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. 2010 Jan 20:7:281-91.
doi: 10.4137/cin.s3835.

Modeling prognostic factors in resectable pancreatic adenocarcinomas

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Modeling prognostic factors in resectable pancreatic adenocarcinomas

Taxiarchis Botsis et al. Cancer Inform. .

Abstract

Background: The accurate prognosis for patients with resectable pancreatic adenocarcinomas requires the incorporation of more factors than those included in AJCC TNM system.

Methods: We identified 218 patients diagnosed with stage I and II pancreatic adenocarcinoma at NewYork-Presbyterian Hospital/Columbia University Medical Center (1999 to 2009). Tumor and clinical characteristics were retrieved and associations with survival were assessed by univariate Cox analysis. A multivariable model was constructed and a prognostic score was calculated; the prognostic strength of our model was assessed with the concordance index.

Results: Our cohort had a median age of 67 years and consisted of 49% men; the median follow-up time was 14.3 months and the 5-year survival 3.6%. Age, tumor differentiation and size, alkaline phosphatase, albumin and CA 19-9 were the independent factors of the final multivariable model; patients were thus classified into low (n = 14, median survival = 53.7 months), intermediate (n = 124, median survival = 19.7 months) and high risk groups (n = 80, median survival = 12.3 months). The prognostic classification of our model remained significant after adjusting for adjuvant chemotherapy and the concordance index was 0.73 compared to 0.59 of the TNM system.

Conclusion: Our prognostic model was accurate in stratifying patients by risk and could be incorporated into clinical decisions.

Keywords: multivariable model; pancreatic adenocarcinomas; prognosis; survival.

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Figures

Figure 1.
Figure 1.
Disease outcome by A) our multivariable model with low risk patients showing an exceptional benefit towards survival compared to intermediate (log rank p = 0.005) and high risk patients (log rank p < 0.001); intermediate vs. high risk patients also have better outcome (log rank p < 0.001) and B) the AJCC TNM staging system (log rank p(IA vs. IB) = 0.125, p(IA vs. IIA) = 0.056, p(IA vs. IIB)= 0.010, p(IB vs. IIA) = 0.718, p(IB vs. IIB) = 0.315 and p(IIA vs. IIB) = 0.311).

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