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Kronik Hepatit B Hastalarında Karaciğer Fibrozisinin On Adet Noninvaziv Metod ile Değerlendirilmesi: Karşılaştırmalı Çalışma

Year 2018, Volume: 4 Issue: 1, 18 - 24, 01.01.2018

Abstract

Amaç: Çalışma kronik hepatit B hastalarında hepatik fi brozisin değerlendirilmesi ve tahmininde noninvaziv metodların değerlendirilmesini amaçlamaktadır. Gereç ve Yöntemler: Çalışmaya, Akdeniz Üniversitesi Tıp Fakültesi Gastroenteroloji Bölümüne 2009-2014 yılları arasında başvuran, invaziv karaciğer biyopsisi yapılmış, 158 KHB’ li hasta dahil edildi. Çalışmamızda, non-invaziv hepatik fi brozis belirteçlerinden literatüre geçmiş Lok indeks, King’ s skoru, CDS Bonacini skoru , Fibro-Q indeks, FİB-4 indeks, HUI modeli, APRI, AAR, Forn’s ve PAPAS indeksleri kullanılmış, çalışmaya alınan hastaların verileri retrospektif olarak taranarak, bu veriler ışığında hastaların invaziv biyopsi skorları ile 10 farklı non-invaziv yöntem karşılaştırılmıştır. Bulgular: Çalışmaya dahil edilen invaziv karaciğer biyopsisi yapılmış158 hastada ortalama yaş 49,39±13,04 saptandı. Hastaların 100'ü erkek %63,3 , 58’ise kadındı %36,7 . 139 %88 hasta HBe Ag negatif, 19 hasta %12 HBe Ag pozitif idi. Çalışmada kullanılan 10 adet noninvaziv metodun her biri için ROC eğrileri oluşturulup İshak fi brozis skorları ile karşılaştırmalı cutt-off değerleri metodlara göre şu şekilde saptandı; AAR = 0,562, Forns indeks = 0,604, FIB-4 indeks = 0,608, PAPAS skoru = 0,565, AP indeks= 0,625, Fibro-Q indeks = 0,589, Kings skoru = 0,590, CDS = 0,598, RPR = 0,614 ve Lok indeks = 0,631.Sonuç: İnceleme sonucunda KHB hasta grubumuzda Lok indeks fi brozis tesbitinde en etkin noninvaziv yöntem olarak saptandı. Lok indeksi etkinlik açısından sırasıyla AP indeks, RPR, FİB-4 ve Forns indeksin izlediği saptandı. HBV DNA düzeyi ile HAİ ve anlamlı fi brozis arasında pozitif korelasyon saptanırken, anlamlı fi brozis ile cinsiyet, HBe Ag ve Hbe Ab arasında istatistiksel olarak korelasyon saptanmadı

