21
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The strengths and limitations of meta-analyses based on aggregate data

      research-article
      1 , , 1
      BMC Medical Research Methodology
      BioMed Central

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Properly performed systematic reviews and meta-analyses are thought by many to represent among the highest level of evidence addressing important clinical issues. Few would disagree that meta-analyses based on individual patient data (IPD) offer several advantages and represent the standard to which all other systematic reviews should be compared.

          Methods

          All cancer-related meta-analyses cited in Medline were classified as based on aggregate or individual patient data. A review was then undertaken of all reports comparing the comparative strengths and limitations of meta-analyses using either aggregate or individual patient data.

          Results

          The majority of published meta-analyses are based on summary or aggregate patient data (APD). Reasons suggested for this include the considerable resources, years of study and often, broad international cooperation required for IPD meta-analyses. Many of the most important features of systematic reviews including formal meta-analyses are addressed by both IPD and APD meta-analyses. The need for defining an explicit and relevant clinical question, exhaustively searching for the totality of evidence, meticulous and unbiased data transfer or extraction, assessment of between study heterogeneity and the use of appropriate statistical methods for estimating summary effect measures are essentially the same for the two approaches.

          Conclusion

          IPD offers advantages and, when feasible, should be considered the best opportunity to summarize the results of multiple studies. However, the resources, time and cooperation required for such studies will continue to limit their use in many important areas of clinical medicine which can be meaningfully and cost-effectively approached by properly performed APD meta-analyses. APD meta-analyses continue to be the mainstay of systematic reviews utilized by the US Preventive Services Task Force, the Cochrane Collaboration and many professional societies to support clinical practice guidelines.

          Related collections

          Most cited references22

          • Record: found
          • Abstract: found
          • Article: not found

          Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints.

          Meta-analyses aim to provide a full and comprehensive summary of related studies which have addressed a similar question. When the studies involve time to event (survival-type) data the most appropriate statistics to use are the log hazard ratio and its variance. However, these are not always explicitly presented for each study. In this paper a number of methods of extracting estimates of these statistics in a variety of situations are presented. Use of these methods should improve the efficiency and reliability of meta-analyses of the published literature with survival-type endpoints.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Individual patient- versus group-level data meta-regressions for the investigation of treatment effect modifiers: ecological bias rears its ugly head.

            When performing a meta-analysis, interest often centres on finding explanations for heterogeneity in the data, rather than on producing a single summary estimate. Such exploratory analyses are frequently undertaken with published, study-level data, using techniques of meta-analytic regression. Our goal was to explore a real-world example for which both published, group-level and individual patient-level data were available, and to compare the substantive conclusions reached by both methods. We studied the benefits of anti-lymphocyte antibody induction therapy among renal transplant patients in five randomized trials, focusing on whether there are subgroups of patients in whom therapy might prove particularly beneficial. Allograft failure within 5 years was the endpoint studied. We used a variety of analytic approaches to the group-level data, including weighted least-squares regression (N=5 studies), logistic regression (N=628, the total number of subjects), and a hierarchical Bayesian approach. We fit logistic regression models to the patient-level data. In the patient-level analysis, we found that treatment was significantly more effective among patients with elevated (20 per cent or more) panel reactive antibodies (PRA) than among patients without elevated PRA. These patients comprise a small (about 15 per cent of patients) subgroup of patients that benefited from therapy. The group-level analyses failed to detect this interaction. We recommend using individual patient data, when feasible, to study patient characteristics, in order to avoid the potential for ecological bias introduced by group-level analyses. Copyright 2002 John Wiley & Sons, Ltd.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Meta-analysis of the literature or of individual patient data: is there a difference?

              The use of meta-analyses or overviews to combine formally the results of related randomised clinical trials is becoming increasingly common. However the distinction between analyses based on information extracted from the published literature and those based on collecting and reanalysing updated individual patient data is not clear. We have investigated the difference between meta-analysis of the literature (MAL) and meta-analysis of individual patient data (MAP) by comparing the two approaches using randomised trials of cisplatin-based therapy in ovarian cancer. The MAL was based on 788 patients and the MAP on 1329 and estimated median follow-ups were 3.5 and 6.5 years, respectively. The MAL gave a result of greater statistical significance (p = 0.027 vs p = 0.30) and an estimate of absolute treatment effect three times as large as the MAP (7.5% vs 2.5%). Publication bias, patient exclusion, length of follow-up, and method of analysis all contributed to this observed difference. The results of a meta-analysis of the literature alone may be misleading. Whenever possible, a meta-analysis of updated individual patient data should be done because this provides the least biased and most reliable means of addressing questions that have not been satisfactorily resolved by individual clinical trials.
                Bookmark

                Author and article information

                Journal
                BMC Med Res Methodol
                BMC Medical Research Methodology
                BioMed Central (London )
                1471-2288
                2005
                25 April 2005
                : 5
                : 14
                Affiliations
                [1 ]Department of Medicine University of Rochester Medical Center Rochester, New York 14642 USA
                Article
                1471-2288-5-14
                10.1186/1471-2288-5-14
                1097735
                15850485
                47032009-c9cf-4ffc-840c-5830b029bf5e
                Copyright © 2005 Lyman and Kuderer; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 3 January 2005
                : 25 April 2005
                Categories
                Research Article

                Medicine
                Medicine

                Comments

                Comment on this article