Mario Strazzabosco

Università degli Studi di Milano-Bicocca, Milano, Lombardy, Italy

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Publications (194)1275.89 Total impact

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    ABSTRACT: Objectives: the impact of liver diseases (LDs) on health-related quality of life (HRQoL) is an important aspect to understand the burden of these conditions and improve their management. A well characterized impact of the major LDs on HRQoL of the general population is still lacking. The aim of our study was to fill this GAP. Methods: a dataset with HRQoL data of a representative sample of the general population of most populated Italian region was matched with the dataset from a multicenter study conducted in the same region and time period to generate and validate a set of health care outcomes indicators for the major LDs (hepatitis B (HBV), hepatitis C (HCV), compensated cirrhosis (CC), decompensated cirrhosis (DC), hepatocellular carcinoma (HCC), autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC), primary sclerosing cholangitis (PSC), NAFLD/NASH and patients listed for liver transplant (LTL)). Within both datasets, HRQoL data were collected using the EQ-5D-3L. Multivariate logistic and Tobit regressions were then performed adjusting for possible confounders (age, sex, education and working status). Results: a total of 6,800 “healthy subjects” and 3,105 subjects with LDs were included in the analyses. Multivariate logistic analyses showed that DC, HCC, and LTL had significantly (p< 0.05) higher risk to have problems in mobility, self-care, and usual activities compared to “healthy subjects”. AIH had significantly higher risk to have problems in self-care; while HCV, CC, DC, and NAFLD/NASH in Anxiety/depression. Similar results were obtained with the Tobit model performed using VAS and Utility-index. DC, HCC, AIH and LTL reported the highest decrease in VAS and Utility score. Conclusions: HRQoL decreased in advanced LDs (DC, HCC, LTL) and AIH. This study provides an actual true estimate of the impact of major LDs on the patients’ HRQoL compare to the general population, and therefore is a key tool for decision-making in care delivery for liver diseases.
    Value in Health 11/2014; 17(7):A369. · 2.89 Impact Factor
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    ABSTRACT: Objectives: Sofosbuvir in combination with ribavirin (SOF/RBV) is a novel treatment able to suppress HCV viremia when applied to HCV patients listed for transplant, preventing HCV recurrence. Aim of this study was to assess the costeffectiveness of this regimen in HCV patients listed for transplant for cirrhosis (HCVcirrhosis) or for hepatocellular carcinoma (HCV-HCC). Methods: a semi-Markov model was developed. The model simulates the progression of HCV-cirrhosis or HCV-HCC patients from the time of listing until death considering the risk of HCV recurrence post-transplant. The model compared 2 different strategies: 1) SOF/RBV up to a maximum of 24 weeks or until OLT if performed before the 24th week, 2) No antiviral treatment. The model estimated the costs related to the treatment with SOF/RBV, the costs associated to each health state, the life-years (LYSs), the quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio (ICER) expressed as € per QALY gained. The analysis was performed from the Italian National Health System perspective with a lifetime time horizon and one-month Markov cycles. Future costs and clinical benefits, expressed as QALYs, were discounted at 3% per year. Results: in the base-case analysis the ICER for 24 weeks of SOF/RBVR was € 30,518 per QALY gained in HCV-cirrhosis patients and € 41,610 in HCV-HCC patients. The reliability of our results was confirmed by the one way sensitivity-analysis and by the cost-effectiveness acceptability curve. Further, SOF/RBV cost-effectiveness was clearly sensitive to the duration of treatment; assuming 12 weeks SOF/RBV treatment duration, the ICER decreased to € 19,317 in HCVCirrhosis and € 29,540 in HCV-HCC. Conclusions: our study shows that treating patients with HCV-cirrhosis or HCV-HCC listed for transplant with SOF/RBV is cost-effective and may become the new standard of care for these patients. However a well-defined prospective study is needed to confirm the value of the parameters assumed in the model and the results.
