Combined pretherapeutic endoscopic and laparoscopic ultrasonography may predict survival of patients with upper gastrointestinal tract cancer

Michael Bau Mortensen, Claus Fristrup, Alan Ainsworth, Henning Overgaard Nielsen, Torsten Pless, Claus Hovendal
Surgical Endoscopy 2011, 25 (3): 804-12

BACKGROUND: The combination of endoscopic and laparoscopic ultrasonography (EUS-LUS) is accurate for resectability assessment of patients with upper gastrointestinal cancer (UGIC). But neither the ability of EUS/LUS to predict long-term prognosis nor the potential impact on patient survival using this selection strategy has been investigated. This prospective, single-center study evaluated whether pretherapeutic EUS-LUS stratification related to the prognosis in UGIC patients and whether patient selection by this strategy provided a prognostic outcome comparable with survival data from the literature.

METHODS: Each patient had a pretherapeutic tumor node metastasis (TNM) stage and a resectability assessment assigned based on EUS-LUS findings. Survival curves were constructed and compared for each of the EUS-LUS TNM stage and resectability groups at the end of the observation period. Finally, the R0 resection rate, median, and 5-year survival rates were compared with the literature.

RESULTS: This study enrolled 936 consecutive patients with esophageal (n = 256), gastric (n = 273), or pancreatic (n = 407) cancer. A statistically significant survival difference (p < 0.01) between the different TNM stages and resectability groups predicted by EUS-LUS was observed regardless of the cancer type. The poor prognosis for the patients with irresectable or disseminated UGIC was accurately predicted by EUS and LUS. The R0 resection rate as well as the median and 5-year survival rates were comparable with data from the literature.

CONCLUSION: The pretherapeutic EUS-LUS patient stratification related significantly to the final prognosis for UGIC patients. An EUS-LUS-based patient selection strategy seemed to provide a prognostic outcome similar to data from computed tomography (CT)-based populations.

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