Western surgical association articleSelective Approach for Patients with Advanced Malignancy and Gastrointestinal Obstruction

BackgroundThe purpose of this study was to determine the frequency of tumor-related gastrointestinal obstruction and identify variables associated with functional outcomes and survival in patients with advanced malignancy and gastrointestinal obstruction.Study designWe reviewed the medical records of 490 patients with advanced cancer, who underwent surgical consultation for gastrointestinal obstruction between January 2000 and May 2014. We used chi-square and logistic regression analyses to identify variables associated with survival and eating at discharge.ResultsObstructions were tumor-related in 334 (68%) patients, adhesion-related in 96 (20%), and of unclear etiology in 60 (12%). The obstruction site was the gastric outlet in 78 (16%), small bowel in 312 (64%), and large bowel in 100 (20%). Treatment was classified as medical (49% of patients), surgical (32%), and procedural (interventional radiology or endoscopy) (17%). Sixty-eight percent of patients were eating at the time of discharge, and 42% died within 90 days of surgical consultation. Median overall survival rates for patients managed with procedural, medical, and surgical treatment were 69, 135, and 314 days, respectively (p < 0.001). Intact primary/local recurrence, carcinomatosis, and albumin level <3.5 g/dL were negatively associated with eating at discharge. Compared with medical management, surgery was not associated with the ability to eat. Variables associated with death within 90 days of consultation included an intact primary/local recurrence, carcinomatosis, abdominal visceral metastasis, and procedural treatment.ConclusionsPatients managed with surgery demonstrated improved survival on unadjusted analysis. However, on multivariate analysis that included the imaging extent of disease, surgery was not associated with outcome, which highlights the importance of patient selection and the need for additional research to identify variables critical for treatment selection.