    Value in Health 11/2014; 17(7):A367-A368. · 2.89 Impact Factor
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    ABSTRACT: The impact of liver diseases (LDs) on health-related quality of life (HRQoL) is an important aspect to understand the burden of these conditions and to improve their management. A well characterized impact of the major LDs on HRQoL of the general population is still lacking. The aim of our study was to fill this gap. A dataset with HRQoL data of a representative sample of the general population of most populated Italian region was matched with the dataset from a multicenter study conducted in the same region and time period to generate and validate a set of health care outcomes indicators for the major LDs (hepatitis B (HBV), hepatitis C (HCV), compensated cirrhosis (CC), decompensated cirrhosis (DC), hepatocellular carcinoma (HCC), autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC), primary sclerosing cholangitis (PSC), NAFLD/ NASH and patients listed for liver transplant (LTL)). Within both datasets, HRQoL data were collected using the EQ-5D-3L, a generic instrument that enables HRQoL to be compared within and between clinical conditions and with the general population. It generates a health profile made up of 5 domains (Mobility, Self-care, Usual activities, Pain/discomfort, Anxiety/ depression). It also consists of a visual analogue scale (EQ-5D VAS) which measures overall HRQoL. Further, results from the EQ-5D health profile can be converted to utility index, useful to conduct economic evaluations. Multivariate logistic and linear regressions were then performed adjusting for possible confounders (age, sex, education and working status). A total of 6,800 nullhealthy subjectsnull and 3,105 subjects with LDs (625 HCV, 287 HBV, 614 CC, 531 DC, 647 HCC, 59 LTL, 229 NAFLD/NASH, 68 PBC, 55 PSC, and 49 AIH) were included in the analyses. Multivariate logistic analyses showed that DC, HCC, and LTL had significantly (p<0.05) higher risk to have problems in mobility, self-care, and usual activities compared to nullhealthy subjectednull. AIH had significantly higher risk to have problems in self-care while HCV, CC, DC, and NAFLD/NASH in Anxiety/depression. Similar results were obtained with multivariate linear analyses performed using VAS and Utility-index. DC, HCC, AIH and LTL reported the highest decrease in VAS and Utility score. In conclusion, our results show that HRQoL of asymptomatic liver conditions are comparable to the general population except for the Anxiety/depression dimension. The HRQoL decreased in advanced LDs (DC, HCC, LTL) and AIH. This study provides an actual true estimate of the impact of major LDs on the patients' HRQoL compare to the general population, and therefore is a key tool for decision-making in care delivery for liver diseases.
    Hepatology 10/2014; 60(Suppl 1):948A-949A. · 11.19 Impact Factor
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    ABSTRACT: Development of complications in liver cirrhosis (LC) is associated with increased mortality, hospital admissions and costs. Management of LC complications in clinical practice is well established, but the real value and effectiveness of care provided are still difficult to assess. Measurement of outcome indicators (OIs) together with patients-health related quality of life (p-HRQoL) could assist both clinicians and administrators in the process of care, in order to ensure greater quality in patients with LC. Aim of our study was to validate specific OIs, coupled with p-HRQoL scales, and apply them in the clinical assessment of compensated (CC) and decompensated cirrhosis (DC) management. A panel of hepatologists identified a set of OIs using published evidence, a modified Delphi method and a standard 9-point RAND appropriateness scale. These OIs were part of a larger effort, included in a prospective multicenter observational study (Value Based Medicine in Hepatology Study), involving three European tertiary clinical centers. P-HRQoL collected using the EQ-5D questionnaire, generated an health profile, by means of five utility domains (mobility, self care, anxiety/ depression, usual activities and pain/discomfort), and a visual analogue scale (VAS), which measured overall p-HRQoL in a range from 0 to 100. During 18 months we enrolled 1772 patients with LC: 1015 CC and 757 DC; the median follow-up time was 2 years. Results: the OIs chosen by the panelist were meant to evaluate the efficacy of care of major complications of LC: variceal bleeding occurred with an annual incidence of 3,1%, with 1-year survival of 76% of patients, and hepatocellular carcinoma (HCC) developed in a rate of 3,5% per year, with 83% CC patients diagnosed at early stage HCC. The strongest OIs according to the experts were decompensation rate in CC, which was 6.6% per year in our study, and overall survival in DC patients. The 1-year survival after the first decompensation episode (ascites in 73% of cases) was 96% for CPTA, 82% for CPT-B, 56% CPT-C, whereas it was 94% and 57% for MELD score respectively below or above 15. Furthermore, no significant changes in p-HRQoL between baseline and after 2 years follow-up were found in CC and CPT-A patients, while p-HRQoL progressively decreased in DC and CPT B-C patients. In conclusion, combined measurements of specific OIs and p-HRQoL scales provide the methodological bases to implement a value-based approach to the care of patients with LC. In fact, these outcomes combined with measurements of direct and indirect costs could guide future decision-making process and improve value of care in cirrhosis.
