Modelling variation in test sensitivity for monitoring leptospirosis in beef cattle.

When Bayesian latent class analysis is used for diagnostic test data in the absence of a gold standard test, it is common to assume that any unknown test sensitivities and specificities are constant across different populations. Indeed this assumption is often necessary for model identifiability. However there are a number of practical situations, depending on the type of test and the nature of the disease, where this assumption may not be true. We present a case study of using a microscopic agglutination test to diagnose leptospiroris infection in beef cattle, which strongly suggests that sensitivity in particular varies among herds. We develop and fit an alternative model in which sensitivity is related to within-herd prevalence, and discuss the statistical and epidemiological implications.

Patterns of Sexual Activity and the Development of Sexual Pain Across the Menopausal Transition.

OBJECTIVE: To examine whether patterns of sexual intercourse frequency and demographic, menopausal status, genitourinary, health, and psychosocial factors are associated with developing sexual pain across the menopausal transition. METHODS: These were longitudinal analyses of questionnaire data from the multicenter, multiracial and ethnic prospective cohort SWAN (Study of Women's Health Across the Nation) (1995-2008). We used multivariable discrete-time proportional hazards models to examine whether incident sexual pain was associated with preceding long-term (up to 10 visits) or short-term (two and three visits) sexual intercourse frequency patterns or other factors (eg, menopause status, genitourinary symptoms, lifestyle factors, and mental health). RESULTS: Of the 2,247 women with no sexual pain at baseline, 1,087 (48.4%) developed sexual pain at least "sometimes" up to 10 follow-up visits over 13 years. We found no consistent association between prior patterns of sexual intercourse frequency and development of sexual pain. For example, neither decreases in intercourse frequency from baseline (adjusted hazard ratio [aHR] 0.93, 95% CI 0.73-1.19) nor decreases in frequency over three prior visits (aHR 1.00, 95% CI 0.72-1.41) were associated with incident pain. Reasons for interruptions in intercourse activity at the prior visit, including lack of interest (aHR 1.64, 95% CI 0.74-3.65) and relationship issues (aHR 0.36, 95% CI 0.04-2.88), were not associated with developing pain. Being postmenopausal using hormone therapy (aHR 3.16, 95% CI 1.46-6.85), and reported vaginal dryness (aHR 3.73, 95% CI 2.88-4.83) were most strongly associated with incident sexual pain. CONCLUSION: Long-term and short-term declines in sexual intercourse frequency across the menopausal transition were not associated with increased hazard of developing pain with intercourse. This empirical evidence does not support the common belief that a reduction in women's sexual frequency is responsible for their symptoms of sexual pain.

Analysis of German BSE Surveillance Data: Estimation of the Prevalence of Confirmed Cases versus the Number of Infected, but Non-Detected, Cattle to Assess Confidence in Freedom from Infection.

Quantitative risk assessments for Bovine spongiform encephalopathy (BSE) necessitate estimates for key parameters such as the prevalence of infection, the probability of absence of infection in defined birth cohorts, and the numbers of BSE-infected, but non-detected cattle entering the food chain. We estimated three key parameters with adjustment for misclassification using the German BSE surveillance data using a Gompertz model for latent (i.e., unobserved) age-dependent detection probabilities and a Poisson response model for the number of BSE cases for birth cohorts 1999 to 2015. The models were combined in a Bayesian framework. We estimated the median true BSE prevalence between 3.74 and 0.216 cases per 100,000 animals for the birth cohorts 1990 to 2001 and observed a peak for the 1996 birth cohort with a point estimate of 16.41 cases per 100,000 cattle. For birth cohorts ranging from 2002 to 2013, the estimated median prevalence was below one case per 100,000 heads. The calculated confidence in freedom from disease (design prevalence 1 in 100,000) was above 99.5% for the birth cohorts 2002 to 2006. In conclusion, BSE surveillance in the healthy slaughtered cattle chain was extremely sensitive at the time, when BSE repeatedly occurred in Germany (2000-2009), because the entry of BSE-infected cattle into the food chain could virtually be prevented by the extensive surveillance program during these years and until 2015 (estimated non-detected cases/100.000 [95% credible interval] in 2000, 2009, and 2015 are 0.64 [0.5,0.8], 0.05 [0.01,0.14], and 0.19 [0.05,0.61], respectively).

Gold standards are out and Bayes is in: Implementing the cure for imperfect reference tests in diagnostic accuracy studies.

