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Int J Epidemiol. 2007 Jun;36(3):666-76. Epub 2007 Apr 30.

Tools for assessing quality and susceptibility to bias in observational studies in epidemiology: a systematic review and annotated bibliography.

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  • 1Primary Care Genetics, General Practice and Primary Care Research Unit, University of Cambridge and Public Health Genetics Unit, Strangeways Research Labs, Worts Causeway, Cambridge, UK. simon.sanderson@sri.cam.ac.uk

Abstract

BACKGROUND:

Assessing quality and susceptibility to bias is essential when interpreting primary research and conducting systematic reviews and meta-analyses. Tools for assessing quality in clinical trials are well-described but much less attention has been given to similar tools for observational epidemiological studies.

METHODS:

Tools were identified from a search of three electronic databases, bibliographies and an Internet search using Google. Two reviewers extracted data using a pre-piloted extraction form and strict inclusion criteria. Tool content was evaluated for domains potentially related to bias and was informed by the STROBE guidelines for reporting observational epidemiological studies.

RESULTS:

A total of 86 tools were reviewed, comprising 41 simple checklists, 12 checklists with additional summary judgements and 33 scales. The number of items ranged from 3 to 36 (mean 13.7). One-third of tools were designed for single use in a specific review and one-third for critical appraisal. Half of the tools provided development details, although most were proposed for future use in other contexts. Most tools included items for selection methods (92%), measurement of study variables (86%), design-specific sources of bias (86%), control of confounding (78%) and use of statistics (78%); only 4% addressed conflict of interest. The distribution and weighting of domains across tools was variable and inconsistent.

CONCLUSION:

A number of useful assessment tools have been identified by this report. Tools should be rigorously developed, evidence-based, valid, reliable and easy to use. There is a need to agree on critical elements for assessing susceptibility to bias in observational epidemiology and to develop appropriate evaluation tools.

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PMID:
17470488
[PubMed - indexed for MEDLINE]
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