Meta‐analysis in albumin dialysis: Are we really ready for it?

Worldwide, approximately 10,000 liver transplant procedures are performed each year. In actuality, when comparing procedures performed vs. the actual demand of procedures needed, the difference between the two numbers is quite sobering. The multidisciplinary group composed of hepatologists, intensivists, and liver transplant surgeons, commonly referred to as “the Liver Community,” is continually searching for the ideal solution to satisfy the ever-growing number of actual liver transplants needed. They face two major challenges in their search where supply does not equal demand: (1) to increase the availability of liver transplants or alternatively use “long-term” treatment options, and (2) to develop treatment options that stabilize the patients suffering from liver failure to give them the opportunity to reach the point where the permanent solutions can be applied. To meet the first demand, the Liver Community is exploring long-term options such as splitting livers and living donations, as well as slightly more experimental approaches, including non–heart beating donations and liver (or stem) cell transplantations for in vitro hepatic tissue construction. While scientists move forward in their research, the Community is working together as a whole in gathering any and all available data on using liver support as a survival bridge to the available long-term options for patients in need of liver transplants. Numerous small studies have lead to attempts at using meta-analysis to give a clear statement about survival and liver support.1 The authors of the article “Molecular Absorbent Recirculating System (MARS) for Acute and Acute-on-Chronic Liver Failure: A Meta-Analysis” in this issue of Liver Transplantation use meta-analysis to analyze the success of liver support.2 The authors of the present meta-analysis combined two prospective randomized controlled trials in chronic liver disease with hepatorenal syndrome type I and alcoholic hepatitis that were pooled with two prospective controlled trials in acute liver failure and postcardiogenic shock–induced liver failure, as well as two controlled nonrandomized studies (one retrospective, one crossover) in chronic liver disease with superimposed (mixed) complications and exacerbated hepatitis B. The four randomized trials pooled together provided a total of 67 patients to analyze, with 36 patients receiving MARS and 31 patients receiving conventional treatment. Those patients with conventional treatment had a 67.7% mortality compared to the MARS patients, who had a 33.3% mortality. At first glance, the survival rate looks favorable toward MARS. However, the confidence intervals were too large to render the data significant to the relative risk reduction using the meta-analysis program. Thus, the question asked by Patrick Kamath in an editorial of Hepatology remains open: “Is there Life in Mars? ”3 As stated by the authors, there are severe problems with their meta-analysis that leave the answer to this question to the larger studies that are on their way. First, as indicated by the authors of the present article, the total numbers of patients enrolled in the study were too small to support meta-analysis. Furthermore, the tremendous difference in primary indication, primary endpoint and treatment protocols for intervention and standard treatment make a clean pooling impossible. The Community would most likely agree that even if only looking at survival using standard of care, it would be difficult to compare the different etiologies presented in the present article. The real question is: If these groups are not comparable without using liver support, how can they be compared when adding the factor of liver support? The answer is simple: They cannot. Even with the valiant attempt of the authors to achieve a conclusive answer, and knowing the Community may be hungry for this answer, there is just not enough meat on the bone. Attempting to use meta-analysis tools before there is sufficient data can lead to false assumptions, whether positive or negative. Until there are sufficient random-