Bayesian mixture models, often termed latent class models, allow users to estimate the diagnostic accuracy of tests and true prevalence in one or more populations when the positive and/or negative reference standards are imperfect. Moreover, they allow the data analyst to show the superiority of a novel test over an old test, even if this old test is the (imperfect) reference standard. We use published data on Toxoplasmosis in pigs to explore the effects of numbers of tests, numbers of populations, and dependence structure among tests to ensure model (local) identifiability. We discuss and make recommendations about use of priors, sensitivity analysis, model identifiability and study design options, and strongly argue for the use of Bayesian mixture models as a logical and coherent approach for estimating the diagnostic accuracy of two or more tests.

Comparing Objective and Subjective Bayes Factors for the Two-Sample Comparison: The Classification Theorem in Action.

Many Bayes factors have been proposed for comparing population means in two-sample (independent samples) studies. Recently, Wang and Liu (2015) presented an "objective" Bayes factor (BF) as an alternative to a "subjective" one presented by Gönen et al. (2005). Their report was evidently intended to show the superiority of their BF based on "undesirable behavior" of the latter. A wonderful aspect of Bayesian models is that they provide an opportunity to "lay all cards on the table." What distinguishes the various BFs in the two-sample problem is the choice of priors (cards) for the model parameters. This article discusses desiderata of BFs that have been proposed, and proposes a new criterion to compare BFs, no matter whether subjectively or objectively determined: A BF may be preferred if it correctly classifies the data as coming from the correct model most often. The criterion is based on a famous result in classification theory to minimize the total probability of misclassification. This criterion is objective, easily verified by simulation, shows clearly the effects (positive or negative) of assuming particular priors, provides new insights into the appropriateness of BFs in general, and provides a new answer to the question, "Which BF is best?"

Patterns of Cardiometabolic Health as Midlife Women Transition to Menopause: A Prospective Multiethnic Study.

CONTEXT: Cardiometabolic conditions increase in midlife, but early customized prevention strategies are not established for such women. OBJECTIVE: To characterize and identify factors longitudinally related to constellations of cardiometabolic risk components in multiracial/ethnic women in midlife. DESIGN: We conducted a prospective, longitudinal, multiethnic cohort study of 3003 midlife women undergoing menopausal transition (MT). Metabolic syndrome (MetS) was defined as having at least three of five components: high fasting triglyceride (hTG) level, low high-density lipoprotein cholesterol (lHDL-C) level, high fasting plasma glucose (hGluc) level, large waist circumference (abdominal obesity; Ob), and hypertension (HTN). We described the patterns of constellations and estimated hazard ratios (HRs) for constellations at (i) incident MetS and (ii) recovery from MetS, using multivariable-adjusted Cox regression. SETTING: Seven US sites. PARTICIPANTS: In all, 1412 non-Hispanic white, 851 black, 272 Japanese, 237 Hispanic, and 231 Chinese women. EXPOSURES: Race/ethnicity, lifestyle factors, and MT stage. MAIN OUTCOMES MEASURES: Cardiometabolic constellations, incident MetS, and MetS recovery. RESULTS: Central obesity was the most frequent component. Having no components was the most frequent (31%) baseline constellation. Physical activity (HR = 1.68; 95% CI: 1.06, 2.68) and lower caloric intake (HR = 0.96; 95% CI: 0.93, 0.99 per 100 cal/d) were associated with recovery from MetS. Ob/hTG/lHDL-C (18%), Ob/HTN/lHDL-C (16%), and Ob/HTN/hGluc (14%) were frequent incident constellations. Physically active women had 26% to 62% lower hazards of incident MetS than inactive women. CONCLUSIONS: Modifiable lifestyle behaviors were related to recovery from MetS and decreased risk of the most frequent MetS constellations in midlife women.

Factors associated with reasons incontinent midlife women report for not seeking urinary incontinence treatment over 9 years across the menopausal transition.