References

  • 1. Peng CY, Chien RN, Liaw YF. Hepatitis B virus related decompensated liver cirrhosis; Benefi ts of antiviral therapy. J Hepatol 2012;57:442–50.
  • 2. Wu SD, Wang JY, Li L. Staging of liver fi brosis in chronic hepatitis B patients with a composite predictive model: A comparative study. World J Gastroenterol 2010;16:501–7.
  • 3. Ceylan B, Mete B, Fincanci M, Aslan T, Akkoyunlu Y, Ozguneş N, Colak O, Gunduz A, Senates E, Ozaras R, Inci A, Tabak F. A new model using platelet indices to predict liver fi brosis in patients with chronic hepatitis B infection. Wien Klin Wochenschr 2013;125:453–60.
  • 4. Seto WK1, Lee CF, Lai CL, Ip PP, Fong DY, Fung J, Wong DK, Yuen MF . A new model using routinely available clinical parameters to predict signifi cant liver fi brosis in chronic hepatitis B. Plos One 2011;6:e23077.
  • 5. Chen CJ1, Yang HI, Su J, Jen CL, You SL, Lu SN, Huang GT, Iloeje UH .Risk of hepatocellular carcinoma across a biological gradient of serum hepatitis B virus DNA level. JAMA 2006;295:65–73.
  • 6. Yuen MF1, Yuan HJ, Wong DK, Yuen JC, Wong WM, Chan AO, Wong BC, Lai KC, Lai CL. Prognostic determinants for chronic hepatitis B in Asians: Therapeutic implications. Gut 2005;54:1610–14.
  • 7. Iloeje UH1, Yang HI, Su J, Jen CL, You SL, Chen CJ. Predicting cirrhosis risk based on the level of circulating hepatitis B viral load. Gastroenterology 2006;130:678–86.
  • 8. Zeng MD1, Lu LG, Mao YM, Qiu DK, Li JQ, Wan MB, Chen CW, Wang JY, Cai X, Gao CF, Zhou XQ. Prediction of signifi cant fi brosis in HbeAg-positive patients with chronic hepatitis B by a noninvasive model. Hepatology 2005;42:1437–45.
  • 9. Freidmann SL. Liver fi brosis from bench to bedside. J Hepatol 2003;1:38–53.
  • 10. Hsu CW1, Liang KH, Huang SF, Tsao KC, Yeh CT. Development of a non-invasive fi brosis test for chronic hepatitis B patients and comparison with other unpatented scores. BMC Res Notes 2013;6:212.
  • 11. Afdihal NH, Nunes D. Evaluation of liver fi brosis: A concise review. Am J Gastroenterol 2004;99:1160–74.
  • 12. Ferraioli G, Tinelli C, Malfi tano A, Bello BD. Performance of real-time strain elastography, transient elastography, and aspartate-to-platelet ratio index in the assessment of fi brosis in chronic hepatitis C. Am J Roentgenol 2012;199:19–25.
  • 13. Kim SU1, Lee JH, Kim DY, Ahn SH, Jung KS, Choi EH, Park YN, Han KH, Chon CY, Park JY. Prediction of liver–related events using fi broscan in chronic hepatitis B patients showing advanced liver fi brosis. PloS One 2012;7:e36676.
  • 14. Yoon KT, Lim SM, Park JY, Ahn SH. Liver stiffness measurement using acoustic radiation force impulse (ARFI) elastography and effect of necroinfl ammation. Dig Dis Sci 2012;57:1682–91.
  • 15. Cardoso AC1, Carvalho-Filho RJ, Stern C, Dipumpo A, Giuily N, Ripault MP, Asselah T, Boyer N, Lada O, Castelnau C, Martinot-Peignoux M, Valla DC, Bedossa P, Marcellin P. Direct comparison of diagnostic performance of transient elastography in patients with chronic hepatitis B and chronic hepatitis C. Liver Int 2012;32:612–21.
  • 16. Zhou K, Lu LG. Assessment of fi brosis in chronic liver diseases. J Dig Dis 2009;10:7–14.
  • 17. Baranova A, Lal P, Birerdinc A, Younossi ZM. Non-invasive markers for hepatic fi brosis. BMC gastroenterology 2011;11:91.
  • 18. Grigorescu M. Noninvasive biochemical markers of liver fi brosis. J Gastrointestin Liver Dis 2006;15:149–59.
  • 19. Lok AS1, Ghany MG, Goodman ZD, Wright EC, Everson GT, Sterling RK, Everhart JE, Lindsay KL, Bonkovsky HL, Di Bisceglie AM, Lee WM, Morgan TR, Dienstag JL, Morishima C. Predicting cirrhosis in patients with hepatitis C based on standard laboratory tests: Results of the HALT-C cohort. Hepatology. 2005;42:282-92.
  • 20. Ma J, Jiang Y, Gong G. Evaluation of seven noninvasive models in staging liver fi brosis in patients with chronic hepatitis B virus infection. Eur J Gastroenterol Hepatol 2013;25:428–34.
  • 21. Shin WG1, Park SH, Jang MK, Hahn TH, Kim JB, Lee MS, Kim DJ, Jun SY, Park CK. Aspartate aminotransferase to platelet ratio index (APRI) can predict liver fi brosis in chronic hepatitis B. Dig Liver Dis 2008;40:267–74.
  • 22. Wu SD, Wang JY, Li L. Staging of liver fi brosis in chronic hepatitis B patients with a composite predictive model: A comparative study. World J Gastroenterol 2010;16:501–7.
  • 23. Zhou K1, Gao CF, Zhao YP, Liu HL, Zheng RD, Xian JC, Xu HT, Mao YM, Zeng MD, Lu LG. Simpler score of routine laboratory tests predicts liver fi brosis in patients with chronic hepatitis B. J Gastroenterol Hepatol 2010;25:1569–77.
  • 24. Wai CT, Cheng CL, Wee A, Dan YY, Chan E, Chua W, Mak B, Oo AM, Lim SG. Non-invasive models for predicting histology in patients with chronic hepatitis B. Liver Int 2006;26:666–72.
  • 25. McGary CT, Raja RH, Weigel PH. Endocytosis of hyaluronic acid by rat liver endothelial cells. Evidence for receptor recycling. Biochem J 1989;257:875–84.
  • 26. Kawser CA, Iredale JP, Winwood PJ, Arthur MJ. Rat hepatic stellate cell expression of α2-macroglobulin is a feature of cellular activation: Implications for matrix remodelling in hepatic fi brosis. Clin Sci 1998;95:179–86.
  • 27. Zeng MD1, Lu LG, Mao YM, Qiu DK, Li JQ, Wan MB, Chen CW, Wang JY, Cai X, Gao CF, Zhou XQ. Prediction of signifi cant fi brosis in HBeAg-positive patients with chronic hepatitis B by a noninvasive model. Hepatology 2005;42:1437–45.
  • 28. McHutchison JG1, Blatt LM, de Medina M, Craig JR, Conrad A, Schiff ER, Tong MJ. Measurement of serum hyaluronic acid in patients with chronic hepatitis C and its relationship to liver histology. J Gastroenterol Hepatol 2000;15:945–51.
  • 29. Myers RP1, Tainturier MH, Ratziu V, Piton A, Thibault V, Imbert-Bismut F, Messous D, Charlotte F, Di Martino V, Benhamou Y, Poynard T. Prediction of liver histological lesions with biochemical markers in patients with chronic hepatitis B. J Hepatol 2003;39:222–30.

