Outcomes of patients with non-alcoholic fatty liver disease
Authors: Janus Ong, Maria Stepanova, Zobair Younossi
Journal: Journal of Hepatology (2009)

We appreciate Ruhl and Everhart's comment [[1]Ruhl C.E. Everhart J.E. Non-alcoholic fatty liver disease (NAFLD) and mortality.J Hepatol. 2009; 51: 593Abstract Full Text Full Text PDF PubMed Scopus (4) Google Scholar] about our study [[2]Ong J.P. Pitts A. Younossi Z.M. Increased overall mortality and liver-related mortality in nonalcoholic fatty liver disease.J Hepatol. 2008; 49: 608-612Abstract Full Text Full Text PDF PubMed Scopus (500) Google Scholar]. The authors raise two important issues. The first issue is whether NAFLD is associated with adverse outcomes. And, second, what statistical package should be used for the analysis of NHANES-NDI linked database. Over the past decade, a number of studies have consistently shown that a subtype of NAFLD has a potentially progressive course. The data supporting this notion comes from tertiary care medical centers [3Matteoni C.A. Younossi Z.M. Gramlich T. Bopari N. Liu Y.C. McCullough A.J. Nonalcoholic fatty liver disease: a spectrum of clinical and pathological severity.Gastroenterology. 1999; 116: 1413-1419Abstract Full Text Full Text PDF PubMed Scopus (2832) Google Scholar, 4Ekstedt M. Franzen L. Mathiesen U. Thorelius L. Holmqvist M. Bodenmar G. et al.Long-term follow-up of patients with NAFLD and elevated liver enzymes.Hepatology. 2006; 44: 865-873Crossref PubMed Scopus (1831) Google Scholar, 5Rafiq N. Bai C.H. Fang Y. Srishord M. McCullough A. Gramlich T. et al.Long-term follow-up of patients with non-alcoholic fatty liver.Clin Gastro Hepatol. 2009; 7: 234-238Abstract Full Text Full Text PDF PubMed Scopus (589) Google Scholar], paired liver biopsies [6Harrison S.A. Torgerson S. Hayashi P.H. The natural history of nonalcoholic fatty liver disease: a clinical histopathologic study.Am J Gastroenterol. 2003; 98: 2042-2047Crossref PubMed Scopus (418) Google Scholar, 7Fassio E. Alvarez E. Dominguez N. Landeira G. Longo C. Natural history of nonalcoholic steatohepatitis: a longitudinal study of repeat liver biopsies.Hepatology. 2004; 40: 820-826Crossref PubMed Scopus (429) Google Scholar, 8Adams L.A. Sanderson S. Lindor K.D. Angulo P. The histological course of nonalcoholic fatty liver disease: a longitudinal study of 103 patients with sequential liver biopsies.J Hepatol. 2005; 42: 132-138Abstract Full Text Full Text PDF PubMed Scopus (763) Google Scholar] and a community-based study [[9]Adams L.A. Lymp J.F. St. Sauver J. Sanderson S.O. Lindor K.D. Feldstein A. et al.The natural history of nonalcoholic fatty liver disease: a population based cohort study.Gastroenterology. 2005; 129: 113-121Abstract Full Text Full Text PDF PubMed Scopus (2326) Google Scholar]. Additionally, NHANES database has been used by three in dependent groups [2Ong J.P. Pitts A. Younossi Z.M. Increased overall mortality and liver-related mortality in nonalcoholic fatty liver disease.J Hepatol. 2008; 49: 608-612Abstract Full Text Full Text PDF PubMed Scopus (500) Google Scholar, 10Dunn W. Xu R. Wingard D. Rogers C. Angulo P. Younossi Z.M. et al.Suspected nonalcoholic fatty liver disease and mortality risk in a population-based cohort study.Am J Gastroenterol. 2008; 103: 2263-2271Crossref PubMed Scopus (249) Google Scholar]. The first and second studies suggested an increased all cause mortality [[2]Ong J.P. Pitts A. Younossi Z.M. Increased overall mortality and liver-related mortality in nonalcoholic fatty liver disease.J Hepatol. 2008; 49: 608-612Abstract Full Text Full Text PDF PubMed Scopus (500) Google Scholar] and increased all cause mortality only in the 45-54 age group [[10]Dunn W. Xu R. Wingard D. Rogers C. Angulo P. Younossi Z.M. et al.Suspected nonalcoholic fatty liver disease and mortality risk in a population-based cohort study.Am J Gastroenterol. 