Effects of CCR5-Δ 32, CCR2-64I, and SDF-1 3′A Alleles on HIV-1 Disease Progression: An International Meta-Analysis of Individual-Patient Data
Ioannidis, J.P.A., Rosenberg, P.S., Goedert, J.J., Ashton, L.J., Benfield, T.L., Buchbinder, S.P., Coutinho, R.A., Eugen-Olsen, J., Gallart, T., Katzenstein, T.L., Kostrikis, L.G., Kuipers, H., Louie, L.G., Mallal, S.A., Margolick, J.B., Martinez, O.P., Meyer, L., Michael, N.L., Operskalski, E., Pantaleo, G., Rizzardi, G.P., Schuitemaker, H., Sheppard, H.W., Stewart, G.J., Theodorou, I.D., Ullum, H., Vicenzi, E., Vlahov, D., Wilkinson, D., Workman, C., Zagury, J-F and O'Brien, T.R. (2001) Effects of CCR5-Δ 32, CCR2-64I, and SDF-1 3′A Alleles on HIV-1 Disease Progression: An International Meta-Analysis of Individual-Patient Data. Annals of Internal Medicine, 135 (9). pp. 782-795.
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The burgeoning information on the human genome creates opportunities and challenges for studies of disease associations. Because genetic differences often produce modest effects, many patients must be studied to reach definitive conclusions. In the absence of a single large study, meta-analysis of individual-patient data (1 - 3) from smaller studies offers a way to assemble an adequate sample size. This approach is based on a unifying protocol that has standardized analytic definitions. When the protocol is applied to data contributed by most investigators working in a field, this method can provide more convincing results than a simple pooling of data or a meta-analysis of published reports (3). A meta-analysis of individual-patient data is also superior to a meta-analysis of published reports for examining differences in reported results.
|Publication Type:||Journal Article|
|Murdoch Affiliation:||Centre for Clinical Immunology and Biomedical Statistics|
|Publisher:||American College of Physicians|
|Copyright:||2001 American College of Physicians/American Society of Internal Medicine|
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