    Hepatology 10/2014; 60(Suppl 1):942A-943A. · 11.19 Impact Factor
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    ABSTRACT: Complications in liver cirrhosis (LC) are associated with increased mortality and costs. Management of LC complications is well established in clinical practice, but their real effectiveness is difficult to measure. Assessment of outcome indicators (OIs) together with patients-health related quality of life (p-HRQoL) could help decision-making process for clinicians and administrators. Aim: The aim of our study was to identify a set of OIs, and apply them in the clinical assessment of compensated (CC) and decompensated cirrhosis (DC), together with p-HRQoL scales. Specific OIs chosen by a panel of hepatologists with a modified Delphi method, were tested in a prospective multicenter observational study. P-HRQoL collected using the EQ-5D questionnaire, generated an health profile with five utility domains (mobility, self care, anxiety/depression, usual activities and pain), and a visual analogue scale, which measured overall p-HRQoL in a range from 0 to 100. We enrolled 1772 patients with LC in 18 months: 1015 CC and 757 DC; median follow-up time was 2 years. Results: Variceal bleeding had an annual incidence of 3.1% with 1-year survival of 76%. Hepatocellular carcinoma occurred in a rate of 3.5% per year, and 83% CC patients were diagnosed at early stage. The strongest OIs according to the experts were decompensation rate in CC, which was 6.6% per year, and overall survival in DC patients. The 1-year survival after the first decompensation episode (ascites in 73% of cases) was 96% for CPT-A, 82% CPT-B, 56% CPT-C, whereas it was 94% and 57% for MELD score respectively below or above 15. Interestingly, no significant changes in p-HRQoL between baseline and after 2 years were found in CC and CPT-A patients, while p-HRQoL progressively decreased in DC and CPT B-C. Conclusions: Systematic measurement and comparison of objective OIs and p-HRQoL scales could increase value-based care in liver cirrhosis patients.
    Digestive and Liver Disease 10/2014; 46(Suppl 4):e129. · 2.89 Impact Factor
  • Mario Strazzabosco, Luca Fabris, Emanuele Albano
    Gut 07/2014; · 13.32 Impact Factor
  • Mario Strazzabosco, Luca Fabris
    Hepatology 07/2014; · 11.19 Impact Factor
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    ABSTRACT: New and more promising therapies for chronic hepatitis C (CHC) genotype 1 (G1) naive patients have recently been approved in the United States and Europe, and several more regimens are expected to become available within the next several years. While this scenario unfolds, it is necessary to develop a rational method to allocate current treatment in CHC G1 patients. We performed a cost-effectiveness analysis of boceprevir (BOC)- and telaprevir (TVR)-based triple therapy according to different patients’ selection strategies. A semi-Markov model of CHC natural history and progression towards end-stage liver disease was built. We considered 3 selection strategies based on METAVIR fibrosis stage: (i) treat all patients with F1–F4 fibrosis, (ii) only F2–F4 and (iii) only F3–F4. For each strategy, TVR interleukin-28B-guided (IL28B-guided) and BOC rapid virologic response-guided (RVR-guided) therapies were applied. The model assessed the costs and outcomes, using a lifetime and 5-year time horizon, and adopting the Italian National Health System perspective. The incremental cost-effectiveness ratio (ICER) for F1–F4 strategy relative to F3–F4 was €5132 per quality-adjusted life years gained, across TVR IL-28B-guided therapy, and €7042 in the BOC RVR-guided therapy. Conversely, in the 5-year scenario, the ICER for F1–F4 strategy relative to F3–F4 was €1 818 679 (TVR IL28B-guided) and €1 866 437 (BOC RVR-guided) per end-stage liver disease or death (ESLD-D) avoided. In view of anticipated improvement in the efficacy of future regimens, selective treatment of only patients with advanced fibrosis and cirrhosis with TVR or BOC could represent the most cost-effective strategy to optimize resource utilization.
