Competing-risks analysis for evaluating the prognosis of patients with microinvasive cutaneous squamous cell carcinoma based on the SEER database.

BACKGROUND: Utilizing the traditional Cox regression model to identify the factors affecting the risk of mortality due to microinvasive cutaneous squamous cell carcinoma (micSCC) may produce skewed results. Since cause-specific mortality can guide clinical decision-making, this study employed the Fine-Gray model based on the Surveillance, Epidemiology, and End Results (SEER) database to identify significant predictive variables for the risk of micSCC-related mortality. METHODS: This study used the information of patients with micSCC who were listed in the SEER database during 2000-2015. Cox regression and Fine-Gray models were utilized for the multivariable analysis, and Gray's test and the cumulative incidence function were used for the univariable analyses. RESULTS: There were 100 patients who died from other reasons and 38 who died from micSCC among the 1259 qualified patients with micSCC. Most were female, white, married, had localized metastasis, etc. According to the univariable Gray's test (P < 0.05), the cumulative incidence rate for events of interest was strongly associated with age, sex, marital status, American Joint Committee on Cancer staging, radiation status, summary stage, chemotherapy status, surgery status, and tumor size. Multivariable Cox regression analysis and multivariable competing-risks analysis indicated that age, tumor size, and income were independent risk variables for the prognosis of patients with micSCC. In both age and tumor size variables, the competing-risks model showed a slight decrease in the hazard ratio and a slight narrowing of the 95% confidence interval compared with the Cox regression model. However, this pattern is not evident in the income variable. CONCLUSIONS: This study established a Fine-Gray model for identifying the independent risk factors that influence the risk of mortality among patients with micSCC. This study uncovers that, in the context of competing risks, age, tumor size, and income serve as independent risk factors influencing the risk of mortality due to micSCC among patients. Our findings have the potential to provide more accurate risk assessments for patient outcomes and contribute to the development of individualized treatment plans.

Analysis and prediction of 5-year survival in patients with cutaneous melanoma: a model-based period analysis.

Background: The survival and prognosis of patients are significantly threatened by cutaneous melanoma (CM), which is a highly aggressive disease. It is therefore crucial to determine the most recent survival rate of CM. This study used population-based cancer registry data to examine the 5-year relative survival rate of CM in the US. Methods: Period analysis was used to assess the relative survival rate and trends of patients with CM in the Surveillance, Epidemiology, and End Results (SEER) database during 2004-2018. And based on the data stratified by age, gender, race and subtype in the SEER database, a generalized linear model was 12established to predict the 5-year relative survival rate of CM patients from 2019 to 2023. Results: The 5-year relative survival increased to various degrees for both total CM and CM subtypes during the observation period. The improvement was greatest for amelanotic melanoma, increasing from 69.0% to 81.5%. The 5-year overall relative survival rates of CM were 92.9%, 93.5%, and 95.6% for 2004-2008, 2009-2013, and 2014-2018, respectively. Females had a marginally higher survival rate than males for almost all subtypes, older people had lower survival rates than younger people, white patients had higher survival rates than nonwhite ones, and urban locations had higher rates of survival from CM than rural locations did. The survival rate of CM was significantly lower for distant metastasis. Conclusion: The survival rate of patients with CM gradually improved overall during 2004-2018. With the predicted survival rate of 96.7% for 2019-2023, this trend will still be present. Assessing the changes experienced by patients with CM over the previous 15 years can help in predicting the future course of CM. It also provides a scientific foundation that associated departments can use to develop efficient tumor prevention and control strategies.