Methodological application of stepwise Cox regression model fitting and predicting Nomogram construction based on R software

ObjectiveTo establish the methods of fitting the stepwise Cox regression model and constructing Nomogram based on R software.

MethodsDataset on built-in 228 advanced lung cancer patients and dataset including 6 341 pancreatic cancer patients were downloaded from Surveillance, Epidemiology and End Results(SEER)program of USA were adopted to fit the stepwise Cox regression model with survival package of R, respectively. The rms package was used to construct Nomogram. The forecasting effects of Nomogram were validated by calibration curve.

ResultsThe multivariate Cox regression demonstrated that gender and score of ph.ecog were independent prognostic factors for overall survival of the advanced lung cancer patients, and showed that age, location of carcinoma in pancreas, tumor grade, TNM stage, size of carcinoma together with lymph node ratio(LNR)were independent survival predictors for pancreatic cancer patients, respectively. The Nomograms based on above prognostic factors could precisely calculate the 1-year and 2-year survival probability of patients with advanced lung cancer and pancreatic cancer, respectively. The calibration curve demonstrated the actual 1-year and 2-year survival probability was close to the predicting probability.ConclusionsR software can conveniently construct the Nomogram, visually predicting the survival probability of patients.