    Journal of Viral Hepatitis 07/2014; 22(2):173-81. · 3.08 Impact Factor
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    ABSTRACT: Background and Aims: Hepatocellular carcinoma (HCC) is a worldwide public health problem, accounting for increasing mortality and high costs. Aim of our study was to identify and test outcome indicators (OIs) in HCC, in light of their potential use in policy decision models. Methods: A panel of experts identified a list of OIs using a modified Delphi method; three of these OIs with the highest RAND/UCLA scores were tested in a prospective multicenter observational study (Value Based Medicine in Hepatology, VBMH). During 18 months, 711 HCC patients were enrolled and prospectively followed. Median follow-up time was 14 months. Results: The first OI was survival after 1–3–5 years stratified for BCLC stage or treatment (OI#1). One-year survival for BCLC stage 0/A, B, C, D was 93%, 86%, 50%, 26% respectively. One-year survival of 288 patients who had the first treatment during the study time was 88% for liver transplantation, 97% surgical resection, 100% ablation and 89% for TACE. The remaining two OIs meant to evaluate the appropriateness of treatments. Worsening of BCLC and/or CPT score after loco-regional therapy or surgical resection recorded at three months (OI#2), occurred in 16% of cases (76% after TACE). Very early HCC recurrence (within 6 months) after curative treatments (OI#3) happened in 15% of patients treated (20% after ablation). Conclusions: This set of outcome indicators proved their feasibility in a large cohort of patients and could serve as a benchmark for healthcare providers to move towards a value-based approach in the management of HCC.
    Journal of Hepatology 04/2014; 60(Suppl 1):S399 -. · 10.40 Impact Factor
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    ABSTRACT: Background and Aims: Liver disease (LD) is a major cause of morbidity and mortality worldwide. Development of outcome indicators (OIs) provides health care policy makers with objective criteria that can be used to generate a virtuous competition to improve value of care. Aim of our study was to generate and test a set of health care OIs for the major LDs. Methods: Using a modified Delphi method, 7 expert panels identified a set of OIs according to experience and scientific evidence (as of 2010). Each OI was rated in a two-step process using the RAND 9-point agreement scale. Median scores were computed for each OI. After the second rating, a disagreement index (DI) was calculated to identify and accept (if DI≤1) OIs with median rating ≥7. The final set of selected OIs was tested through an ongoing prospective multicenter observational study involving three tertiary centers in Lombardy, Italy. Results: A total of 51 OIs were identified by the focus groups. We recruited 3213 consecutive liver patients, of whom 91% had at least one follow-up visit after a median follow-up time of 15 months. Among these patients, 1752 were cirrhotic and 711 were affected by HCC. During observation time, 156 patients were transplanted and 210 patients died. All the identified OIs were successfully tested in the clinical setting showing excellent performance and correlation with natural history information. Conclusions: This study provides a set of validated outcomes indicators that can be used to monitor the performance of referral centers and improve the value and sustainability of care.
    Journal of Hepatology 04/2014; 60(Suppl 1):S517 -. · 10.40 Impact Factor
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    ABSTRACT: Background and Aims: Liver Cirrhosis (LC) is responsible for high morbidity, mortality and increasing costs. Aim of our study was to identify outcome indicators (OIs) able to measure quality and value of care in compensated (CC) and decompensated (DC) cirrhosis. Methods: A panel of experts identified a list of OIs using a modified Delphi method; seven of these OIs with the highest RAND/UCLA scores were then tested in a prospective multicenter observational study (Value Based Medicine in Hepatology, VBMH). During 18 months, 1751 patients with LC were enrolled (1004 CC, 747 DC). Results: Annual rate of decompensation (OI#1), annual incidence of first variceal bleeding (OI#2) and annual incidence of HCC (OI#3) in CC were 12%, 2% for low- and 3% for high-risk varices, and 4.3% (81% diagnosed in BCLC-A stage) respectively. One-year survival for CPT score A, B, C was 96%, 81% and 59% (OI#4) respectively, and 94%, 56% when stratified for MELD cut-off of 15 (OI#5). Among DC patients, 4% of them had an episode of variceal bleeding (6 weeks survival 90%, 32% recurrence) (OI#6), 3% had spontaneous bacterial peritonitis (6 weeks survival 86%, 13% recurrence) (OI#7). Conclusions: The seven outcome indicators identified in our study performed well when tested in a large cohort of patients and represent a reference tool to implement a value-based approach to liver diseases.
