ERBB2 and neoplasm: Compared with the traditional multivariable regression, LASSO regression was considered as a better method to select variables since it can minimize overfitting and reduce the complexity of the model by using a loss function or penalty term that is added to the objective function.30,31 Through the LASSO regression algorithm, only seven variables (i.e., tumor grade, T-stage, N-stage, LNR, ER, PR, and HER2 status) were identified as the independent factor associated with OS in our study.