Alessandro Cucchetti1, Franco Trevisani2, Anna Pecorelli2, Virginia Erroi2, Fabio Farinati3, Francesca Ciccarese4, Gian Lodovico Rapaccini5, Mariella Di Marco6, Eugenio Caturelli7, Edoardo G Giannini8, Marco Zoli2, Franco Borzio9, Giuseppe Cabibbo10, Martina Felder11, Antonio Gasbarrini12, Rodolfo Sacco13, Francesco Giuseppe Foschi14, Gabriele Missale15, Filomena Morisco16, Gianluca Svegliati Baroni17, Roberto Virdone18, Mauro Bernardi2, Antonio D Pinna2. 1. Dipartimento di Scienze Mediche e Chirurgiche, Policlinico S. Orsola-Malpighi, Alma Mater Studiorum - Università of Bologna, Italy. Electronic address: aleqko@libero.it. 2. Dipartimento di Scienze Mediche e Chirurgiche, Policlinico S. Orsola-Malpighi, Alma Mater Studiorum - Università of Bologna, Italy. 3. Dipartimento di Scienze Chirurgiche e Gastroenterologiche, Unità di Gastroenterologia, Università di Padova, Padova, Italy. 4. Divisione di Chirurgia, Policlinico San Marco, Zingonia, Italy. 5. Unità di Medicina Interna e Gastroenterologia, Complesso Integrato Columbus, Università Cattolica di Roma, Roma, Italy. 6. Divisione di Medicina, Azienda Ospedaliera Bolognini, Seriate, Italy. 7. Unità Operativa di Gastroenterologia, Ospedale Belcolle, Viterbo, Italy. 8. Dipartimento di Medicina Interna, Unità di Gastroenterologia, Università di Genova, Genova, Italy. 9. Dipartimento di Medicina, Unità di Radiologia, Ospedale Fatebenefratelli, Milano, Italy. 10. Dipartimento Biomedico di Medicina Interna e Specialistica, Unità di Gastroenterologia, Università di Palermo, Palermo, Italy. 11. Ospedale Regionale di Bolzano, Unità di Gastroenterologia, Bolzano, Italy. 12. Unità di Medicina Interna e Gastroenterologia, Policlinico Gemelli, Università Cattolica di Roma, Roma, Italy. 13. Unità Operativa Gastroenterologia e Malattie del Ricambio, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy. 14. Unità di Medicina Interna, Presidio Ospedaliero di Faenza, Faenza, Italy. 15. Unità di Malattie Infettive ed Epatologia, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy. 16. Dipartimento di Medicina Clinica e Chirurgia, Unità di Gastroenterologia, Università di Napoli "Federico II", Napoli, Italy. 17. Clinica di Gastroenterologia, Università Politecnica delle Marche, Ancona, Italy. 18. Dipartimento Biomedico di Medicina Interna e Specialistica, Unità di Medicina Interna, Palermo, Italy.
Abstract
BACKGROUND & AIMS: Lead-time is the time by which diagnosis is anticipated by screening/surveillance with respect to the symptomatic detection of a disease. Any screening program, including surveillance for hepatocellular carcinoma (HCC), is subject to lead-time bias. Data regarding lead-time for HCC are lacking. Aims of the present study were to calculate lead-time and to assess its impact on the benefit obtainable from the surveillance of cirrhotic patients. METHODS: One-thousand three-hundred and eighty Child-Pugh class A/B patients from the ITA.LI.CA database, in whom HCC was detected during semiannual surveillance (n = 850), annual surveillance (n = 234) or when patients came when symptomatic (n = 296), were selected. Lead-time was estimated by means of appropriate formulas and Monte Carlo simulation, including 1000 patients for each arm. RESULTS: The 5-year overall survival after HCC diagnosis was 32.7% in semiannually surveilled patients, 25.2% in annually surveilled patients, and 12.2% in symptomatic patients (p<0.001). In a 10-year follow-up perspective, the median lead-time calculated for all surveilled patients was 6.5 months (7.2 for semiannual and 4.1 for annual surveillance). Lead-time bias accounted for most of the surveillance benefit until the third year of follow-up after HCC diagnosis. However, even after lead-time adjustment, semiannual surveillance maintained a survival benefit over symptomatic diagnosis (number of patients needed to screen = 13), as did annual surveillance (18 patients). CONCLUSIONS: Lead-time bias is the main determinant of the short-term benefit provided by surveillance for HCC, but this benefit becomes factual in a long-term perspective, confirming the clinical utility of an anticipated diagnosis of HCC.
BACKGROUND & AIMS: Lead-time is the time by which diagnosis is anticipated by screening/surveillance with respect to the symptomatic detection of a disease. Any screening program, including surveillance for hepatocellular carcinoma (HCC), is subject to lead-time bias. Data regarding lead-time for HCC are lacking. Aims of the present study were to calculate lead-time and to assess its impact on the benefit obtainable from the surveillance of cirrhotic patients. METHODS: One-thousand three-hundred and eighty Child-Pugh class A/B patients from the ITA.LI.CA database, in whom HCC was detected during semiannual surveillance (n = 850), annual surveillance (n = 234) or when patients came when symptomatic (n = 296), were selected. Lead-time was estimated by means of appropriate formulas and Monte Carlo simulation, including 1000 patients for each arm. RESULTS: The 5-year overall survival after HCC diagnosis was 32.7% in semiannually surveilled patients, 25.2% in annually surveilled patients, and 12.2% in symptomatic patients (p<0.001). In a 10-year follow-up perspective, the median lead-time calculated for all surveilled patients was 6.5 months (7.2 for semiannual and 4.1 for annual surveillance). Lead-time bias accounted for most of the surveillance benefit until the third year of follow-up after HCC diagnosis. However, even after lead-time adjustment, semiannual surveillance maintained a survival benefit over symptomatic diagnosis (number of patients needed to screen = 13), as did annual surveillance (18 patients). CONCLUSIONS: Lead-time bias is the main determinant of the short-term benefit provided by surveillance for HCC, but this benefit becomes factual in a long-term perspective, confirming the clinical utility of an anticipated diagnosis of HCC.
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