    Journal of Hepatology 04/2014; 60(Suppl 1):S228 -. · 10.40 Impact Factor
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    ABSTRACT: BACKGROUND: To generate a robust predictive model of Early (3 months) Graft Loss after liver transplantation, we used a Bayesian approach to combine evidence from a prospective European cohort (Liver-Match) and the United Network for Organ Sharing registry. METHODS: Liver-Match included 1480 consecutive primary liver transplants performed from 2007 to 2009 and the United Network for Organ Sharing a time-matched series of 9740 transplants. There were 173 and 706 Early Graft Loss, respectively. Multivariate analysis identified as significant predictors of Early Graft Loss: donor age, donation after cardiac death, cold ischaemia time, donor body mass index and height, recipient creatinine, bilirubin, disease aetiology, prior upper abdominal surgery and portal thrombosis. RESULTS: A Bayesian Cox model was fitted to Liver-Match data using the United Network for Organ Sharing findings as prior information, allowing to generate an Early Graft Loss-Donor Risk Index and an Early Graft Loss-Recipient Risk Index. A Donor-Recipient Allocation Model, obtained by adding Early Graft Loss-Donor Risk Index to Early Graft Loss-Recipient Risk Index, was then validated in a distinct United Network for Organ Sharing (year 2010) cohort including 2964 transplants. Donor-Recipient Allocation Model updating using the independent Turin Transplant Centre dataset, allowed to predict Early Graft Loss with good accuracy (c-statistic: 0.76). CONCLUSION: Donor-Recipient Allocation Model allows a reliable donor and recipient-based Early Graft Loss prediction. The Bayesian approach permits to adapt the original Donor-Recipient Allocation Model by incorporating evidence from other cohorts, resulting in significantly improved predictive capability
    Digestive and Liver Disease 04/2014; 46(4):340-347. · 2.89 Impact Factor
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    ABSTRACT: Background and Aims: To allocate treatment resources for CHC G1 patients, we performed a cost-effectiveness analysis of Boceprevir (BOC) and Telaprevir (TVR) based triple therapy according to different patient selection strategies. Methods: A semi-Markov model of CHC natural history and progression toward end stage liver diseases (decompensated cirrhosis, HCC and liver transplantation) was built. Model health states were defined by METAVIR fibrosis stages (F0–F4), and complications of cirrhosis. We considered 3 selection strategies based on fibrosis stage: 1) treat all patients with F1–F4 fibrosis, 2) only F2–F4 and 3) only F3–F4. For each strategy, TVR IL28B-guided and BOC RVR-guided therapy was applied. The model assessed the costs and outcomes, including QALYs, Life Years and the number of End Stage Liver Diseases developed or Death (ESLD-D), using lifetime as time horizon and adopting the NHS perspective. An alternative simulation was performed using 5 year as time horizon. Results: The F3–F4 selection strategy was the least expensive and the least effective. Adopting the lifetime horizon, F1–F4 strategy was cost-effective with an ICER of €5,132.13 for QALY, in TVR IL28Bguided, and €7,042.49 for QALY, in BOC RVR-guided therapy. In the 5 year scenario, the F1–F4 strategy was not cost-effective with an ICER of €1,818,679 (TVR IL-28B-guided) and €1,866.437 (BOC RVR-guided) for each ESLD-D avoided. Conclusions: Our model demonstrated the impact of patient selection strategies, and lifetime versus 5 year time horizons, on cost-effectiveness of HCV therapy, and its implications for the evaluation of cost utility of future interferon-containing and interferon-free regimens.
    Journal of Hepatology 04/2014; 60(Suppl 1):S493. · 9.86 Impact Factor
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    ABSTRACT: Primary sclerosing cholangitis (PSC) is a chronic cholangiopathy characterized by biliary fibrosis, development of cholestasis and end stage liver disease, high risk of malignancy and frequent need for liver transplantation. The poor understanding of its pathogenesis is also reflected in the lack of effective medical treatment. Well-characterized animal models are utterly needed to develop novel pathogenetic concepts and study new treatment strategies. Currently there is no consensus on how to evaluate and characterize potential PSC models, which makes direct comparison of experimental results and effective exchange of study material between research groups difficult. The International Primary Sclerosing Cholangitis Study Group (IPSCSG) has therefore summarized these key issues in a position paper proposing standard requirements for the study of animal models of PSC.