Evaluation of Liver Fibrosis by Ten Noninvasive Methods in Evaluation of Liver Fibrosis by Ten Noninvasive Methods in Patients with Chronic Hepatitis B: A Comparative Study Patients with Chronic Hepatitis B: A Comparative Study

Year 2018, Volume: 4 Issue: 1, 18 - 24, 01.01.2018

Abstract

Objective: This study aims to evaluate the predictive value of noninvasive serum markers of hepatic fi brosis in patients with chronic hepatitis B.Material and Methods: This study involved 158 patients with chronic hepatitis B. Noninvasive markers used were as follows; aspartate transaminase AST to alanine transaminase ALT ratio AAR , fi brosis-4 FIB-4 index, age-platelet index AP , Forns index, cirrhosis discriminant score CDS , Kings score, Fibro-Q index, PAPAS score, Lok index and red cell distribution width to platelet ratio RPR . Concurrent liver biopsy specimens were evaluated with the Ishak scoring system. Patients were divided into two groups, those with signifi cant fi brosis Ishak fi brosis score F ≥ 3 and those without Ishak fi brosis score F ≤ 2 . Receiver operating characteristic ROC curve analyses were carried out to compare the results of the noninvasive markers in the two groups.Results: Of the 158 patients evaluated mean age 49.39 ± 13.04, 100 males [63.3%], 58 females [36,7%] , 139 88% were HBe Ag negative and HBe Ab positive and 19 %12 were HBe Ag positive and HBe Ab negative.ROC curve analyses with the Ishak fi brosis score had cutoff values as follows: AAR = 0.562, Forns index = 0.604, FIB-4 index = 0.608, PAPAS score = 0.565, AP index = 0.625, Fibro-Q index = 0.589, Kings score = 0.590, CDS = 0.598, RPR = 0.614 and Lok index = 0.631. Conclusion: The Lok index was found to be the most effective noninvasive method for estimating hepatic fi brosis. The AP index, RPR, Forns index and FIB-4 index were also effective models in our study