2008; 103: 2263-2271Crossref PubMed Scopus (249) Google Scholar]. The third study, did not show an increase in mortality [[11]Ruhl C.E. Everhart J.E. Elevated serum alanine aminotransferase and gammaglutamyltransferase and mortality in the United States population.Gastroenterology. 2009; 136: 477-485Abstract Full Text Full Text PDF PubMed Scopus (304) Google Scholar]. We suspect that differences in study design, selection of NAFLD patients, the control cohort, disease definitions as well as strategies for data analysis may explain these differences. Despite this difference, we believe that most of the available evidence supports the notion that at least a subgroup of patients with NAFLD can progress and develop adverse outcomes. The second issue raised by the authors relates to the statistical package for analysis of NHANES data used in different studies [2Ong J.P. Pitts A. Younossi Z.M. Increased overall mortality and liver-related mortality in nonalcoholic fatty liver disease.J Hepatol. 2008; 49: 608-612Abstract Full Text Full Text PDF PubMed Scopus (500) Google Scholar, 3Matteoni C.A. Younossi Z.M. Gramlich T. Bopari N. Liu Y.C. McCullough A.J. Nonalcoholic fatty liver disease: a spectrum of clinical and pathological severity.Gastroenterology. 1999; 116: 1413-1419Abstract Full Text Full Text PDF PubMed Scopus (2832) Google Scholar, 4Ekstedt M. Franzen L. Mathiesen U. Thorelius L. Holmqvist M. Bodenmar G. et al.Long-term follow-up of patients with NAFLD and elevated liver enzymes.Hepatology. 2006; 44: 865-873Crossref PubMed Scopus (1831) Google Scholar, 5Rafiq N. Bai C.H. Fang Y. Srishord M. McCullough A. Gramlich T. et al.Long-term follow-up of patients with non-alcoholic fatty liver.Clin Gastro Hepatol. 2009; 7: 234-238Abstract Full Text Full Text PDF PubMed Scopus (589) Google Scholar, 6Harrison S.A. Torgerson S. Hayashi P.H. The natural history of nonalcoholic fatty liver disease: a clinical histopathologic study.Am J Gastroenterol. 2003; 98: 2042-2047Crossref PubMed Scopus (418) Google Scholar, 7Fassio E. Alvarez E. Dominguez N. Landeira G. Longo C. Natural history of nonalcoholic steatohepatitis: a longitudinal study of repeat liver biopsies.Hepatology. 2004; 40: 820-826Crossref PubMed Scopus (429) Google Scholar, 8Adams L.A. Sanderson S. Lindor K.D. Angulo P. The histological course of nonalcoholic fatty liver disease: a longitudinal study of 103 patients with sequential liver biopsies.J Hepatol. 2005; 42: 132-138Abstract Full Text Full Text PDF PubMed Scopus (763) Google Scholar, 9Adams L.A. Lymp J.F. St. Sauver J. Sanderson S.O. Lindor K.D. Feldstein A. et al.The natural history of nonalcoholic fatty liver disease: a population based cohort study.Gastroenterology. 2005; 129: 113-121Abstract Full Text Full Text PDF PubMed Scopus (2326) Google Scholar, 10Dunn W. Xu R. Wingard D. Rogers C. Angulo P. Younossi Z.M. et al.Suspected nonalcoholic fatty liver disease and mortality risk in a population-based cohort study.Am J Gastroenterol. 2008; 103: 2263-2271Crossref PubMed Scopus (249) Google Scholar, 11Ruhl C.E. Everhart J.E. Elevated serum alanine aminotransferase and gammaglutamyltransferase and mortality in the United States population.Gastroenterology. 2009; 136: 477-485Abstract Full Text Full Text PDF PubMed Scopus (304) Google Scholar]. We do agree with the authors about the complexity of NHANES data analysis. Nevertheless, SAS survey functions, SUDAAN, and STATA are all recommended by CDC for NHANES data analysis (Dec 2005 updates to Analytic Guidelines). Currently, the NHANES tutorial includes instructions for users who prefer to use any of these three statistical tools. However, it is important to emphasize that the sampling analysis of the NHANES requires special attention because of the weighting procedure that is included in order to keep the population's representativeness. While calculations of means for such designs