OBJECTIVE: We explored factors associated with reasons that women with urinary incontinence (UI) reported for not seeking treatment for their UI from a healthcare professional and whether reasons differed by race/ethnicity, socioeconomic status, or education. METHODS: We analyzed questionnaire data collected from 1995 to 2005 in the Study of Women's Health Across the Nation. In visits 7 to 9, we elicited reasons that women with UI reported for not seeking treatment and condensed them into: UI not bad enough, beliefs about UI causes (UI is a normal consequence of aging or childbirth), and motivational barriers (such as feeling too embarrassed). We used Generalized Estimating Equations and ordinal logistic regression to evaluate factors associated with these reported reasons and number of reasons. RESULTS: Of the 1,339 women reporting UI, 814 (61.0%) reported they did not seek treatment for UI. The most frequently reported reasons were as follows: "UI not bad enough" (73%), "UI is a normal part of aging" (53%), and "healthcare provider never asked" (55%). Women reporting daily UI had higher odds of reporting beliefs about UI causes (adjusted odds ratio UI 3.16, 95% CI 1.64-6.11) or motivational barriers (adjusted odds ratio UI 2.36, 95% CI 1.21-4.63) compared with women reporting less than monthly UI. We found no interactions by race/ethnicity, socioeconomic status, or education and UI characteristics in reasons that women reported for not seeking UI treatment. CONCLUSIONS: Over half of women who did not seek treatment for their UI reported reasons that could be addressed by public health and clinical efforts to make UI a discussion point during midlife well-women visits.

STARD-BLCM: Standards for the Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models.

The Standards for the Reporting of Diagnostic Accuracy (STARD) statement, which was recently updated to the STARD2015 statement, was developed to encourage complete and transparent reporting of test accuracy studies. Although STARD principles apply broadly, the checklist is limited to studies designed to evaluate the accuracy of tests when the disease status is determined from a perfect reference procedure or an imperfect one with known measures of test accuracy. However, a reference standard does not always exist, especially in the case of infectious diseases with a long latent period. In such cases, a valid alternative to classical test evaluation involves the use of latent class models that do not require a priori knowledge of disease status. Latent class models have been successfully implemented in a Bayesian framework for over 20 years. The objective of this work was to identify the STARD items that require modification and develop a modified version of STARD for studies that use Bayesian latent class analysis to estimate diagnostic test accuracy in the absence of a reference standard. Examples and elaborations for each of the modified items are provided. The new guidelines, termed STARD-BLCM (Standards for Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models), will facilitate improved quality of reporting on the design, conduct and results of diagnostic accuracy studies that use Bayesian latent class models.

Associations between urinary biomarkers of polycyclic aromatic hydrocarbon exposure and reproductive function during menstrual cycles in women.

Essentially all women are exposed to polycyclic aromatic hydrocarbons (PAHs), formed during incomplete combustion of organic materials, including fossil fuels, wood, foods, and tobacco. PAHs are ovarian toxicants in rodents, and cigarette smoking is associated with reproductive abnormalities in women. Biomonitoring of hydroxylated PAH (OH-PAH) metabolites in urine provides an integrated measure of exposure to PAHs via multiple routes and has been used to characterize exposure to PAHs in humans. We hypothesized that concentrations of OH-PAHs in urine are associated with reproductive function in women. We recruited women 18-44years old, living in Orange County, California to conduct daily measurement of urinary luteinizing hormone (LH) and estrone 3-glucuronide (E13G) using a microelectronic fertility monitor for multiple menstrual cycles; these data were used to calculate endocrine endpoints. Participants also collected urine samples on cycle day 10 for measurement of nine OH-PAHs. Models were constructed for eight endpoints using a Bayesian mixed modeling approach with subject-specific random effects allowing each participant to act as a baseline for her set of measurements. We observed associations between individual OH-PAH concentrations and follicular phase length, follicular phase LH and E13G concentrations, preovulatory LH surge concentrations, and periovulatory E13G slope and concentration. We have demonstrated the feasibility of using urinary reproductive hormone data obtained via fertility monitors to calculate endocrine endpoints for epidemiological studies of ovarian function during multiple menstrual cycles. The results show that environmental exposure to PAHs is associated with changes in endocrine markers of ovarian function in women in a PAH-specific manner.

Environmental tobacco smoke and risk of late-diagnosis incident fibroids in the Study of Women's Health across the Nation (SWAN).

