Angelo Andriulli1, Alessandra Nardi2, Vito Di Marco3, Antonio Massimo Ippolito4, Caius Gavrila2, Alessio Aghemo5, Daniele Di Paolo6, Giovanni Squadrito7, Eleonora Grassi5, Vincenza Calvaruso3, Maria Rosa Valvano1, Giuseppina Brancaccio8, Antonio Craxi3, Mario Angelico6. 1. Division of Gastroenterology, Casa Sollievo Sofferenza Hospital, IRCCS, Italy. 2. Department of Mathematics, Tor Vergata University, Roma, Italy. 3. Unit of Gastroenterology, Di.B.I.S., University of Palermo, Italy. 4. Division of Gastroenterology, Casa Sollievo Sofferenza Hospital, IRCCS, Italy. Electronic address: antonio.ippolito@me.com. 5. Division of Gastroenterology and Hepatology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy. 6. Hepatology and Liver Transplantation Unit, University of Tor Vergata, Roma, Italy. 7. Division of Clinical and Molecular Hepatology, University of Messina, Italy. 8. Clinic of Infectious Diseases, Second University of Napoli, Italy.
Abstract
BACKGROUND: Aim was to select naïve patients with genotype 1 chronic hepatitis C having a high probability of response to Peg-interferon+ribavirin therapy. METHODS: In 1073 patients (derivation cohort), predictors of rapid and sustained virological response were identified by logistic analysis; regression coefficients were used to generate prediction models for sustained virological response. Probabilities at baseline and treatment week 4 were utilized to develop a decision rule to select patients with high likelihood of response. The model was then validated in 423 patients (validation cohort). RESULTS: In the derivation cohort, 257 achieved rapid virological response and 818 did not, with sustained virological response rates of 80.2% and 25.4%, respectively; interleukin-28B polymorphisms, fibrosis staging, gamma-glutamyl transferase, and viral load predicted sustained virological response. Assuming a <30% sustained virological response probability for not recommending Peg-interferon+ribavirin, 100 patients (25.6%) in the validation cohort were predicted a priori to fail this regimen. Assuming a ≥80% sustained virological response probability as a threshold to continue with Peg-interferon+ribavirin, 61 patients were predicted to obtain sustained virological response, and 55 of them (90.2%) eventually did. CONCLUSIONS: This model uses easily determined variables for a personalized estimate of the probability of sustained virological response with Peg-interferon+ribavirin, allowing to identify patients who may benefit from conventional therapy.
BACKGROUND: Aim was to select naïve patients with genotype 1 chronic hepatitis C having a high probability of response to Peg-interferon+ribavirin therapy. METHODS: In 1073 patients (derivation cohort), predictors of rapid and sustained virological response were identified by logistic analysis; regression coefficients were used to generate prediction models for sustained virological response. Probabilities at baseline and treatment week 4 were utilized to develop a decision rule to select patients with high likelihood of response. The model was then validated in 423 patients (validation cohort). RESULTS: In the derivation cohort, 257 achieved rapid virological response and 818 did not, with sustained virological response rates of 80.2% and 25.4%, respectively; interleukin-28B polymorphisms, fibrosis staging, gamma-glutamyl transferase, and viral load predicted sustained virological response. Assuming a <30% sustained virological response probability for not recommending Peg-interferon+ribavirin, 100 patients (25.6%) in the validation cohort were predicted a priori to fail this regimen. Assuming a ≥80% sustained virological response probability as a threshold to continue with Peg-interferon+ribavirin, 61 patients were predicted to obtain sustained virological response, and 55 of them (90.2%) eventually did. CONCLUSIONS: This model uses easily determined variables for a personalized estimate of the probability of sustained virological response with Peg-interferon+ribavirin, allowing to identify patients who may benefit from conventional therapy.
Authors: A Andriulli; F Morisco; A M Ippolito; V Di Marco; M R Valvano; M Angelico; G Fattovich; R Granata; A Smedile; M Milella; M Felder; G B Gaeta; P Gatti; M Fasano; G Mazzella; T Santantonio Journal: Hepatol Int Date: 2014-08-13 Impact factor: 6.047
Authors: Sebastián Marciano; Silvia M Borzi; Melisa Dirchwolf; Ezequiel Ridruejo; Manuel Mendizabal; Fernando Bessone; María E Sirotinsky; Diego H Giunta; Julieta Trinks; Pablo A Olivera; Omar A Galdame; Marcelo O Silva; Hugo A Fainboim; Adrián C Gadano Journal: World J Hepatol Date: 2015-04-08
Authors: Nadia A Nabulsi; Michelle T Martin; Lisa K Sharp; David E Koren; Robyn Teply; Autumn Zuckerman; Todd A Lee Journal: Front Pharmacol Date: 2020-11-13 Impact factor: 5.810
Authors: Anna Szymanek-Pasternak; Krzysztof A Simon; Sylwia Serafińska; Justyna Janocha-Litwin; Monika Pazgan-Simon; Grzegorz Madej Journal: Clin Exp Hepatol Date: 2016-11-28