Latent Class Analysis to Classify Patients with Transthyretin Amyloidosis by Signs and Symptoms

Diagnostic Accuracy of the INSHI Consensus Case Definition for the Diagnosis of Paradoxical Tuberculosis-IRIS

BACKGROUND

The diagnosis of paradoxical tuberculosis-associated immune reconstitution inflammatory syndrome (TB-IRIS) relies on characteristic clinical features synthesized as the International Network for the Study of HIV-associated IRIS (INSHI) case definition. There is no confirmatory laboratory test.

SETTING

Site B HIV-TB clinic in Khayelitsha, Cape Town, South Africa.

METHODS

Using data of participants with HIV-associated tuberculosis starting antiretroviral treatment from a prospective trial evaluating prednisone for TB-IRIS prevention, we applied latent class analysis to model a gold standard for TB-IRIS. The model-predicted probability of TB-IRIS for each participant was used to assess the performance of the INSHI case definition and compare its diagnostic accuracy with several adapted case definitions.

RESULTS

Data for this analysis were complete for 217 participants; 41% developed TB-IRIS. Our latent class model included the following parameters: respiratory symptoms; night sweats; INSHI major criteria 1, 2, and 4; maximum C-reactive protein >90 mg/L; maximum heart rate >120/min; maximum temperature >37.7°C; and preantiretroviral therapy CD4 count <50 cells/µL. The model estimated a TB-IRIS incidence of 43% and had optimal goodness of fit (χ2 = 337, P = 1.0). The INSHI case definition displayed a sensitivity of 0.77 and a specificity of 0.86. Replacing all the minor INSHI criteria with objectives measures (C-reactive protein elevation, fever, and/or tachycardia) resulted in a definition with better diagnostic accuracy, with a sensitivity of 0.89 and a specificity of 0.88.

CONCLUSION

The INSHI case definition identifies TB-IRIS with reasonable accuracy. Amending the case definition by replacing INSHI minor criteria with objective variables improved sensitivity without loss of specificity.