PURPOSE: To analyze the use of proteomic profiles to discriminate healthy from patients with colorectal liver metastases (CLM) and to predict neoplastic recurrence after CLM resection. METHODS: From April 2005 to October 2008, 70 patients operated for first curative resection of CLM and 60 healthy controls underwent determination of preoperative serum proteomic profile. We performed a preliminary training with patients and controls and obtained a classification system based on these patients' proteomic profiles training. The system was then tested about the ability to predict the colon versus rectum origin, metachronous or synchronous appearance, risk of recurrence after CLM resection and whether a sample was from a control or a CLM patient. RESULTS: Sensitivity, specificity, positive and negative predictive values for detecting CLM patients were 75, 100, 100 and 54.6 %, respectively. Best CLM appearance time identification was 50 % and primary tumor origin identification was 62.5 %. Best classifications of neoplastic recurrence within the first year after CLM resection and during the follow-up period were 47.5 and 45 %, respectively. Larger training sets and prevalence-based training sets led to better classification of patients and characteristics. CONCLUSION: Proteomic profiles are a promising tool for discriminating CLM patients from healthy patients and for predicting neoplastic recurrence.
PURPOSE: To analyze the use of proteomic profiles to discriminate healthy from patients with colorectal liver metastases (CLM) and to predict neoplastic recurrence after CLM resection. METHODS: From April 2005 to October 2008, 70 patients operated for first curative resection of CLM and 60 healthy controls underwent determination of preoperative serum proteomic profile. We performed a preliminary training with patients and controls and obtained a classification system based on these patients' proteomic profiles training. The system was then tested about the ability to predict the colon versus rectum origin, metachronous or synchronous appearance, risk of recurrence after CLM resection and whether a sample was from a control or a CLM patient. RESULTS: Sensitivity, specificity, positive and negative predictive values for detecting CLM patients were 75, 100, 100 and 54.6 %, respectively. Best CLM appearance time identification was 50 % and primary tumor origin identification was 62.5 %. Best classifications of neoplastic recurrence within the first year after CLM resection and during the follow-up period were 47.5 and 45 %, respectively. Larger training sets and prevalence-based training sets led to better classification of patients and characteristics. CONCLUSION: Proteomic profiles are a promising tool for discriminating CLM patients from healthy patients and for predicting neoplastic recurrence.
Authors: S Iwatsuki; I Dvorchik; J R Madariaga; J W Marsh; F Dodson; A C Bonham; D A Geller; T J Gayowski; J J Fung; T E Starzl Journal: J Am Coll Surg Date: 1999-09 Impact factor: 6.113
Authors: Josep Martí; María Marta Modolo; Josep Fuster; Jaume Comas; Rebeca Cosa; Joana Ferrer; Victor Molina; Juan Romero; Constantino Fondevila; Ramón Charco; Juan Carlos García-Valdecasas Journal: World J Gastroenterol Date: 2009-06-07 Impact factor: 5.742