Defining the True Sensitivity of Culture for the Diagnosis of Melioidosis Using Bayesian Latent Class Models

Background Culture remains the diagnostic gold standard for many bacterial infections, and the method against which other tests are often evaluated. Specificity of culture is 100% if the pathogenic organism is not found in healthy subjects, but the sensitivity of culture is more difficult to determine and may be low. Here, we apply Bayesian latent class models (LCMs) to data from patients with a single Gram-negative bacterial infection and define the true sensitivity of culture together with the impact of misclassification by culture on the reported accuracy of alternative diagnostic tests. Methods/Principal Findings Data from published studies describing the application of five diagnostic tests (culture and four serological tests) to a patient cohort with suspected melioidosis were re-analysed using several Bayesian LCMs. Sensitivities, specificities, and positive and negative predictive values (PPVs and NPVs) were calculated. Of 320 patients with suspected melioidosis, 119 (37%) had culture confirmed melioidosis. Using the final model (Bayesian LCM with conditional dependence between serological tests), the sensitivity of culture was estimated to be 60.2%. Prediction accuracy of the final model was assessed using a classification tool to grade patients according to the likelihood of melioidosis, which indicated that an estimated disease prevalence of 61.6% was credible. Estimates of sensitivities, specificities, PPVs and NPVs of four serological tests were significantly different from previously published values in which culture was used as the gold standard. Conclusions/Significance Culture has low sensitivity and low NPV for the diagnosis of melioidosis and is an imperfect gold standard against which to evaluate alternative tests. Models should be used to support the evaluation of diagnostic tests with an imperfect gold standard. It is likely that the poor sensitivity/specificity of culture is not specific for melioidosis, but rather a generic problem for many bacterial and fungal infections.

[1]  N. White,et al.  Pseudomonas pseudomallei liver abscesses: a clinical, laboratory, and ultrasonographic study. , 1992, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[2]  M. Tan,et al.  Random effects models in latent class analysis for evaluating accuracy of diagnostic tests. , 1996, Biometrics.

[3]  G. Rogers,et al.  Studying bacterial infections through culture-independent approaches. , 2009, Journal of medical microbiology.

[4]  N. Day,et al.  Increasing Incidence of Human Melioidosis in Northeast Thailand , 2010, The American journal of tropical medicine and hygiene.

[5]  Matthew A. Kayala,et al.  A Burkholderia pseudomallei protein microarray reveals serodiagnostic and cross-reactive antigens , 2009, Proceedings of the National Academy of Sciences.

[6]  Andrew Thomas,et al.  WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility , 2000, Stat. Comput..

[7]  B. Alexander Diagnosis of fungal infection: new technologies for the mycology laboratory. , 2002, Transplant infectious disease : an official journal of the Transplantation Society.

[8]  L. Joseph,et al.  Bayesian Approaches to Modeling the Conditional Dependence Between Multiple Diagnostic Tests , 2001, Biometrics.

[9]  A. Cheng,et al.  Evaluation of Immunoglobulin M (IgM) and IgG Rapid Cassette Test Kits for Diagnosis of Melioidosis in an Area of Endemicity , 2004, Journal of Clinical Microbiology.

[10]  M. Klouche,et al.  Rapid methods for diagnosis of bloodstream infections , 2008, Clinical chemistry and laboratory medicine.

[11]  K. Khupulsup,et al.  Application of indirect hemagglutination test and indirect fluorescent antibody test for IgM antibody for diagnosis of melioidosis in Thailand. , 1986, The American journal of tropical medicine and hygiene.

[12]  N. Day,et al.  Quantitation of B. Pseudomallei in clinical samples. , 2007, The American journal of tropical medicine and hygiene.

[13]  P. Mootsikapun,et al.  Splenic abscess: clinical features, microbiologic finding, treatment and outcome. , 2003, Journal of the Medical Association of Thailand = Chotmaihet thangphaet.

[14]  A. Simpson,et al.  Value of Throat Swab in Diagnosis of Melioidosis , 2001, Journal of Clinical Microbiology.

[15]  Søren Højsgaard,et al.  Diagnosing diagnostic tests: evaluating the assumptions underlying the estimation of sensitivity and specificity in the absence of a gold standard. , 2005, Preventive veterinary medicine.

[16]  N. Day,et al.  Development of antibodies to Burkholderia pseudomallei during childhood in melioidosis-endemic northeast Thailand. , 2006, The American journal of tropical medicine and hygiene.

[17]  A. Cheng,et al.  Intensity of exposure and incidence of melioidosis in Thai children. , 2008, Transactions of the Royal Society of Tropical Medicine and Hygiene.

[18]  A. Cheng,et al.  Accuracy of Enzyme-Linked Immunosorbent Assay Using Crude and Purified Antigens for Serodiagnosis of Melioidosis , 2006, Clinical and Vaccine Immunology.

[19]  A. Cheng,et al.  Melioidosis: Epidemiology, Pathophysiology, and Management , 2005, Clinical Microbiology Reviews.

[20]  N. White,et al.  Melioidosis: a major cause of community-acquired septicemia in northeastern Thailand. , 1989, The Journal of infectious diseases.

[21]  A. Cheng,et al.  Prospective evaluation of a rapid immunochromogenic cassette test for the diagnosis of melioidosis in northeast Thailand. , 2006, Transactions of the Royal Society of Tropical Medicine and Hygiene.

[22]  A. Cheng,et al.  Role and Significance of Quantitative Urine Cultures in Diagnosis of Melioidosis , 2005, Journal of Clinical Microbiology.

[23]  Bradley P. Carlin,et al.  Bayesian measures of model complexity and fit , 2002 .

[24]  Yinsheng Qu,et al.  A Model for Evaluating Sensitivity and Specificity for Correlated Diagnostic Tests in Efficacy Studies with an Imperfect Reference Test , 1998 .

[25]  N. White,et al.  The use of selective media for the isolation of Pseudomonas pseudomallei in clinical practice. , 1990, Journal of medical microbiology.

[26]  N. White,et al.  HALVING OF MORTALITY OF SEVERE MELIOIDOSIS BY CEFTAZIDIME , 1989, The Lancet.

[27]  L. Joseph,et al.  Bayesian estimation of disease prevalence and the parameters of diagnostic tests in the absence of a gold standard. , 1995, American journal of epidemiology.

[28]  Emmanuel Lesaffre,et al.  Bayesian latent class models with conditionally dependent diagnostic tests: A case study , 2008, Statistics in medicine.