Download PDF
Semin Reprod Med 2003; 21(1): 073-084
DOI: 10.1055/s-2003-39997
Copyright © 2003 by Thieme Medical Publishers, Inc., 333 Seventh Avenue, New York, NY 10001, USA. Tel.: +1(212) 584-4662

Characteristics of Good Causation Studies

Salim Daya
  • Departments of Obstetrics and Gynaecology, and Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
Further Information

Publication History

Publication Date:
12 June 2003 (online)

    Permissions and Reprints

ABSTRACT

The study of causal relationships is important when addressing questions of efficacy of treatment interventions and etiology of disease. The evaluation of a cause-and-effect relationship between exposure to a putative causal factor and outcome can be undertaken using a variety of study designs including randomized controlled trial and cohort and case control studies. Study participants should be selected in a manner that minimizes bias and confounding and is representative of the target population. Confounding can be controlled by using several strategies including restriction, randomization, stratification, matching, and multivariable analyses. The degree of association is then summarized by the relative risk for prospective studies and the odds ratio for retrospective studies. The precision of these estimates should be indicated by providing their confidence intervals. Important indicators of causation are correct temporal and dose-response relationships between exposure and outcome, a large magnitude in the strength of association, and consistency and specificity of association. Biological and epidemiological sensibility and analogy to other well-established relationships provide additional support for a causal hypothesis.

KEYWORDS

Cause and effect relationship - case-control study - diagnostic tests for causation - bias and confounding - odds ratios and relative risks

REFERENCES

  • 1 Elwood M. Critical Appraisal of Epidemiological Studies and Clinical Trials. Oxford: Oxford Medical Publications 1998
    Google Scholar
  • 2 Daya S. Infertility trials and study design. In: Templeton AP, O'Brien PMS, eds. Evidence-Based Fertility Treatment London: RCOG Press 1998: 65-86
    Google Scholar
  • 3 Daya S. The two-by-two table.  Evidence-Based Obstet Gynecol . 2000;  2 33-34
    PubMedGoogle Scholar
  • 4 Levine M, Walter S, Lee H, Haines T, Holbrook A, Moyer V, for the Evidence-Based Medicine Working Group. Users' guide to the medical literature IV: how to use an article about harm.  JAMA . 1994;  271 1615-1619
    PubMedGoogle Scholar
  • 5 Daya S. Fertility drugs and ovarian cancer. In: Coutinho EM, Spinola P, eds. Reproductive Medicine: A Millennium Review London: Parthenon Publishing 1999: 45-48
    Google Scholar
      >