are typically straightforward, variance estimation in a stratified sampling is a tricky procedure because for complex sample surveys, exact mathematical formulas for variance estimates are usually not available. Two methods exist for variance estimation developed for stratified sampling such as NHANES: the Taylor linearization and the replication method. The latter is not implemented in the SAS survey functions. Currently, however, NCHS recommends the use of the Taylor Series Linearization methods for variance estimation in all NHANES surveys. SUDAAN, STATA, and the SAS Survey procedures can be used to obtain variance estimated by this method [[12]Available from: <http://www.cdc.gov/nchs/tutorials/Nhanes/SurveyDesign/VarianceEstimation/intro.htm>Google Scholar]. The difference between SAS survey function and SUDAAN occurs when one wants to calculate confidence intervals or perform statistical tests. For that purpose, one needs not only estimate for means and variances, but also the behavior (the degrees of freedom) for their distributions. Typically, the number of degrees of freedom for statistical tests is related to the number of independent objects included in these tests. There is a known limitation in SAS functions in estimating the degrees of freedom for statistical tests when not all the strata are present in the sub-population of interest (typically, when the sub-population is small): thus, SAS overestimates the degrees of freedom and returns slightly biased confidence intervals. This issue is addressed in the NHANES guidelines and has been considered. Another limitation of SAS is that the calculation of percentiles is not implemented within it; this can be important for some designs. In a more complex analysis such as regression analyses, SAS procedures require additional attention because all but the very last SAS versions (SAS 9.2) do not have the necessary options implemented by default. Specifically, for correct weighting, the domain option should be used in a regression procedure, and this option is not included in the SAS 9.1 and older versions. This can be addressed by downloading the necessary SAS patch. After that, however, the SAS regression procedure is as reliable as SUDAAN's, and the only difference occurs when one wants to calculate confidence intervals – SAS handles the degrees of freedom in a different way and the intervals (though not the estimates themselves) could be slightly different in certain cases. In a recent publication, SAS survey function and SUDAAN were compared [[13]Gossett JM, Jo CH, Simpson PM. US Health and Nutrition: SAS® Survey Procedures and NHANES. In: Proceedings, 31st Annual SAS Users Group International Conference, San Francisco, California. SUGI 31 Paper 140-31; March 26–29, 2006.Google Scholar]. In this study, authors duplicated previously reported SUDAAN calculations using SAS procedures [[13]Gossett JM, Jo CH, Simpson PM. US Health and Nutrition: SAS® Survey Procedures and NHANES. In: Proceedings, 31st Annual SAS Users Group International Conference, San Francisco, California. SUGI 31 Paper 140-31; March 26–29, 2006.Google Scholar]. The resulting output was not significantly different from that of SUDAAN. The authors concluded that the survey functions of SAS could be used for NHANES analysis if a number of additional previously described steps are taken [[13]Gossett JM, Jo CH, Simpson PM. US Health and Nutrition: SAS® Survey Procedures and NHANES. In: Proceedings, 31st Annual SAS Users Group International Conference, San Francisco, California. SUGI 31 Paper 140-31; March 26–29, 2006.Google Scholar]. In conclusion, we agree with Ruhl et al. that analysis of NHANES database requires careful consideration as well as following the appropriate guidelines recommended by NCHS. Furthermore, we agree that when in doubt, both SAS and SUDAAN should be used for the analysis of NHANES data.