OBJECTIVE: To assess the longitudinal relationship of environmental tobacco smoke (ETS) exposure during midlife, and its interaction with active smoking, with the risk of late-diagnosis incident uterine fibroids during the menopausal transition. DESIGN: Thirteen-year prospective cohort study. SETTING: Not applicable. PATIENT(S): Community-based, multiracial/ethnic cohort of 2,575 women aged 42 to 52 years at baseline, undergoing the menopausal transition. INTERVENTION(S): Questionnaire and blood draws. MAIN OUTCOME MEASURE(S): Discrete-time proportional odds models were used to estimate the conditional odds ratio (OR) and 95% confidence interval (CI) of incident fibroids, adjusted for menopausal status, race/ethnicity, study site, age, education, estradiol levels, sex hormone use, body mass index, timing of blood draw, age at menarche, alcohol use, and smoking status and pack-years. RESULT(S): As part of SWAN, at each near-annual study visit, ETS exposure, smoking, and fibroid occurrence were self-reported via questionnaire, and blood draws were collected. Women who were exposed to ETS (≥1 person-hour/week) had 1.28 (95% CI, 1.03, 1.60) times the adjusted odds of incident fibroids in the ensuing year compared the unexposed. The odds were elevated in never smokers (adjusted OR 1.34; 95% CI, 1.06, 1.70) and former smokers (adjusted OR 2.57; 95% CI, 1.05, 7.23). CONCLUSION(S): In midlife, ETS exposure was associated with an increased risk of late-diagnosis incident fibroids in women undergoing the menopausal transition.

Triglyceride Levels and Fracture Risk in Midlife Women: Study of Women's Health Across the Nation (SWAN).

CONTEXT: Unfavorable lipid levels contribute to cardiovascular disease and may also harm bone health. OBJECTIVE: Our objective was to investigate relationships between fasting plasma lipid levels and incident fracture in midlife women undergoing the menopausal transition. DESIGN AND SETTING: This was a 13-year prospective, longitudinal study of multiethnic women in five US communities, with near-annual assessments. PARTICIPANTS: At baseline, 2062 premenopausal or early perimenopausal women who had no history of fracture were included. EXPOSURES: Fasting plasma total cholesterol, triglycerides (TG), low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol at baseline and follow-up visits 1 and 3-7. MAIN OUTCOME MEASURE(S): Incident nontraumatic fractures 1) 2 or more years after baseline, in relation to a single baseline level of lipids; and 2) 2-5 years later, in relation to time-varying lipid levels. Cox proportional hazards modelings estimated hazard ratios and 95% confidence interval (CI). RESULTS: Among the lipids, TG levels changed the most, with median levels increased by 16% during follow-up. An increase of 50 mg/dl in baseline TG level was associated with a 1.1-fold increased hazards of fracture (adjusted hazard ratio, 1.11; 95% CI, 1.04-1.18). Women with baseline TG higher than 300 mg/dl had an adjusted 2.5-fold greater hazards for fractures (95% CI, 1.13-5.44) than women with baseline TG lower than 150 mg/dl. Time-varying analyses showed a comparable TG level-fracture risk relationship. Associations between total cholesterol, low-density lipoprotein cholesterol, or high-density lipoprotein cholesterol levels and fractures were not observed. CONCLUSIONS: Midlife women with high fasting plasma TG had an increased risk of incident nontraumatic fracture. Secondary Abstract: Midlife women with fasting plasma triglyceride (TG) of at least 300 mg/dl had 2.5-fold greater hazards of fracture in 2 years later and onward, compared to those with TG below 150 mg/dl, in a multiethnic cohort. Time-varying analyses revealed comparable results.

Bayesian Nonparametric Longitudinal Data Analysis.

Practical Bayesian nonparametric methods have been developed across a wide variety of contexts. Here, we develop a novel statistical model that generalizes standard mixed models for longitudinal data that include flexible mean functions as well as combined compound symmetry (CS) and autoregressive (AR) covariance structures. AR structure is often specified through the use of a Gaussian process (GP) with covariance functions that allow longitudinal data to be more correlated if they are observed closer in time than if they are observed farther apart. We allow for AR structure by considering a broader class of models that incorporates a Dirichlet Process Mixture (DPM) over the covariance parameters of the GP. We are able to take advantage of modern Bayesian statistical methods in making full predictive inferences and about characteristics of longitudinal profiles and their differences across covariate combinations. We also take advantage of the generality of our model, which provides for estimation of a variety of covariance structures. We observe that models that fail to incorporate CS or AR structure can result in very poor estimation of a covariance or correlation matrix. In our illustration using hormone data observed on women through the menopausal transition, biology dictates the use of a generalized family of sigmoid functions as a model for time trends across subpopulation categories.

Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard.

