Aim: The aim of this study was to identify factors that predict treatment outcome in patients with metastatic pancreatic cancer treated with gemcitabine, and then to use these factors to develop a practical prognostic index. Methods: A retrospective study was performed on 66 consecutive patients with histologically confirmed pancreatic adenocarcinoma who were treated with gemcitabine. Factors that predicted treatment outcome were identified by univariate and multivariate analyses using the Cox proportional hazards model. Results: Multivariate analysis identified Eastern Cooperative Oncology Group performance status, primary tumor location, and C-reactive protein as important independent predictive factors. Prognostic score was calculated using the following formula: score = (1 if performance status is 0 or 1; 2 if performance status is 2; and 5 if performance status is 3) + (1 if primary site is body or tail, 3 if primary site is head) + (1 if C-reactive protein is <1 mg/dL, 3 if C-reactive protein is 1-3 mg/dL, 6 if C-reactive protein is >3 mg/dL). Patients were accordingly divided into three groups: good (prognostic index = 3 or 4), fair (prognostic index = 5-7), and poor (prognostic index = 8). Median survival was 265, 155, and 65 days for each group, respectively (P < 0.0001). The internally validated c-index (receiver operating characteristics area under the curve) of this model was 0.711. Applied to another data set, the externally validated c-index was 0.692. Prognosis was favorable in the good prognosis group, patients in the fair prognosis group were likely to benefit from gemcitabine, and those in the poor prognosis group were unlikely to benefit. Conclusion: This index improved predictive ability in patients with metastatic pancreatic cancer treated with gemcitabine, which may be helpful in counseling patients and making first treatment decisions.
|Number of pages||6|
|Journal||Journal of Gastroenterology and Hepatology (Australia)|
|Issue number||8 PART1|
|Publication status||Published - 08-2008|
All Science Journal Classification (ASJC) codes