Louis, Chrystal U.

Objectives This analysis investigated nomogram use to evaluate metastatic pancreatic cancer prognosis. Methods Thirty-four baseline factors were examined in the Metastatic Pancreatic Adenocarcinoma Clinical Trial (MPACT) (nab-paclitaxel plus gemcitabine vs gemcitabine) data set. Factors significantly (P < 0.1) associated with overall survival (OS) in a univariable model or with known clinical relevance were tested further. In a multivariable model, factors associated with OS (P < 0.1) were selected to generate the primary nomogram, which was internally validated using bootstrapping, a concordance index, and calibration plots. Results Using data from 861 patients, 6 factors were retained (multivariable analysis): neutrophil-lymphocyte ratio, albumin level, Karnofsky performance status, sum of longest diameter of target lesions, presence of liver metastases, and previous Whipple procedure. The nomogram distinguished low-, medium-, and high-risk groups (concordance index, 0.67; 95% confidence interval, 0.65–0.69; median OS, 11.7, 8.0, and 3.3 months, respectively). Conclusions This nomogram may guide estimates of the range of OS outcomes and contribute to patient stratification in future prospective metastatic pancreatic cancer trials; however, external validation is required to improve estimate reliability and applicability to a general patient population. Caution should be exercised in interpreting these results for treatment decisions: patient characteristics could differ from those included in the nomogram development.

4109 Background: Prognostic nomograms have been developed in various cancers, including ovarian, breast, and gastrointestinal; however, there is limited information on nomograms in MPC. The large, phase 3 MPACT study of nab-P + Gem vs Gem alone for the treatment of MPC provides a robust database for the development of a nomogram to predict OS using baseline patient variables. Methods: A multivariable Cox model was created from MPACT data using factors that were significantly predictive of OS in univariable analysis or considered clinically important (stepwise selection to remain in model). From the Cox model, a nomogram was derived that assigned points equal to the weighted sum of relative significance of each variable. The nomogram was internally validated using bootstrapping, a concordance index (c-index), and calibration plots. Results: Data from all 861 pts were used. Seven of the 34 considered variables were retained in the multivariable analysis (Table; all factors significant at the P < 0.01 level, except for analgesic use [ P = 0.07]). The resulting nomogram was able to distinguish low (n = 216), medium (n = 430), and high (n = 215) risk groups (c-index: 0.69; CI: 0.67-0.71) with median OS values of 12.9, 8.2, and 3.7 months, respectively. Calibration curves showed that the nomogram’s predicted probabilities were mostly consistent with observed probabilities for 6-, 9-, and 12-month OS. Conclusions: Treatment arm, Karnofsky performance status (KPS), neutrophil-to-lymphocyte ratio (NLR), albumin level, sum of longest tumor diameters (SLD), and presence of liver metastasis were the key predictors of OS. This nomogram, which will be presented in visual format in the final presentation, may help physicians and pts make informed treatment decisions. Clinical trial information: NCT00844649. [Table: see text]