A Bayesian approach to strengthen inference for case‐control studies with multiple error‐prone exposure assessments

Zhang, Jing; Cole, Stephen R.; Richardson, David B.; Chu, Haitao

doi:10.1002/sim.5842

Cited by 9 publications

(10 citation statements)

References 39 publications

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“…It is recommended that future studies employ a more stringent gold standard such as a medical record review or active follow‐up. Future studies should also employ statistical methods that use multiple imprecise case identification methods to correct for measurement error …”

Section: Discussionmentioning

confidence: 99%

Descriptive evaluation of methods for identifying work‐related emergency department injury visits

Morano

Richardson

Proescholdbell

2019

American J Industrial Med

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Background: Use of worker's compensation (WC) as payer underestimates work-related (WR) injuries. We evaluated three methods to identify WR injuries:WC as payer, ICD-9-CM work-status codes E000.0/E000.1, and other ICD-9-CM external cause codes. Methods: We identified injury-related emergency department visits from NorthCarolina's syndromic surveillance system (2010)(2011)(2012)(2013). Characteristics were compared by indicator. We manually reviewed 800 admission notes to confirm if the visit was WR or non-WR; WR keywords from the review were applied to all visits.Results: 133 156 injury-related visits (age, 16 years or older) were identified: WC = 69%, work-status codes = 18%, other ICD-9-CM codes = 13%. Among manually reviewed visits: few visits identified by WC (0.3%) or work-status codes (2%) were non-WR, while 12% of other ICD-9-CM code identified visits were non-WR; 53%, 46%, and 31% of visits identified by WC, work-status codes, and other ICD-9-CM codes were WR, respectively. Conclusions: Findings support use of WC and work-status codes to capture WR injuries; other ICD-9-CM codes should be used with caution or in combination with other indicators. K E Y W O R D S administrative data, emergency department, ICD-9-

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Section: Discussionmentioning

confidence: 99%

Descriptive evaluation of methods for identifying work‐related emergency department injury visits

Morano

Richardson

Proescholdbell

2019

American J Industrial Med

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“…The cross-classification of all test results should be presented in a format similar to that of the motivating example dataset in Additional file 4 . The fact that meta-analysis is possible using imperfect reference tests suggests it may be more efficient to design future studies with multiple imperfect tests rather than using a single “as-accurate-as-possible” reference test, as has been shown in the analysis of epidemiological studies with imperfect measures of exposure [ 30 , 31 ]. When applied to a dataset on visceral leishmaniasis diagnostic tests, the model indicated that C of the two tests of interest may have been underestimated due to the use of imperfect reference test.…”

Section: Discussionmentioning

confidence: 99%

A general framework for comparative Bayesian meta-analysis of diagnostic studies

Menten

Lesaffre

2015

BMC Med Res Methodol

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BackgroundSelecting the most effective diagnostic method is essential for patient management and public health interventions. This requires evidence of the relative performance of alternative tests or diagnostic algorithms. Consequently, there is a need for diagnostic test accuracy meta-analyses allowing the comparison of the accuracy of two or more competing tests. The meta-analyses are however complicated by the paucity of studies that directly compare the performance of diagnostic tests. A second complication is that the diagnostic accuracy of the tests is usually determined through the comparison of the index test results with those of a reference standard. These reference standards are presumed to be perfect, i.e. allowing the classification of diseased and non-diseased subjects without error. In practice, this assumption is however rarely valid and most reference standards show false positive or false negative results. When an imperfect reference standard is used, the estimated accuracy of the tests of interest may be biased, as well as the comparisons between these tests.MethodsWe propose a model that allows for the comparison of the accuracy of two diagnostic tests using direct (head-to-head) comparisons as well as indirect comparisons through a third test. In addition, the model allows and corrects for imperfect reference tests. The model is inspired by mixed-treatment comparison meta-analyses that have been developed for the meta-analysis of randomized controlled trials. As the model is estimated using Bayesian methods, it can incorporate prior knowledge on the diagnostic accuracy of the reference tests used.ResultsWe show the bias that can result from using inappropriate methods in the meta-analysis of diagnostic tests and how our method provides more correct estimates of the difference in diagnostic accuracy between two tests. As an illustration, we apply this model to a dataset on visceral leishmaniasis diagnostic tests, comparing the accuracy of the RK39 dipstick with that of the direct agglutination test.ConclusionsOur proposed meta-analytic model can improve the comparison of the diagnostic accuracy of competing tests in a systematic review. This is however only true if the studies and especially information on the reference tests used are sufficiently detailed. More specifically, the type and exact procedures used as reference tests are needed, including any cut-offs used and the number of subjects excluded from full reference test assessment. If this information is lacking, it may be better to limit the meta-analysis to direct comparisons.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-015-0061-7) contains supplementary material, which is available to authorized users.

