Background: Predictive nomograms are becoming increasingly used to define and predict outcome. They can be developed at presentation or following treatment and include variables not conventionally used in standard staging systems.
Methods: We use a predictive nomogram based on prospectively collected data from 555 pancreatic resections for adenocarcinoma at a single institution. At last follow-up, 481 (87%) had died, defining a mature and comprehensive database. We used a 1-, 2-, and 3-year follow-up, as the number of patients alive beyond 3 years is sufficiently limited to provide insufficient events.
Results: Based on a Cox model, we then developed a nomogram that predicts the probability that a patient will survive pancreatic cancer for 1, 2, and 3 years from the time of the initial resection, assuming that there is not death from an alternate cause. Calibration between observed and corrected is good, and variables not conventionally associated with standard staging systems improved the predictivity of the model.
Conclusions: This nomogram can serve as a basis for investigating other potentially predictive variables that are proposed of prognostic importance for patients undergoing resection for adenocarcinoma of the pancreas.