The area under the receiver operating characteristic (ROC) curve (AUC) is used as a performance metric for quantitative tests. Although multiple biomarkers may be available for diagnostic or screening purposes, diagnostic accuracy is often assessed individually rather than in combination. In this paper, we consider the interesting problem of combining multiple biomarkers for use in a single diagnostic criterion with the goal of improving the diagnostic accuracy above that of an individual biomarker. The diagnostic criterion created from multiple biomarkers is based on the predictive probability of disease, conditional on given multiple biomarker outcomes. If the computed predictive probability exceeds a specified cutoff, the corresponding subject is allocated as 'diseased'. This defines a standard diagnostic criterion that has its own ROC curve, namely, the combined ROC (cROC). The AUC metric for cROC, namely, the combined AUC (cAUC), is used to compare the predictive criterion based on multiple biomarkers to one based on fewer biomarkers. A multivariate random-effects model is proposed for modeling multiple normally distributed dependent scores. Bayesian methods for estimating ROC curves and corresponding (marginal) AUCs are developed when a perfect reference standard is not available. In addition, cAUCs are computed to compare the accuracy of different combinations of biomarkers for diagnosis. The methods are evaluated using simulations and are applied to data for Johne's disease (paratuberculosis) in cattle.

Circulating Sex Hormones and Risk of Uterine Fibroids: Study of Women's Health Across the Nation (SWAN).

CONTEXT: Estrogen has been implicated in the development of uterine fibroids. However, the contribution of androgen in women is unknown. OBJECTIVE: Our objective was to assess the longitudinal relations of circulating androgens and estradiol (E2) and their joint effects to the risk of developing fibroids. DESIGN: This is a 13-year longitudinal study in the Study of Women's Health Across the Nation. SETTING: This study was conducted in seven sites across the United States (1997-2013). PARTICIPANTS: At baseline, 3240 pre- or early peri-menopausal women with an intact uterus, ages 45-52 years were included; 43.6% completed the follow-up. There were 512 incident and 478 recurrent fibroid cases. EXPOSURES: We measured near-annual time-varying serum levels of bioavailable E2 and bioavailable T, dichotomized at the median (high vs low). MAIN OUTCOMES AND MEASURES: We estimated the conditional odds ratio (OR) of fibroids in the ensuing year using discrete-time proportional odds models adjusted for race/ethnicity/site, age, body mass index, menopausal stage, reproductive factors, smoking, timing of blood draw, and FSH. RESULTS: Women with high T had a statistically significant increased risk of incident fibroids (OR, 1.33; 95% confidence interval [CI], 1.01-1.76; P = .04), but not recurrent fibroids. This risk was further elevated in those with high T and E2 (OR, 1.52; 95% CI, 1.07-2.17; P = .02). High E2 and T was associated with lower risk of recurrent fibroids (OR, 0.50; 95% CI, 0.26-0.96; P = .04). CONCLUSIONS: High T with high E2 was associated with an elevated risk of incident fibroids in midlife women who never reported fibroids before baseline. Conversely, the risk of recurrent fibroids was mitigated in women with high E2 and high T.

Flexible regression models for ROC and risk analysis, with or without a gold standard.

A novel semiparametric regression model is developed for evaluating the covariate-specific accuracy of a continuous medical test or biomarker. Ideally, studies designed to estimate or compare medical test accuracy will use a separate, flawless gold-standard procedure to determine the true disease status of sampled individuals. We treat this as a special case of the more complicated and increasingly common scenario in which disease status is unknown because a gold-standard procedure does not exist or is too costly or invasive for widespread use. To compensate for missing data on disease status, covariate information is used to discriminate between diseased and healthy units. We thus model the probability of disease as a function of 'disease covariates'. In addition, we model test/biomarker outcome data to depend on 'test covariates', which provides researchers the opportunity to quantify the impact of covariates on the accuracy of a medical test. We further model the distributions of test outcomes using flexible semiparametric classes. An important new theoretical result demonstrating model identifiability under mild conditions is presented. The modeling framework can be used to obtain inferences about covariate-specific test accuracy and the probability of disease based on subject-specific disease and test covariate information. The value of the model is illustrated using multiple simulation studies and data on the age-adjusted ability of soluble epidermal growth factor receptor - a ubiquitous serum protein - to serve as a biomarker of lung cancer in men. SAS code for fitting the model is provided. Copyright © 2015 John Wiley & Sons, Ltd.

Factors associated with seeking treatment for urinary incontinence during the menopausal transition.