References

  • 1. Peng CY, Chien RN, Liaw YF. Hepatitis B virus related decompensated liver cirrhosis; Benefi ts of antiviral therapy. J Hepatol 2012;57:442–50.
  • 2. Wu SD, Wang JY, Li L. Staging of liver fi brosis in chronic hepatitis B patients with a composite predictive model: A comparative study. World J Gastroenterol 2010;16:501–7.
  • 3. Ceylan B, Mete B, Fincanci M, Aslan T, Akkoyunlu Y, Ozguneş N, Colak O, Gunduz A, Senates E, Ozaras R, Inci A, Tabak F. A new model using platelet indices to predict liver fi brosis in patients with chronic hepatitis B infection. Wien Klin Wochenschr 2013;125:453–60.
  • 4. Seto WK1, Lee CF, Lai CL, Ip PP, Fong DY, Fung J, Wong DK, Yuen MF . A new model using routinely available clinical parameters to predict signifi cant liver fi brosis in chronic hepatitis B. Plos One 2011;6:e23077.
  • 5. Chen CJ1, Yang HI, Su J, Jen CL, You SL, Lu SN, Huang GT, Iloeje UH .Risk of hepatocellular carcinoma across a biological gradient of serum hepatitis B virus DNA level. JAMA 2006;295:65–73.
  • 6. Yuen MF1, Yuan HJ, Wong DK, Yuen JC, Wong WM, Chan AO, Wong BC, Lai KC, Lai CL. Prognostic determinants for chronic hepatitis B in Asians: Therapeutic implications. Gut 2005;54:1610–14.
  • 7. Iloeje UH1, Yang HI, Su J, Jen CL, You SL, Chen CJ. Predicting cirrhosis risk based on the level of circulating hepatitis B viral load. Gastroenterology 2006;130:678–86.
  • 8. Zeng MD1, Lu LG, Mao YM, Qiu DK, Li JQ, Wan MB, Chen CW, Wang JY, Cai X, Gao CF, Zhou XQ. Prediction of signifi cant fi brosis in HbeAg-positive patients with chronic hepatitis B by a noninvasive model. Hepatology 2005;42:1437–45.
  • 9. Freidmann SL. Liver fi brosis from bench to bedside. J Hepatol 2003;1:38–53.
  • 10. Hsu CW1, Liang KH, Huang SF, Tsao KC, Yeh CT. Development of a non-invasive fi brosis test for chronic hepatitis B patients and comparison with other unpatented scores. BMC Res Notes 2013;6:212.
  • 11. Afdihal NH, Nunes D. Evaluation of liver fi brosis: A concise review. Am J Gastroenterol 2004;99:1160–74.
  • 12. Ferraioli G, Tinelli C, Malfi tano A, Bello BD. Performance of real-time strain elastography, transient elastography, and aspartate-to-platelet ratio index in the assessment of fi brosis in chronic hepatitis C. Am J Roentgenol 2012;199:19–25.
  • 13. Kim SU1, Lee JH, Kim DY, Ahn SH, Jung KS, Choi EH, Park YN, Han KH, Chon CY, Park JY. Prediction of liver–related events using fi broscan in chronic hepatitis B patients showing advanced liver fi brosis. PloS One 2012;7:e36676.
  • 14. Yoon KT, Lim SM, Park JY, Ahn SH. Liver stiffness measurement using acoustic radiation force impulse (ARFI) elastography and effect of necroinfl ammation. Dig Dis Sci 2012;57:1682–91.
  • 15. Cardoso AC1, Carvalho-Filho RJ, Stern C, Dipumpo A, Giuily N, Ripault MP, Asselah T, Boyer N, Lada O, Castelnau C, Martinot-Peignoux M, Valla DC, Bedossa P, Marcellin P. Direct comparison of diagnostic performance of transient elastography in patients with chronic hepatitis B and chronic hepatitis C. Liver Int 2012;32:612–21.
  • 16. Zhou K, Lu LG. Assessment of fi brosis in chronic liver diseases. J Dig Dis 2009;10:7–14.
