The first competing risk survival nomogram in patients with papillary renal cell carcinoma

Sci Rep. 2021 Jun 4;11(1):11835. doi: 10.1038/s41598-021-91217-z.

Abstract

There is still a lack of competing risk analysis of patients with papillary renal cell carcinoma (pRCC) following surgery. We performed the cumulative incidence function (CIF) to estimate the absolute risks of cancer-specific mortality (CSM) and other-cause mortality (OCM) of pRCC over time, and constructed a nomogram predicting the probability of 2-, 3- and 5-year CSM based on competing risk regression. A total of 5993 pRCC patients who underwent nephrectomy between 2010 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The 2-, 3-, 5-year CSM rates were 3.2%, 4.4% and 6.5%, respectively, and that of OCM were 3.2%, 5.0% and 9.3%, respectively. The estimates of 5-year cumulative mortality were most pronounced among patients aged > 75 years in OCM (17.0%). On multivariable analyses, age, tumor grade, T stage, N stage, and with or without bone, liver and lung metastases were identified as independent predictors of CSM following surgery and were integrated to generate the nomogram. The nomogram achieved a satisfactory discrimination with the AUCt of 0.730 at 5-year, and the calibration curves presented impressive agreements. Taken together, age-related OCM is a significant portion of all-cause mortality in elderly patients and our nomogram can be used for decision-making and patient counselling.

MeSH terms

  • Aged
  • Area Under Curve
  • Calibration
  • Carcinoma, Renal Cell / epidemiology
  • Carcinoma, Renal Cell / mortality*
  • Decision Making
  • Female
  • Humans
  • Incidence
  • Kidney Neoplasms / epidemiology
  • Kidney Neoplasms / mortality*
  • Male
  • Medical Oncology / methods
  • Middle Aged
  • Multivariate Analysis
  • Neoplasm Metastasis
  • Neoplasm Staging
  • Nephrectomy / methods
  • Nomograms*
  • Probability
  • ROC Curve
  • Retrospective Studies
  • Risk
  • Risk Factors
  • SEER Program
  • Software
  • Survival Analysis*
  • United States
  • Urology / methods