Risk factors for peritoneal carcinomatosis in gastric cancer patients, and outcomes following resection and hyperthermic intraperitoneal chemotherapy (HIPEC)

Autor: Sima Blank, Kunal Parikh, Spiros P. Hiotis, Oliver S. Chow, Daniel M. Labow, Ghalib Jibara, Ki Won Kim
Rok vydání: 2012
Předmět:
Zdroj: Journal of Clinical Oncology. 30:e14656-e14656
ISSN: 1527-7755
0732-183X
Popis: e14656 Background: Gastric cancer (GC) contributes significantly to the burden of cancer death in the United States. Unfavorable prognosis in patients with gastric cancer and peritoneal carcinomatosis (GCPC) is well-documented. In this study, a model predictive of GCPC is proposed, and outcomes in patients with GCPC treated with surgery and hyperthermic intraperitoneal chemotherapy (HIPEC) are assessed. Methods: A single-institution analysis of 112 patients treated for GC between the years 2000 and 2011 was performed. Demographic and clinical-pathologic criteria were entered into univariate and multivariate analyses, to identify criteria independently predictive of GCPC. Overall survival in each cohort was determined via Kaplan-Meier analysis. Results: GCPC developed in 28/112 (25%) of GC patients. Several variables were associated with GCPC by univariate analysis (age, p = 0.018; tumor stage, p = 0.004; tumor location, p = 0.046), but only age (≤60) and tumor stage (T3/T4) were independently predictive of GCPC by multivariate analysis (HR = 3.949, p = 0.024; HR = 3.942, p = 0.049, respectively). Intermediate-term survival was not significantly impacted in nine GCPC patients treated with HIPEC (65% 1-year, 39% 3-year without HIPEC; vs. 73% 1-year, 39% 3-year with HIPEC, p = NS). Conclusions: A model to identify gastric cancer patients at highest risk for GCPC is proposed. Although intermediate term survival in a small number of GCPC patients (9) treated with HIPEC is not significantly improved, emerging experience with increased follow-up with HIPEC in larger cohorts is needed. Earlier application of HIPEC targeted at patients at highest risk may be feasible in utilizing a model predictive of GCPC.
Databáze: OpenAIRE