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Prognostic nomograms to predict overall survival and cause specific death in vulvar squamous cell carcinoma

Abstract

Objective The incidence of vulvar squamous cell carcinoma has been rising in recent decades. The prognosis of patients with vulvar squamous cell carcinoma was explored, and nomograms were constructed to predict survival rates.

Methods Vulvar squamous cell carcinoma patient data were downloaded from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into a training dataset and testing dataset. Univariable and multivariable Cox regression were used to identify risk factors affecting vulvar squamous cell carcinoma overall survival in the training dataset. Cumulative incidence function and Fine–Gray regression were used to analyze cancer specific death in the training dataset. Overall survival and cancer specific death nomograms were constructed and validated in the testing and whole datasets. Receiver operating characteristic and calibration were used to verify the predictive value and clinical applicability of the models.

Results Age ≥60 years, grade 3, American Joint Committee on Cancer stages III and IV, TNM (tumor, nodes, metastasis) stages T2, T3, N1, and M1 had a negative effect on overall survival in vulvar cancer patients. Surgery (hazard ratio (HR)=0.416, 95% confidence interval (CI) 0.349 to 0.496, p<0.001) and chemotherapy (HR=0.637, 95% CI 0.544 to 0.746, p<0.001) may improve overall survival. Age, tumor grade, American Joint Committee on Cancer stage, T stage, N stage, M stage, surgery, and chemotherapy significantly affected vulvar cancer specific death. For area under the receiver operating characteristic curve, the predictive ability of the nomograms for overall survival and cancer specific death for 1 year (area under the curve (AUC)=0.862), 3 years (AUC=0.832), and 5 years (AUC=0.808) were all >0.800.

Conclusion The nomograms established in our study had an excellent predictive ability for overall survival and cancer specific death in vulvar cancer patients.

  • Gynecology
  • Vulvar Diseases
  • Vulvar Neoplasms

Data availability statement

Data are available in a public, open access repository. https://seer.cancer.gov/

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