Catalogo Articoli (Spogli Riviste)

OPAC HELP

Titolo:
Sample size calculations for risk equivalence testing in pharmacoepidemiology
Autore:
Tubert-Bitter, P; Manfredi, R; Lellouch, J; Begaud, B;
Indirizzi:
INSERM, U472, F-94807 Villejuif, France INSERM Villejuif France F-94807INSERM, U472, F-94807 Villejuif, France Univ Bordeaux 2, Dept Pharmacol, F-33076 Bordeaux, France Univ Bordeaux 2Bordeaux France F-33076 rmacol, F-33076 Bordeaux, France
Titolo Testata:
JOURNAL OF CLINICAL EPIDEMIOLOGY
fascicolo: 12, volume: 53, anno: 2000,
pagine: 1268 - 1274
SICI:
0895-4356(200012)53:12<1268:SSCFRE>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
NULL HYPOTHESIS; RELATIVE RISK; TRIALS; POWER;
Keywords:
pharmacoepidemiology; cohort studies; equivalence; sample size; adverse drug reactions; risk comparison;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Life Sciences
Citazioni:
18
Recensione:
Indirizzi per estratti:
Indirizzo: Tubert-Bitter, P INSERM, U472, 16 Ave Paul Vaillant Couturier, F-94807 Villejuif, France INSERM 16 Ave Paul Vaillant Couturier Villejuif France F-94807
Citazione:
P. Tubert-Bitter et al., "Sample size calculations for risk equivalence testing in pharmacoepidemiology", J CLIN EPID, 53(12), 2000, pp. 1268-1274

Abstract

Equivalence testing has been widely discussed and is commonly used in pharmacokinetics (bioequivalence) and clinical trials (therapeutic equivalence). It can also be applied to pharmacoepidemiology, where the aim may be to test with a known risk (one-group design) or with another drug (two-group design). Whether the approach is two-sided or one-sided, predefined equivalence limits are required. The definition of the equivalence region can be based on either risk difference or risk ratio. Risk equivalence resting is complicated by the binary nature of the outcome, its low frequency, and by theabsence of commonly defined equivalence limits for differences or ratios. In this context, we consider usable formulae for sample sizes. In most cases, at least when the risk studied is large enough (above 1/1,000), it appears that these formulae result in sample sizes that may be acceptable for practical purposes. For example, demonstrating equivalence with a known risk of 0.01, a 20% maximal risk difference, and a one-sided test (alpha = 0.05 and beta = 0.2) requires: under the one-group design (known risk), 15,309 patients; and under the two-group design, 30,617 patients per group. This approach is the appropriate way to conclude equivalence, rather than the commonly used approach of difference testing and concluding equivalence when the null hypothesis of equality is not rejected. (C) 2000 Elsevier Science Inc. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 20/01/20 alle ore 22:38:03