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


CONCLUSIONS
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.
Lyman
Gary H
GH
Department of Medicine, University of Rochester, Medical Center, Rochester, New York 14642, USA. gary_lyman@urmc.rochester.edu
Kuderer
Nicole M
NM
D015982:Bias; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D006801:Humans; D016239:MEDLINE; D015201:Meta-Analysis as Topic; D009369:Neoplasms / Q000628:therapy*; D017063:Outcome Assessment, Health Care / Q000379:methods*; D018579:Patient Selection; D012107:Research Design; D016019:Survival Analysis