title: Using a bayesian latent class model to evaluate the utility of investigating persons with negative polymerase chain reaction results for pertussis.
abstract: Pertussis remains difficult to control. Imperfect sensitivity of diagnostic tests and lack of specific guidance regarding interpretation of negative test results among patients with compatible symptoms may contribute to its spread. In this study, we examined whether additional pertussis cases could be identified if persons with negative pertussis test results were routinely investigated. We conducted interviews among 250 subjects aged ≤18 years with pertussis polymerase chain reaction (PCR) results reported from 2 reference laboratories in Wisconsin during July-September 2010 to determine whether their illnesses met the Centers for Disease Control and Prevention's clinical case definition (CCD) for pertussis. PCR validity measures were calculated using the CCD as the standard for pertussis disease. Two Bayesian latent class models were used to adjust the validity measures for pertussis detectable by 1) culture alone and 2) culture and/or more sensitive measures such as serology. Among 190 PCR-negative subjects, 54 (28%) had illnesses meeting the CCD. In adjusted analyses, PCR sensitivity and the negative predictive value were 1) 94% and 99% and 2) 43% and 87% in the 2 types of models, respectively. The models suggested that public health follow-up of reported pertussis patients with PCR-negative results leads to the detection of more true pertussis cases than follow-up of PCR-positive persons alone. The results also suggest a need for a more specific pertussis CCD.
authors.affiliation: Department of Pediatrics, School ofMedicine and Public Health, University of Wisconsin–Madison, Madison,WI 53792, USA.
authors.forename: Gillian A M
authors.initials: GA
authors.lastname: Tarr
authors.forename: Jens C
authors.initials: JC
authors.lastname: Eickhoff
authors.forename: Ruth
authors.initials: R
authors.lastname: Koepke
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Hopfensperger
authors.forename: Jeffrey P
authors.initials: JP
authors.lastname: Davis
authors.forename: James H
authors.initials: JH
authors.lastname: Conway
mesh_terms: D000293:Adolescent; D001499:Bayes Theorem; D001886:Bordetella pertussis / Q000235:genetics / Q000302:isolation & purification*; D002648:Child; D002675:Child, Preschool; D004269:DNA, Bacterial / Q000032:analysis*; D003627:Data Interpretation, Statistical; D005188:False Negative Reactions; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods*; D011237:Predictive Value of Tests; D060888:Real-Time Polymerase Chain Reaction; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014917:Whooping Cough / Q000175:diagnosis*; D014922:Wisconsin
chemical_list: D004269:DNA, Bacterial
keywords: Bayesian analysis; Bordetella pertussis; pertussis; polymerase chain reaction; predictive value of tests; public health surveillance; sensitivity; whooping cough