OBJECTIVE: To examine whether longitudinal urinary incontinence (UI) characteristics, race or ethnicity, socioeconomic status, and education were associated with UI treatment-seeking in a prospective cohort of community-dwelling midlife women. METHODS: We analyzed data from 9 years of the Study of Women's Health Across the Nation. The study asked participants reporting at least monthly UI about seeking treatment for their UI at baseline and in visit years 7, 8, and 9. Our main covariates included self-reported race or ethnicity, income, level of difficulty paying for basics, and education level. We used multiple logistic regression to examine associations between demographic, psychosocial, and longitudinal UI characteristics and whether women sought UI treatment. We explored interactions by race or ethnicity, socioeconomic status measures, and education level. RESULTS: A total of 1,550 women (68% of women with UI) reported seeking treatment for UI over the 9 years of this study. In multivariable analyses, women had higher odds of seeking treatment when UI in the year before seeking treatment was more frequent (adjusted odds ratio [OR] 3.16, 95% confidence interval [CI] 1.15-8.67) and more bothersome (adjusted OR 1.09, 95% CI 1.01-1.18), with longer symptom duration, and with worsening UI symptoms (adjusted OR 1.75, 95% CI 1.01-3.04). Women who saw physicians regularly, had more preventive women's health visits, or both were more likely to seek UI treatment (adjusted OR 1.18, 95% CI 1.07, 1.30). Race or ethnicity, socioeconomic measures, and education were not significantly related to seeking treatment for UI. CONCLUSION: We found no evidence of racial or ethnic, socioeconomic, or education level disparities in UI treatment-seeking. Rather, longitudinal UI characteristics were most strongly associated with treatment-seeking behavior in midlife women. LEVEL OF EVIDENCE: II.

Limited utility of current MRI criteria for distinguishing multiple sclerosis from common mimickers: primary and secondary CNS vasculitis, lupus and Sjogren's syndrome.

BACKGROUND: Magnetic resonance imaging (MRI) criteria play an important role in making an earlier diagnosis of multiple sclerosis (MS) in patients presenting with clinically isolated syndrome. OBJECTIVE: The objective of this paper is to determine whether MRI criteria may be used to distinguish MS from primary and secondary central nervous system (CNS) vasculitis, lupus, and Sjogren's syndrome. METHODS: MRI criteria were applied retrospectively to images for patients with clinically definite MS (CDMS), primary CNS vasculitis, secondary CNS vasculitis, and autoimmune disorders including systemic lupus erythematosus (SLE) and Sjogren's syndrome. Classical statistics and Bayesian analyses were performed. RESULTS: Overall modified Barkhof's MRI criteria were statistically significant in distinguishing CDMS (60%) from SLE/Sjogren's syndrome (17%, p = 0.0173) but not in distinguishing CDMS from primary CNS vasculitis (50%, p = 0.7376) or secondary CNS vasculitis (58%, p = 1.0000). Four of the five other MRI criteria tested were demonstrated to be superior to modified Barkhof's criteria in predicting MS: nine or more T2 lesions (a component of Barkhof's criteria), one or more ovoid periventricular T2 lesions, one or more perpendicular periventricular T2 lesions, and one or more T2 lesions larger than 6 mm. CONCLUSIONS: MRI criteria, including the modified Barkhof's criteria, were unsuccessful in distinguishing MS from primary CNS vasculitis or secondary CNS vasculitis and mildly successful in distinguishing MS from SLE/Sjogren's syndrome.

Bayesian estimation of the sensitivity and specificity of individual fecal culture and Paralisa to detect Mycobacterium avium subspecies paratuberculosis infection in young farmed deer.

A Bayesian latent class model was used to estimate the sensitivity and specificity of an immunoglobulin G1 serum enzyme-linked immunosorbent assay (Paralisa) and individual fecal culture to detect young deer infected with Mycobacterium avium subsp. paratuberculosis. Paired fecal and serum samples were collected, between July 2009 and April 2010, from 20 individual yearling (12-24-month-old) deer in each of 20 South Island and 18 North Island herds in New Zealand and subjected to culture and Paralisa, respectively. Two fecal samples and 16 serum samples from 356 North Island deer, and 55 fecal and 37 serum samples from 401 South Island deer, were positive. The estimate of individual fecal culture sensitivity was 77% (95% credible interval [CI] = 61-92%) with specificity of 99% (95% CI = 98-99.7%). The Paralisa sensitivity estimate was 19% (95% CI = 10-30%), with specificity of 94% (95% CI = 93-96%). All estimates were robust to variation of priors and assumptions tested in a sensitivity analysis. The data informs the use of the tests in determining infection status at the individual and herd level.