Nomograms for predicting the prognosis of stage IV XXXX after curative resection: A multicenter retrospective study.

@entity1 @entity5 @entity787 @entity14 @entity3 @entity1349
PURPOSE: Although stage IV @entity14 ( @entity14 ) encompasses a wide variety of clinical conditions with diverse prognoses, no statistical model for predicting the postoperative prognosis of stage IV @entity14 has been established. Thus, we here aimed to construct a predictive model for disease-free survival (DFS) and @entity1349 ( @entity1349 ) after curative surgery for stage IV @entity14 using nomograms. METHODS: The study included 1133 stage IV @entity14 @entity1 who underwent curative surgical resection in 19 institutions. @entity1 were divided into derivation (n  =  586) and validation (n  =  547) groups. Nomograms to predict the 1- and 3-year DFS rates and the 3- and 5-year @entity1349 rates were constructed using the derivation set. Calibration plots were constructed, and concordance indices (c-indices) were calculated. The predictive utility of the nomogram was validated in the validation set. RESULTS: The postoperative @entity787 ( @entity787 ) level, depth of @entity5 invasion (T factor), lymph node @entity3 (N factor), and number of metastatic organs were adopted as variables for the DFS-predicting nomogram, whereas the postoperative @entity787 level, T factor, N factor, and peritoneal dissemination were adopted for the nomogram to predict @entity1349 . The nomograms showed moderate calibration, with c-indices of 0.629 and 0.640 in the derivation set and 0.604 and 0.637 in the validation set for DFS and @entity1349 , respectively. CONCLUSIONS: The nomograms developed were capable of estimating the probability of DFS and @entity1349 on the basis of only 4 variables, and may represent useful tools for postoperative surveillance of stage IV @entity14 @entity1 in routine practice.