  • 17. Baranova A, Lal P, Birerdinc A, Younossi ZM. Non-invasive markers for hepatic fi brosis. BMC gastroenterology 2011;11:91.
  • 18. Grigorescu M. Noninvasive biochemical markers of liver fi brosis. J Gastrointestin Liver Dis 2006;15:149–59.
  • 19. Lok AS1, Ghany MG, Goodman ZD, Wright EC, Everson GT, Sterling RK, Everhart JE, Lindsay KL, Bonkovsky HL, Di Bisceglie AM, Lee WM, Morgan TR, Dienstag JL, Morishima C. Predicting cirrhosis in patients with hepatitis C based on standard laboratory tests: Results of the HALT-C cohort. Hepatology. 2005;42:282-92.
  • 20. Ma J, Jiang Y, Gong G. Evaluation of seven noninvasive models in staging liver fi brosis in patients with chronic hepatitis B virus infection. Eur J Gastroenterol Hepatol 2013;25:428–34.
  • 21. Shin WG1, Park SH, Jang MK, Hahn TH, Kim JB, Lee MS, Kim DJ, Jun SY, Park CK. Aspartate aminotransferase to platelet ratio index (APRI) can predict liver fi brosis in chronic hepatitis B. Dig Liver Dis 2008;40:267–74.
  • 22. Wu SD, Wang JY, Li L. Staging of liver fi brosis in chronic hepatitis B patients with a composite predictive model: A comparative study. World J Gastroenterol 2010;16:501–7.
  • 23. Zhou K1, Gao CF, Zhao YP, Liu HL, Zheng RD, Xian JC, Xu HT, Mao YM, Zeng MD, Lu LG. Simpler score of routine laboratory tests predicts liver fi brosis in patients with chronic hepatitis B. J Gastroenterol Hepatol 2010;25:1569–77.
  • 24. Wai CT, Cheng CL, Wee A, Dan YY, Chan E, Chua W, Mak B, Oo AM, Lim SG. Non-invasive models for predicting histology in patients with chronic hepatitis B. Liver Int 2006;26:666–72.
  • 25. McGary CT, Raja RH, Weigel PH. Endocytosis of hyaluronic acid by rat liver endothelial cells. Evidence for receptor recycling. Biochem J 1989;257:875–84.
  • 26. Kawser CA, Iredale JP, Winwood PJ, Arthur MJ. Rat hepatic stellate cell expression of α2-macroglobulin is a feature of cellular activation: Implications for matrix remodelling in hepatic fi brosis. Clin Sci 1998;95:179–86.
  • 27. Zeng MD1, Lu LG, Mao YM, Qiu DK, Li JQ, Wan MB, Chen CW, Wang JY, Cai X, Gao CF, Zhou XQ. Prediction of signifi cant fi brosis in HBeAg-positive patients with chronic hepatitis B by a noninvasive model. Hepatology 2005;42:1437–45.
  • 28. McHutchison JG1, Blatt LM, de Medina M, Craig JR, Conrad A, Schiff ER, Tong MJ. Measurement of serum hyaluronic acid in patients with chronic hepatitis C and its relationship to liver histology. J Gastroenterol Hepatol 2000;15:945–51.
  • 29. Myers RP1, Tainturier MH, Ratziu V, Piton A, Thibault V, Imbert-Bismut F, Messous D, Charlotte F, Di Martino V, Benhamou Y, Poynard T. Prediction of liver histological lesions with biochemical markers in patients with chronic hepatitis B. J Hepatol 2003;39:222–30.
There are 29 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Tolga Şahin This is me

İnci Süleymanlar This is me

Publication Date January 1, 2018
Published in Issue Year 2018 Volume: 4 Issue: 1

Cite

Vancouver Şahin T, Süleymanlar İ. Kronik Hepatit B Hastalarında Karaciğer Fibrozisinin On Adet Noninvaziv Metod ile Değerlendirilmesi: Karşılaştırmalı Çalışma. Akd Med J. 2018;4(1):18-24.