The paired availability design for historical controls

被引：19

作者：

Baker S.G. ^{[1
]}

Lindeman K.S. ^{[2
]}

Kramer B.S. ^{[3
]}

机构：

[1] Division of Cancer Prevention, National Cancer Institute, Bethesda, MD

[2] Department of Anesthesiology, Johns Hopkins Medical Institutions, Baltimore, MD

[3] Off. Dis. Prev./Med. Applic. of Res., National Institutes of Health, Bethesda, MD

来源：

BMC Medical Research Methodology | / 1卷 / 1期

关键词：

Cesarean Section; Propensity Score; Medical Center; Epidural Analgesia; Unbiased Estimate;

D O I：

10.1186/1471-2288-1-9

中图分类号：

学科分类号：

摘要：

Background: Although a randomized trial represents the most rigorous method of evaluating a medical intervention, some interventions would be extremely difficult to evaluate using this study design. One alternative, an observational cohort study, can give biased results if it is not possible to adjust for all relevant risk factors. Methods: A recently developed and less well-known alternative is the paired availability design for historical controls. The paired availability design requires at least 10 hospitals or medical centers in which there is a change in the availability of the medical intervention. The statistical analysis involves a weighted average of a simple "before" versus "after" comparison from each hospital or medical center that adjusts for the change in availability. Results: We expanded requirements for the paired availability design to yield valid inference. (1) The hospitals or medical centers serve a stable population. (2) Other aspects of patient management remain constant over time. (3) Criteria for outcome evaluation are constant over time. (4) Patient preferences for the medical intervention are constant over time. (5) For hospitals where the intervention was available in the "before" group, a change in availability in the "after group" does not change the effect of the intervention on outcome. Conclusion: The paired availability design has promise for evaluating medical versus surgical interventions, in which it is difficult to recruit patients to a randomized trial.

引用

页码：1 / 7

页数：6

共 20 条

[1]

Concato J., Feinstein A.R., Holford T.R., The risk of determining risk with multivariable models, Ann Intern Med, 118, pp. 201-210, (1993)

[2]

Rubin D.B., Estimating causal effects from large data sets using propensity scores, Ann Intern Med, 27, pp. 757-763, (1997)

[3]

Concato J., Shah H., Horwitz R.I., Randomized controlled trials, observational studies, and the hierarchy of research designs, N Engl J Med, 342, pp. 1887-1892, (2000)

[4]

Benson K., Hartz A.J., A comparison of observational and randomized, controlled trials, N Engl J Med, 342, pp. 1878-1886, (2000)

[5]

Baker S.G., Lindeman K.S., Randomized and nonrandomized studies. Statistical considerations, Anesthesiology, 92, pp. 928-930, (2000)

[6]

Egger M., Schneider M., Smith G.D., Spurious precision? Meta-analysis of observational studies, Br Med J, 316, pp. 140-144, (1998)

[7]

Jha P., Flather M., Lonn E., Farkouh M., Yusuf S., The antioxidant vitamins and cardiovascular disease. A critical review of epidemiologic and clinical trials data, Ann Intern Med, 123, pp. 860-872, (1995)

[8]

Grady D., Hulley S.B., Hormones to prevent coronary disease in women: When are observational studies adequate evidence?, Ann Intern Med, 133, pp. 999-1001, (2000)

[9]

Baker S.G., Lindeman K.S., Rethinking historical controls, Biostatistics, (2001)

[10]

Smith R.P., Meier P., Observational studies and randomized trials, New Engl J Med, 343, (2000)

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