Estimation of sensitivity and specificity of site‐specific diagnostic tests

Hujoel, Philippe P.; Moulton, Lawrence H.; Loesche, W. J.

doi:10.1111/j.1600-0765.1990.tb00903.x

Cited by 37 publications

(33 citation statements)

References 10 publications

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“…Statistical analysis.-Site-specific analysis was performed for determination of the within-patient dependency of sites (Hujoel et al, 1990). A beta binomial ANOVA model (SAS, SAS Institute, Inc., NC) was used to correlate the withinpatient frequency of positive BANA or positive ELISA reactions with the frequency of periodontal disease in the 20 parents found to have a history of periodontal disease (generalized linear interacting model: GLIM).…”

Section: Methodsmentioning

confidence: 99%

Detection of Two Anaerobic Periodontopathogens in Children by Means of the BANA and ELISA Assays

et al. 1991

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The mouths of young children become colonized by a variety of bacteria, but there have been only a few studies that have sought the presence of periodontopathic species in this population. Almost all of these studies used culturing techniques rather than the newer detection methodologies for various periodontopathogens. Studies in adults have shown that Treponema denticola and Porphyromonas (Bacteroides) gingivalis can be detected in dental plaque by use of the BANA and ELISA diagnostic tests. In the present study, plaque samples from four subgingival sites in each of 157 children (aged from two to 18 years) were tested for BANA hydrolysis with a BANA reagent card, and for T. denticola and P. gingivalis with an ELISA assay. Anaerobic periodontopathogens hydrolyzing the BANA substrate were found to be present in at least one of four plaque samples in 88 children (56%). T. denticola and/or P. gingivalis were detected by ELISA in at least one plaque sample in each of 135 children (86%). This study shows that children are widely colonized by these micro-organisms. A higher proportion of Black children than Caucasian children was colonized by these BANA-positive organisms. Also, children having a parent with a documented history of periodontal disease were more likely to be BANA-positive than were children of parents with unknown periodontal status.

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Section: Methodsmentioning

confidence: 99%

Detection of Two Anaerobic Periodontopathogens in Children by Means of the BANA and ELISA Assays

et al. 1991

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“…If data are available, different methods for estimation ofthe within-patient correlation coefficient have been reported in the dental literature (Donner and Banting, 1989;Hujoel et al, 1990;DeRouen et al, 1991) and can be used. Ifno preliminary data or published reports are available, an evaluation ofthe optimum site sample size as a function of the within-patient correlation can provide an indication of whether whole-mouth examinations or some partial-recording procedure should be used.…”

Section: Methods and Resultsmentioning

confidence: 99%

Determination and Selection of the Optimum Number of Sites and Patients for Clinical Studies

Hujoel

DeRouen

1992

J Dent Res

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Calculating required sample sizes is a critical step in the design of any study. For dental studies, the sample size needs to be specified at two levels: (1) the number of patients (n) enrolled in the study, and (2) the average number of sites (m) examined per patient. In general, m and n should be selected in such a way that the precision of the research findings is maximized, while the cost of the study is minimized. This objective can be realized by taking stock of the components of variation and the costs involved with enrolling patients and examining sites. The research cost for n patients ($C1/patient), at an average of m sites per patient ($C2/site), can usually be approximated by nC1 + nmC2. The precision varies as a function of the variance components, m, and n. To optimize precision for a fixed cost, the average number of sites examined per patient (m(opt)) should be approximately equal to [formula: see text] where rho is the within-patient correlation coefficient of the site-specific variable measured. When m(opt) is approximately equal to or in excess of the average number of sites available per patient, whole-mouth examinations are indicated. When m(opt) is considerably smaller than the average number of sites available, the sample of optimum size should be obtained by some random mechanism. Examination of a number of sites considerably different from m(opt) results in a waste of resources, regardless of the number of patients studied. Standard statistical analyses for determination of the patient sample size required to obtain a pre-specified precision or power are discussed.

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“…However, when a subject contributes more than one paired binary response, it results in clustered data where the independent subjects are the clusters and each pair of responses is a unit within the cluster. If the dependence among paired responses within a subject is ignored, the variance of the parameter estimate may be underestimated, leading to smaller p-values and possible false statistical conclusions [16,17]. The performance of a test that does not account for clustering is likely to change in the presence of correlated (clustered) matched-pairs.…”

Section: Non-inferiority For Clustered Matched-pair Datamentioning

confidence: 92%

Analysis of clustered matched‐pair data for a non‐inferiority study design

Durkalski

Palesch

Lipsitz

et al. 2002

Statistics in Medicine

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Hypothesis testing of matched-pair data has been adapted for equivalence (one- and two-sided) study designs; however, a statistical problem arises when more than one measurement is recorded for each study subject. Ignoring the correlation between the repeated measurements per subject may underestimate the standard error of the parameter estimate. A method of testing for non-inferiority or equivalence of clustered matched-pair data is not yet available. This paper proposes a Wald-type test statistic for a non-inferiority hypothesis and applies it to the comparison of two diagnostic procedures.

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Estimation of sensitivity and specificity of site‐specific diagnostic tests

Cited by 37 publications

References 10 publications

Detection of Two Anaerobic Periodontopathogens in Children by Means of the BANA and ELISA Assays

Detection of Two Anaerobic Periodontopathogens in Children by Means of the BANA and ELISA Assays

Determination and Selection of the Optimum Number of Sites and Patients for Clinical Studies

Analysis of clustered matched‐pair data for a non‐inferiority study design

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