|
[1] WANG FS,FAN JG,ZHANG Z,et al. The global burden of liver disease:The major impact of China[J]. Hepatology,2014,60(6):2099-108.
|
|
[2] LIU J,ZHANG S,WANG Q,et al. Seroepidemiology of hepatitis B virus infection in 2 million men aged 21-49 years in rural China:A population-based,cross-sectional study[J].Lancet Infect Dis,2016,16(1):80-6.
|
|
[3] TERRAULT NA,LOK AS,MNCMAHO BJ,et al. Update on prevention,diagnosis,and treatment and of chronic hepatitis B:AASLD 2018 hepatitis B guidance[J]. Hepatology,2018,67(4):1560-1599.
|
|
[4] World Health Organization. Guidelines for the prevention,care and treatment of persons with chronic hepatitis B infection[M]. Geneva,2015.
|
|
[5] PAPATHEODORIDIS GV,CHAN HL,HANSEN BE,et al. Risk of hepatocellular carcinoma in chronic hepatitis B:Assessment and modification with current antiviral therapy[J]. J Hepatol,2015,62(4):956-967.
|
|
[6] GRADY D,BERKOWITZ SA. Why is a good clinical prediction rule so hard to find?[J]. Arch Intern Med,2011,171(19):1701-1702.
|
|
[7] TANGRI N,KENT DM. Toward a modern ear in clinical prediction:The TRIPOD statement for reporting prediction models[J]. Am J Kidney Dis,2015,65(4):530-533.
|
|
[8] STEYERBERG EW,VERGOUWE Y. Towards better clinical prediction models:Seven steps for development and an ABCD for validation[J]. Eur Heart J,2014,35(29):1925-31.
|
|
[9] MOONS KG,ALTMAN DG,REITSMA JB,et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD):Explanation and elaboration[J]. Ann Intern Med,2015,162(1):W1-W73.
|
|
[10] YUEN MF,TANAKA Y,FONG DY,et al. Independent risk factors and predictive score for the development of hepatocellular carcinoma in chronic hepatitis B[J]. J Hepatol,2009,50(1):80-88.
|
|
[11] YANG HI,SHERMAN M,SU J,et al. Nomograms for risk of hepatocellular carcinoma in patients with chronic hepatitis B virus infection[J]. J Clin Oncol,2010,28(14):2437-2444.
|
|
[12] WONY VW,CHAN SL,MO F,et al. Clinical scoring system to predict hepatocellular carcinoma in chronic hepatitis B carriers[J]. J Clin Oncol,2010,28(10):1660-1665.
|
|
[13] YANG HI,YUEN MF,CHAN HL,et al. Risk estimation for hepatocellular carcinoma in chronic hepatitis B(REACH-B):Development and validation of a predictive score[J]. Lancet Oncol,2011,12(6):568-574.
|
|
[14] WONY GL,CHAN HL,WONG CK,et al. Liver stiffnessbased optimization of hepatocellular carcinoma risk score in patients with chronic hepatitis B[J]. J Hepatol,2014,60(2):339-345.
|
|
[15] LEE HW,YOO EJ,KIM BK,et al. Prediction of development of liver-related events by transient elastography in hepatitis B patients with complete virological response on antiviral therapy[J]. Am J Gastroenterol,2014,109(8):1241-1249.
|
|
[16] PAPATHEODORIDIS GV,DALEKOS G,SYPSA V,et al. PAGEB:A risk score for hepatocellular carcinoma in Caucasians with chronic hepatitis B under a 5-year entecavir or tenofovir therapy[J]. J Hepatol,2016,64(4):800-806.
|
|
[17] POH Z,SHEN L,YANG HI,et al. Real-world risk score for hepatocellular carcinoma(RWS-HCC):A clinically practical risk predictor for HCC in chronic hepatitis B[J]. Gut,2016,65(5):887-888.
|
|
[18] KIM JH,KIM YD,LEE M,et al. Modified PAGE-B score predicts the risk of hepatocellular carcinoma in Asians with chronic hepatitis B on antiviral therapy[J]. J Hepatol,2018,69(5):1066-1073.
|
|
[19] HSU YC,YIP TC,HO HJ,et al. Development of a scoring system to predict hepatocellular carcinoma in Asians on antivirals for chronic hepatitis B[J]. J Hepatol,2018,69(2):278-285.
|
|
[20] YU JH,SUH YJ,JIN YJ,et al. Prediction model for hepatocellular carcinoma risk in treatment-naive chronic hepatitis B patients receiving entecavir/tenofovir[J]. Eur J Gastroenterol Hepatol,2019,31(7):865-872.
|
|
[21] YANG HI,YEH ML,WONG GL,et al. Real-world effectiveness from the Asia Pacific Rim liver consortium for HBV risk score for the prediction of hepatocellular carcinoma in chronic hepatitis B patients treated with oral antiviral therapy[J]. J Infect Dis,2020,221(3):389-399.
|
|
[22] WU S,KONG Y,PIAO H,et al. On-treatment changes of liver stiffness at week 26 could predict 2-year clinical outcomes in HBV-related compensated cirrhosis[J]. Liver Int,2018,38(6):1045-1054.
|
|
[23] KONG YY,SUN YM,ZHOU JL,et al. Early steep decline of liver stiffness predicts histological reversal of fibrosis in chronic hepatitis B patients treated with entecavir[J]. J Viral Hepat,2019,26:576-585.
|
|
[24] ALBA AC,AGORITSAS T,WALSH M,et al. Discrimination and calibration of clinical prediction models:Users’Guides to the medical literature[J]. JAMA,2017,318(14):1377-1384.
|
|
[25] KAPPEN TH,van KLEI WA,van WOLFSWINKEL,et al. Evaluating the impact of predicton models:Lessons learned,challenges,and recommendations[J]. Diagn Progn Res,2018,2:11.
|
|
[26] COLLINS GS,REITSMA JB,ALTMAN DG,et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD):The TRIPOD statement[J]. BMJ,2015,350:g7594.
|
|
[27] SUN YM,ZHOU JL,WANG L,et al. New classification of liver biopsy assessment for fibrosis in chronic hepatitis B patients before and after treatment[J]. Hepatology,2017,65(5):1438-1450.
|
|
[28] D’AMICO G,ABRALDES JG,REBORA P,et al. Ordinal outcomes are superior to binary outcomes for designing and evaluating clinical trials in compensated cirrhosis[J]. Hepatology,2019.[Online ahead of print]
|
|
[29] WOLFF RF,MOONS KGM,RILEY RD,et al. PROBAST:A tool to assess the risk of bias and applicability of prediction model studies[J]. Ann Intern Med,2019,170:51-58.
|
DownLoad: