Review of analytical methods for prospective cohort studies using time to event data: single studies and implications for meta-analysis
| Autor: | Derrick A Bennett |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Statistics and Probability
medicine.medical_specialty Epidemiology MEDLINE 01 natural sciences law.invention Cohort Studies 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Meta-Analysis as Topic Health Information Management Randomized controlled trial law medicine Humans Prospective Studies 030212 general & internal medicine 0101 mathematics Prospective cohort study Proportional Hazards Models Management science business.industry Causality Data science Epidemiologic Studies Logistic Models Meta-analysis business Cohort study |
| Zdroj: | Statistical Methods in Medical Research. 12:297-319 |
| ISSN: | 1477-0334 0962-2802 |
| Popis: | Prospective cohort studies are extremely important in epidemiological research as they give direct information on the sequence of events, which can be used to demonstrate causality. They also have the advantage that many diseases can be studied simultaneously. However, they are usually very time consuming and expensive to run. In addition, practitioners of evidence-based medicine prefer to make decisions based on several studies rather than a single study, hence the need for meta-analysis. The use of meta-analyses in order to synthesize the evidence from randomized controlled trials is extremely popular in medicine and is also being utilized increasingly in epidemiology. The statistical methodology for meta-analyses of epidemiological studies is a long way behind in terms of the advances made in the methodology for randomized controlled trials. Numerous methodological issues, particularly in respect to dealing with biases inherent in these types of studies, have made the results of meta-analyses of epidemiological studies that use summary data open to criticism. This review mainly concentrates on analytical methods for prospective cohort studies that have survival outcomes. In addition, the implications for meta-analysis assuming that the analyst has access to individual participant data are also discussed. The approaches are described with respect to underlying theory and assumptions. It is hoped that this review will promote the use of these approaches in meta-analyses conducted in epidemiology as well as providing some directions for future research. |
| Databáze: | OpenAIRE |
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