What is a PMA?

What is a Prospective Meta-Analysis?

The key feature of a prospective meta-analysis (PMA) is that the studies/cohorts are identified and determined to be eligible for inclusion in the meta-analysis, and hypotheses and analyses strategies are specified, before any results of the studies/cohorts related to the PMA research question are known. PMA can help to overcome some of the recognised problems of retrospective meta-analyses.

What is the difference between PMA and a systematic review?

A properly conducted systematic review defines the question to be addressed in advance of the identification of potentially eligible trials. Systematic reviews are by nature, however, retrospective as the trials included are usually identified once they have been completed and the results reported(1, 2). Knowledge of the results may influence:

  • The criteria for study selection;
  • The decision to publish the results of a trial (and hence introduce publication bias to a review);
  • The definition of a systematic review question;
  • The treatments and patients groups evaluated;
  • The outcomes to be assessed in the review.

A PMA is a meta-analysis of studies which were identified, evaluated and determined to be eligible for the meta-analysis before the results of any of those studies became known. PMA can therefore help to overcome some of the recognised problems of retrospective meta-analyses by enabling:

  • Hypotheses to be specified a priori ignorant of the individual trials;
  • Prospective application of selection criteria;
  • A priori statements of intended analyses, including sub-group analyses, to be made before the results of individual trials are known. This avoids potentially unreliable data-dependent emphasis on particular subgroups.

Systematic reviews also depend on the ability of the reviewer to obtain reliable data on all patients for the relevant outcomes, which can be difficult if full information is not reported in the trial publications. As most (but not all) PMA will collect and analyse individual participant data (IPD) they will be able to overcome this problem, with the additional advantage of being able to conduct time-to-event analyses if appropriate. PMA also provide a unique opportunity for standardisation across trials of information required for outcomes and subgroups. For example, the same instruments might be used to measure a particular outcome in all trials. Investigators can then ensure that data collection is carried out in the same way across each trial, using the same instruments and the same definitions.

PMA are an attractive option to clinical trialists who, although appreciating the benefits of single, adequately sized trials, are unable to undertake them(3, 4). It is a method that has been utilised in recent years by trialists in cardiovascular disease(5-7) and childhood leukemia(8, 9). It can be a useful methodology, for example, when large sample sizes are required to ensure adequate power but single, large-scale trials are not feasible. This could be due to local interests preventing participation in a trial when information is perceived to be "lost overseas". An alternative is for investigators to conduct their own study locally, and to collaborate with the investigators of similar studies, arranging for the results to be combined at the completion of each trial (thereby allowing for ongoing, cumulative and prospective meta-analysis). This enables individual investigators to maintain a certain amount of autonomy, and at the same time to plan appropriately for the meta-analysis. Another situation where it may be beneficial, particularly in the absence of mandatory prospective registration of randomised trials, is when 2 or more trials addressing the same clinical question commence and the investigators are ignorant of the existence of the other trial/s. Once similar trials are identified investigators can collaborate (adapting data collection if necessary) and plan prospectively to combine their results in a meta-analysis.


  1. Pogue J, Yusuf S. Overcoming the limitations of current meta-analysis of randomised controlled trials. Lancet 1998; 351: 47-52. [Pubmed] 
  2. Zanchetti A, Mancia G. Searching for information from unreported trials - amnesty for the past and prospective meta-analyses for the future. Journal of Hypertension 1998; 16: 125. [Pubmed]
  3. Simes RJ. Confronting publication bias: a cohort design for meta-analysis. Statistics in Medicine 1987; 6: 11-29. [Pubmed]
  4. Probstfield J, Applegate WB. Prospective meta-analysis: Ahoy! A clinical trial? Journal of the American Geriatrics Society 1995; 43: 452-453. [Pubmed]
  5. Simes RJ. Prospective meta-analysis of cholesterol-lowering studies: the Prospective Pravastatin Pooling (PPP) Project and the Cholesterol Treatment Trialists (CTT) Collaboration. American Journal of Cardiology 1995; 76: 122c-126c. [Pubmed]
  6. Cholesterol Treatment Trialists (CTT) Collaboration. Protocol for a prospective collaborative overview of all current and planned randomized trials of cholesterol treatment regimens. American Journal of Cardiology 1995; 75: 1130-1134. [Pubmed]
  7. World Health Organisation - International Society of Hypertension Blood Pressure Lowering Treatment Trialists' Collaboration. Protocol for prospective collaborative overviews of major randomised trials of blood-pressure-lowering treatments. Journal of Hypertension 1998; 16: 127-137. [Pubmed]
  8. Shuster JJ, Gieser PW. Meta-analysis and prospective meta-analysis in childhood leukemia clinical research. Annals of Oncology 1996; 7: 1009-1014. [Pubmed]
  9. Valsecchi MG, Masera G. A new challenge in clinical research in childhood ALL: the prospective meta-analysis strategy for intergroup collaboration. Annals of Oncology 1996; 7: 1005-1008. [Pubmed]