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“…Estimation of E-cadherin sensitivity and specificity to assess detachment was conducted using Bayesian latent class analysis following the framework of Zhang et al [ 20 ]. Based on our previous finding that dichotomous E-cadherin defined by cut points of 0.52, 0.60, and 0.85 were each associated with time to all-cause mortality in this dataset [ 6 ], we estimated the diagnostic accuracy of each of these dichotomous E-cadherin variables.…”

Section: Methodsmentioning

confidence: 99%

“…The correlation in disease misclassification is accommodated by a latent continuous variable Z i ~ N ( 0, 1 ). The positive result for the j th assessment is assumed to depend on both the latent true disease status D i of the i th subject and the Gaussian latent variable Z i through a generalized linear mixed regression model, such as a probit model [ 20 ], where d i = 0,1. Here, the latent Gaussian random variable Z i is assumed to be independent of the latent disease status D i .…”

Section: Methodsmentioning

confidence: 99%

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Diagnostic accuracy and prediction increment of markers of epithelial-mesenchymal transition to assess cancer cell detachment from primary tumors

et al. 2018

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BackgroundMetastases play a role in about 90% of cancer deaths. Markers of epithelial-mesenchymal transition (EMT) measured in primary tumor cancer cells might provide diagnostic information about the likelihood that cancer cells have detached from the primary tumor. Used together with established diagnostic tests of detachment—lymph node evaluation and radiologic imaging—EMT marker measurements might improve the ability of clinicians to assess the patient’s risk of metastatic disease. Translation of EMT markers to clinical use has been hampered by a lack of valid analyses of clinically-informative parameters. Here, we demonstrate a rigorous approach to estimating the sensitivity, specificity, and prediction increment of an EMT marker to assess cancer cell detachment from primary tumors.MethodsWe illustrate the approach using immunohistochemical measurements of the EMT marker E-cadherin in a set of colorectal primary tumors from a population-based prospective cohort in North Carolina. Bayesian latent class analysis was used to estimate sensitivity and specificity in a setting of multiple imperfect diagnostic tests and no gold standard. Risk reclassification analysis was used to assess the extent to which addition of the marker to the panel of established diagnostic tests would improve mortality prediction. We explored how changing the latent class conditional dependence assumptions and definition of marker positivity would impact the results.ResultsAll diagnostic accuracy and prediction increment statistics varied with the choice of cut point to define marker positivity. When comparing different definitions of marker positivity to each other, numerous trade-offs were observed in terms of sensitivity, specificity, predictive discrimination, and prediction model calibration. We then discussed several implementation considerations and the plausibility of analytic assumptions.ConclusionsThe approaches presented here can be extended to any EMT marker, to most forms of cancer, and to different kinds of EMT marker measurements, such as RNA or gene methylation data. These methods provide valid, clinically-informative assessment of whether and how to use a given EMT marker to refine tumor staging and consequent treatment decisions.Electronic supplementary materialThe online version of this article (10.1186/s12885-017-3964-3) contains supplementary material, which is available to authorized users.

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A Bayesian approach to strengthen inference for case‐control studies with multiple error‐prone exposure assessments

Cited by 9 publications

References 39 publications

Descriptive evaluation of methods for identifying work‐related emergency department injury visits

Descriptive evaluation of methods for identifying work‐related emergency department injury visits

A general framework for comparative Bayesian meta-analysis of diagnostic studies

Diagnostic accuracy and prediction increment of markers of epithelial-mesenchymal transition to assess cancer cell detachment from primary tumors

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