    Journal of Hepatology 02/2014; · 9.86 Impact Factor
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    Digestive and Liver Disease 02/2014; 46(Suppl 1):e11. · 2.89 Impact Factor
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    Digestive and Liver Disease 02/2014; 46(Suppl 1):e63. · 2.89 Impact Factor
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    Digestive and Liver Disease 02/2014; 46(Suppl 1):e7. · 2.89 Impact Factor
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    ABSTRACT: To generate a robust predictive model of Early (3 months) Graft Loss after liver transplantation, we used a Bayesian approach to combine evidence from a prospective European cohort (Liver-Match) and the United Network for Organ Sharing registry. Liver-Match included 1480 consecutive primary liver transplants performed from 2007 to 2009 and the United Network for Organ Sharing a time-matched series of 9740 transplants. There were 173 and 706 Early Graft Loss, respectively. Multivariate analysis identified as significant predictors of Early Graft Loss: donor age, donation after cardiac death, cold ischaemia time, donor body mass index and height, recipient creatinine, bilirubin, disease aetiology, prior upper abdominal surgery and portal thrombosis. A Bayesian Cox model was fitted to Liver-Match data using the United Network for Organ Sharing findings as prior information, allowing to generate an Early Graft Loss-Donor Risk Index and an Early Graft Loss-Recipient Risk Index. A Donor-Recipient Allocation Model, obtained by adding Early Graft Loss-Donor Risk Index to Early Graft Loss-Recipient Risk Index, was then validated in a distinct United Network for Organ Sharing (year 2010) cohort including 2964 transplants. Donor-Recipient Allocation Model updating using the independent Turin Transplant Centre dataset, allowed to predict Early Graft Loss with good accuracy (c-statistic: 0.76). Donor-Recipient Allocation Model allows a reliable donor and recipient-based Early Graft Loss prediction. The Bayesian approach permits to adapt the original Donor-Recipient Allocation Model by incorporating evidence from other cohorts, resulting in significantly improved predictive capability.
    Digestive and Liver Disease 01/2014; · 2.89 Impact Factor
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    Carola Maria Morell, Mario Strazzabosco
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    ABSTRACT: Notch signaling is a crucial determinant of cell fate decision during development and disease in several organs. Notch effects are strictly dependent on the cellular context in which it is activated. In the liver, Notch signaling is involved in biliary tree development and tubulogenesis. Recent advances have shed the light on Notch as a critical player in liver regeneration and repair, as well as in liver metabolism and inflammation and cancer. Notch signaling is finely regulated at several levels. The complexity of the pathway provides several possible targets for development of therapeutic agents able to inhibit Notch. Recent reports have shown that persistent activation of Notch signaling is associated with liver malignancies, particularly hepatocellular with stem cell features and cholangiocarcinoma. These novel findings suggest that interfering with the aberrant activation of Notch pathway may have therapeutic relevance. However, further studies are needed to clarify the mechanisms regulating physiologic and pathologic Notch activation in the adult liver, to better understand the mechanistic role(s) of Notch in liver diseases and to develop safe and specific therapeutic agents.
    Journal of Hepatology 12/2013; · 9.86 Impact Factor
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    Value in Health 11/2013; 16(7):A500. · 2.89 Impact Factor

Publication Stats

2k Citations
1,275.89 Total Impact Points

Institutions

  • 2010–2014
    • Università degli Studi di Milano-Bicocca
      • Department of Surgery and Interdisciplinary Medicine
      Milano, Lombardy, Italy
  • 1989–2014
    • Yale University
      • • Section of Digestive Diseases
      • • Department of Internal Medicine
      • • School of Medicine
      New Haven, Connecticut, United States
  • 2013
    • University of Naples Federico II
      Napoli, Campania, Italy
  • 2004–2013
    • Ospedali Riuniti di Bergamo
      Bérgamo, Lombardy, Italy
  • 1991–2013
    • Yale-New Haven Hospital
      New Haven, Connecticut, United States
  • 1983–2013
    • University of Padova
      • • Department of Surgery, Oncology and Gastroenterology DISCOG
      • • Department of Pediatrics
      • • Department of Medicine DIMED
      Padova, Veneto, Italy
  • 2009–2011
    • Medical University of Graz
      • Institut für Pathologie
      Gratz, Styria, Austria
  • 2005
    • Istituto Mediterraneo per i Trapianti e Terapie ad Alta Specializzazione (ISMETT)
      Palermo, Sicily, Italy
    • University of Rome Tor Vergata
      Roma, Latium, Italy
  • 1988–2003
    • Università degli studi di Parma
      Parma, Emilia-Romagna, Italy
  • 2002
    • Universidad de Navarra
      • Division of Gene Therapy and Hepatology
      Pamplona, Navarre, Spain
  • 2000
    • University of Vienna
      Wien, Vienna, Austria
    • Università degli Studi di Sassari
      Sassari, Sardinia, Italy
  • 1998–2000
    • University-Hospital of Padova
      Padua, Veneto, Italy