carcinoma: A population‐based study

Pan

Yang

et al. 2019

Cancer Medicine

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“…In order to see whether the models developed earlier in this study perform better than the previously established prognostic markers, patients were stratified using clinical factors such as AJCC pathological staging, age, TNM staging, Breslow thickness, Gender and Ulceration status. These have been reported to be associated with risk in CM patients in the past [ 53 , 54 , 55 , 56 ]. Table 5 shows these results.…”

Section: Resultsmentioning

confidence: 99%

Risk prediction in cutaneous melanoma patients from their clinico-pathological features: superiority of clinical data over gene expression data

Arora

Kaur

Lathwal

et al. 2020

Heliyon

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Risk assessment in cutaneous melanoma (CM) patients is one of the major challenges in the effective treatment of CM patients. Traditionally, clinico-pathological features such as Breslow thickness, American Joint Committee on Cancer (AJCC) tumor staging, etc. are utilized for this purpose. However, due to advancements in technology, most of the upcoming risk prediction methods are gene-expression profile (GEP) based. In this study, we have tried to develop new GEP and clinico-pathological features-based biomarkers and assessed their prognostic strength in contrast to existing prognostic methods. We developed risk prediction models using the expression of the genes associated with different cancer-related pathways and got a maximum hazard ratio (HR) of 2.52 with p-value~10 À8 for the apoptotic pathway. Another model, based on combination of apoptotic and notch pathway genes boosted the HR to 2.57. Next, we developed models based on individual clinical features and got a maximum HR of 2.45 with p-value~10 À6 for Breslow thickness. We also developed models using the best features of clinical as well as gene-expression data and obtained a maximum HR of 3.19 with p-value~10 À9. Finally, we developed a new ensemble method using clinical variables only and got a maximum HR of 6.40 with p-valuẽ 10 À15. Based on this method, a web-based service and an android application named 'CMcrpred' is available at (https://webs.iiitd.edu.in/raghava/cmcrpred/) and Google Play Store respectively to facilitate scientific community. This study reveals that our new ensemble method based on only clinico-pathological features overperforms methods based on GEP based profiles as well as currently used AJCC staging. It also highlights the need to explore the full potential of clinical variables for prognostication of cancer patients.

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“…The survival time was defined as the interval between the date of diagnosis of the primary cutaneous melanoma and the registered date of death or the date of the last consultation. We defined and classified these variables based on previous reports about malignant melanoma 91011121314…”

Section: Methodsmentioning

confidence: 99%

Clinicopathologic Features and Prognostic Factors of Primary Cutaneous Melanoma: a Multicenter Study in Korea

et al. 2019

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Background Malignant melanoma is a cutaneous malignancy with a high mortality rate and high potential for metastases. Detailed information on the clinicopathologic characteristics and prognostic factors of cutaneous melanoma is currently limited in Korea. This study aimed to identify the epidemiological and clinicopathologic characteristics of primary cutaneous melanoma in Korean patients, and to assess which prognostic variables could influence both the development of metastases in primary cutaneous melanoma and overall survival (OS). Methods A total of 261 patients diagnosed with primary cutaneous melanoma in seven medical centers between 1997 and 2017 were retrospectively investigated with regard to clinical presentation, localization of the tumor, histopathologic subtype, and survival time. Results The nodular histologic subtype, ulceration, and Breslow thickness were significantly associated with the development of metastasis; and overweight and obesity (body mass index > 23) were significantly associated with increased Breslow thickness. The location of the metastases appeared to influence OS: brain metastases were associated with the highest risk of death, followed by gastrointestinal, lung, and extra-regional lymph node metastases. Conclusion In this study, tumor thickness, nodular histologic subtype, and ulceration predicted metastatic spread of primary cutaneous melanoma. In addition, OS was associated with the location of metastases. Obesity was related to the prognosis of primary cutaneous melanoma. Clinicians should bear these findings in mind when forming a diagnosis because of the risk of a poor prognosis.

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Prognostic factors for metastasis in cutaneous melanoma

Cited by 43 publications

References 47 publications

Nomograms for predicting long‐term overall survival and cancer‐specific survival in lip squamous cell carcinoma: A population‐based study

Nomograms for predicting long‐term overall survival and cancer‐specific survival in lip squamous cell carcinoma: A population‐based study

Risk prediction in cutaneous melanoma patients from their clinico-pathological features: superiority of clinical data over gene expression data

Clinicopathologic Features and Prognostic Factors of Primary Cutaneous Melanoma: a Multicenter Study in Korea

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