scholarly journals Insights into latent class analysis of diagnostic test performance

Biostatistics ◽  
2006 ◽  
Vol 8 (2) ◽  
pp. 474-484 ◽  
Author(s):  
M. S. Pepe ◽  
H. Janes
2013 ◽  
Vol 103 (12) ◽  
pp. 1243-1251 ◽  
Author(s):  
William W. Turechek ◽  
Craig G. Webster ◽  
Jingyi Duan ◽  
Pamela D. Roberts ◽  
Chandrasekar S. Kousik ◽  
...  

Squash vein yellowing virus (SqVYV) is the causal agent of viral watermelon vine decline, one of the most serious diseases in watermelon (Citrullus lanatus L.) production in the southeastern United States. At present, there is not a gold standard diagnostic test for determining the true status of SqVYV infection in plants. Current diagnostic methods for identification of SqVYV-infected plants or tissues are based on the reverse-transcription polymerase chain reaction (RT-PCR), tissue blot nucleic acid hybridization assays (TB), and expression of visual symptoms. A quantitative assessment of the performance of these diagnostic tests is lacking, which may lead to an incorrect interpretation of results. In this study, latent class analysis (LCA) was used to estimate the sensitivities and specificities of RT-PCR, TB, and visual assessment of symptoms as diagnostic tests for SqVYV. The LCA model assumes that the observed diagnostic test responses are linked to an underlying latent (nonobserved) disease status of the population, and can be used to estimate sensitivity and specificity of the individual tests, as well as to derive an estimate of the incidence of disease when a gold standard test does not exist. LCA can also be expanded to evaluate the effect of factors and was done here to determine whether diagnostic test performances varied among the type of plant tissue being tested (crown versus vine tissue), where plant samples were taken relative to the position of the crown (i.e., distance from the crown), host (i.e., genus), and habitat (field-grown versus greenhouse-grown plants). Results showed that RT-PCR had the highest sensitivity (0.94) and specificity (0.98) of the three tests. TB had better sensitivity than symptoms for detection of SqVYV infection (0.70 versus 0.32), while the visual assessment of symptoms was more specific than TB and, thus, a better indicator of noninfection (0.98 versus 0.65). With respect to the grouping variables, RT-PCR and TB had better sensitivity but poorer specificity for diagnosing SqVYV infection in crown tissue than it did in vine tissue, whereas symptoms had very poor sensitivity but excellent specificity in both tissues for all cucurbits analyzed in this study. Test performance also varied with habitat and genus but not with distance from the crown. The results given here provide quantitative measurements of test performance for a range of conditions and provide the information needed to interpret test results when tests are used in parallel or serial combination for a diagnosis.


2017 ◽  
Vol 45 (6) ◽  
pp. 824-832 ◽  
Author(s):  
R. Sood ◽  
D. J. Gracie ◽  
M. J. Gold ◽  
N. To ◽  
M. I. Pinto-Sanchez ◽  
...  

Author(s):  
Shahieda Adams ◽  
Rodney Ehrlich ◽  
Roslynn Baatjies ◽  
Nandini Dendukuri ◽  
Zhuoyu Wang ◽  
...  

Background: Given the lack of a gold standard for latent tuberculosis infection (LTBI) and paucity of performance data from endemic settings, we compared test performance of the tuberculin skin test (TST) and two interferon-gamma-release assays (IGRAs) among health-care workers (HCWs) using latent class analysis. The study was conducted in Cape Town, South Africa, a tuberculosis and human immunodeficiency virus (HIV) endemic setting Methods: 505 HCWs were screened for LTBI using TST, QuantiFERON-gold-in-tube (QFT-GIT) and T-SPOT.TB. A latent class model utilizing prior information on test characteristics was used to estimate test performance. Results: LTBI prevalence (95% credible interval) was 81% (71–88%). TST (10 mm cut-point) had highest sensitivity (93% (90–96%)) but lowest specificity (57%, (43–71%)). QFT-GIT sensitivity was 80% (74–91%) and specificity 96% (94–98%), and for TSPOT.TB, 74% (67–84%) and 96% (89–99%) respectively. Positive predictive values were high for IGRAs (90%) and TST (99%). All tests displayed low negative predictive values (range 47–66%). A composite rule using both TST and QFT-GIT greatly improved negative predictive value to 90% (range 80–97%). Conclusion: In an endemic setting a positive TST or IGRA was highly predictive of LTBI, while a combination of TST and IGRA had high rule-out value. These data inform the utility of LTBI-related immunodiagnostic tests in TB and HIV endemic settings.


2002 ◽  
Vol 6 (4) ◽  
pp. 181-187 ◽  
Author(s):  
Dante M. Langhi Junior ◽  
José O. Bordin ◽  
Adauto Castelo ◽  
Stephen D. Walter ◽  
Hélio Moraes-Souza ◽  
...  

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