| Literature DB >> 25048515 |
Alessandro Cucchetti1, Benjamin Djulbegovic, Athanasios Tsalatsanis, Alessandro Vitale, Iztok Hozo, Fabio Piscaglia, Matteo Cescon, Giorgio Ercolani, Francesco Tuci, Umberto Cillo, Antonio Daniele Pinna.
Abstract
UNLABELLED: Transcatheter arterial chemoembolization (TACE) is the first-line therapy recommended for patients with intermediate hepatocellular carcinoma (HCC). However, in clinical practice, these patients are often referred to surgical teams to be evaluated for hepatectomy. After making a treatment decision (e.g., TACE or surgery), physicians may discover that the alternative treatment would have been preferable, which may bring a sense of regret. Under this premise, it is postulated that the optimal decision will be the one associated with the least amount of regret. Regret-based decision curve analysis (Regret-DCA) was performed on a Cox's regression model developed on 247 patients with cirrhosis resected for intermediate HCC. Physician preferences on surgery versus TACE were elicited in terms of regret; threshold probabilities (Pt) were calculated to identify the probability of survival for which physicians are uncertain of whether or not to perform a surgery. A survey among surgeons and hepatologists regarding three hypothetical clinical cases of intermediate HCC was performed to assess treatment preference domains. The 3- and 5-year overall survival rates after hepatectomy were 48.7% and 33.8%, respectively. Child-Pugh score, tumor number, and esophageal varices were independent predictors of survival (P<0.05). Regret-DCA showed that for physicians with Pt values of 3-year survival between 35% and 70%, the optimal strategy is to rely on the prediction model; for physicians with Pt<35%, surgery should be offered to all patients; and for Pt values>70%, the least regretful strategy is to perform TACE on all patients. The survey showed a significant separation among physicians' preferences, indicating that surgeons and hepatologists can uniformly act according to the regret threshold model.Entities:
Mesh:
Year: 2015 PMID: 25048515 DOI: 10.1002/hep.27321
Source DB: PubMed Journal: Hepatology ISSN: 0270-9139 Impact factor: 17.425