Alkaline phosphatase at diagnosis of primary sclerosing cholangitis and 1 year later: evaluation of prognostic value

Primary sclerosing cholangitis (PSC) is a slowly progressive liver disease. Reliable biomarkers to predict outcome are urgently needed to serve as surrogate endpoints and/or stratifiers in clinical trials. Reduction in serum alkaline phosphatase (ALP) has been proposed as prognostic surrogate marker in PSC. The aim of this study was to asses if ALP at diagnosis (T0), 1 year later (T1), and percentage change between both time points hold prognostic value, and to determine the optimal threshold.

[1]  G. Gores,et al.  Surrogate endpoints for clinical trials in primary sclerosing cholangitis: Review and results from an International PSC Study Group consensus process , 2016, Hepatology.

[2]  M. Leeflang,et al.  Applicability and prognostic value of histologic scoring systems in primary sclerosing cholangitis. , 2015, Journal of hepatology.

[3]  R. Poupon.  Liver alkaline phosphatase: A missing link between choleresis and biliary inflammation , 2015, Hepatology.

[4]  A. Burroughs,et al.  Levels of alkaline phosphatase and bilirubin are surrogate end points of outcomes of patients with primary biliary cirrhosis: an international follow-up study. , 2014, Gastroenterology.

[5]  W. Stremmel,et al.  Reduction in alkaline phosphatase is associated with longer survival in primary sclerosing cholangitis, independent of dominant stenosis , 2014, Alimentary pharmacology & therapeutics.

[6]  T. Karlsen,et al.  Review article: controversies in the management of primary biliary cirrhosis and primary sclerosing cholangitis , 2014, Alimentary pharmacology & therapeutics.

[7]  F. Vleggaar,et al.  Population‐based epidemiology, malignancy risk, and outcome of primary sclerosing cholangitis , 2013, Hepatology.

[8]  K. Boberg,et al.  Association between reduced levels of alkaline phosphatase and survival times of patients with primary sclerosing cholangitis. , 2013, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

[9]  R. Chapman,et al.  Improvement of serum alkaline phosphatase to <1.5 upper limit of normal predicts better outcome and reduced risk of cholangiocarcinoma in primary sclerosing cholangitis. , 2013, Journal of hepatology.

[10]  T. Fleming,et al.  Biomarkers and surrogate endpoints in clinical trials , 2012, Statistics in medicine.

[11]  E. Björnsson,et al.  Alkaline phosphatase normalization is associated with better prognosis in primary sclerosing cholangitis. , 2011, Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver.

[12]  G. Gores,et al.  Diagnosis and management of primary sclerosing cholangitis , 2010, Hepatology.

[13]  K. V. van Erpecum,et al.  Improved prognosis of patients with primary biliary cirrhosis that have a biochemical response to ursodeoxycholic acid. , 2009, Gastroenterology.

[14]  Y. Chrétien,et al.  Biochemical response to ursodeoxycholic acid and long‐term prognosis in primary biliary cirrhosis , 2008, Hepatology.

[15]  Tianxi Cai,et al.  Evaluating Prediction Rules for t-Year Survivors With Censored Regression Models , 2007 .

[16]  J. Rodés,et al.  Excellent long-term survival in patients with primary biliary cirrhosis and biochemical response to ursodeoxycholic Acid. , 2006, Gastroenterology.

[17]  R. Chapman,et al.  The medical management of primary sclerosing cholangitis. , 2006, Seminars in liver disease.

[18]  Sunil J Rao,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2003 .

[19]  C. Benz,et al.  [Primary sclerosing cholangitis]. , 2000, Der Internist.

[20]  C. Garbe,et al.  Problems in defining cutoff points of continuous prognostic factors: example of tumor thickness in primary cutaneous melanoma. , 1997, Journal of clinical epidemiology.

[21]  F. Harrell,et al.  Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors , 2005 .

[22]  J J Shuster,et al.  Re: Dangers of using "optimal" cutpoints in the evaluation of prognostic factors. , 1994, Journal of the National Cancer Institute.

[23]  W. Sauerbrei,et al.  Dangers of using "optimal" cutpoints in the evaluation of prognostic factors. , 1994, Journal of the National Cancer Institute.