Outcomes of antiretroviral therapy in the Swiss HIV Cohort Study: latent class analysis

An in-depth understanding of the different groups that make up the HIV-infected population should inform prevention and care. Using latent class analysis (LCA) we identified seven groups with similar socio-demographic and behavioral characteristics at enrolment in the Swiss HIV Cohort Study: older gay men, younger gay men, older heterosexual men, injection drug users, single migrants, migrant women in partnerships and heterosexual men and women. Outcomes of combination antiretroviral therapy (ART) were analyzed in 1,633 patients starting ART. Compared to older gay men, the probability of a virologic response to ART was reduced in single migrants, in older heterosexual men and in IDUs. Loss to follow-up was higher in single migrants and IDUs, and mortality was increased in older heterosexual men and IDUs. Socio-behavioral groups identified by LCA allow insights above what can be gleaned from traditional transmission groups, and may identify patients who could benefit from targeted interventions.

Portal levels of latent transforming growth factor-β are related to liver function in patients with liver cirrhosis

Transforming growth factor-β1 (TGFβ1) is a short-lived immune suppressive and profibrotic protein. Its latent precursor is relatively stable and may even protect from fibrosis. Latent TGFβ1 is synthesized by various tissues including the liver and portal, hepatic, and systemic concentrations of latent TGFβ1 were determined in patients with liver cirrhosis and patients with normal liver function to find out whether circulating levels are affected by liver disease.

Improved sensitivity of an interferon-gamma release assay (T-SPOT.TB™) in combination with tuberculin skin test for the diagnosis of latent tuberculosis in the presence of HIV co-infection

Background Interferon-gamma release assays (IGRA) are more specific than the tuberculin skin test (TST) for the diagnosis of Mycobacterium tuberculosis infection. Data on sensitivity are controversial in HIV infection. Methods IGRA (T-SPOT.TB) was performed using lymphocytes stored within 6 months before culture-confirmed tuberculosis was diagnosed in HIV-infected individuals in the Swiss HIV Cohort Study. Results 64 individuals (69% males, 45% of non-white ethnicity, median age 35 years (interquartile range [IQR] 31-42), 28% with prior AIDS) were analysed. Median CD4 cell count was 223 cells/μl (IQR 103-339), HIV-RNA was 4.7 log10 copies/mL (IQR 4.3-5.2). T-SPOT.TB resulted positive in 25 patients (39%), negative in 18 (28%) and indeterminate in 21 (33%), corresponding to a sensitivity of 39% (95% CI 27-51%) if all test results were considered, and 58% (95% CI 43-74%) if indeterminate results were excluded. Sensitivity of IGRA was independent of CD4 cell count (p = 0.698). Among 44 individuals with available TST, 22 (50%) had a positive TST. Agreement between TST and IGRA was 57% (kappa = 0.14, p = 0.177), and in 34% (10/29) both tests were positive. Combining TST and IGRA (at least one test positive) resulted in an improved sensitivity of 67% (95% CI 52-81%). In multivariate analysis, older age was associated with negative results of TST and T-SPOT.TB (OR 3.07, 95% CI 1,22-7.74, p = 0.017, per 10 years older). Conclusions T-SPOT.TB and TST have similar sensitivity to detect latent TB in HIV-infected individuals. Combining TST and IGRA may help clinicians to better select HIV-infected individuals with latent tuberculosis who qualify for preventive treatment.

CYP2E1 genotype and isoniazid-induced hepatotoxicity in patients treated for latent tuberculosis

OBJECTIVE: To determine whether pharmacogenetic tests such as N-acetyltransferase 2 (NAT2) and cytochrome P450 2E1 (CYP2E1) genotyping are useful in identifying patients prone to antituberculosis drug-induced hepatotoxicity in a cosmopolite population. METHODS: In a prospective study we genotyped 89 patients treated with isoniazid (INH) for latent tuberculosis. INH-induced hepatitis (INH-H) or elevated liver enzymes including hepatitis (INH-ELE) was diagnosed based on the clinical diagnostic scale (CDS) designed for routine clinical practice. NAT2 genotypes were assessed by fluorescence resonance energy transfer probe after PCR analysis, and CYP2E1 genotypes were determined by PCR with restriction fragment length polymorphism analysis. RESULTS: Twenty-six patients (29%) had INH-ELE, while eight (9%) presented with INH-H leading to INH treatment interruption. We report no significant influence of NAT2 polymorphism, but we did find a significant association between the CYP2E1 *1A/*1A genotype and INH-ELE (OR: 3.4; 95% CI:1.1-12; p = 0.02) and a non significant trend for INH-H (OR: 5.9; 95% CI: 0.69-270; p = 0.13) compared with other CYP2E1 genotypes. This test for predicting INH-ELE had a positive predictive value (PPV) of 39% (95% CI: 26-54%) and a negative predictive value (NPV) of 84% (95% CI: 69-94%). CONCLUSION: The genotyping of CYP2E1 polymorphisms may be a useful predictive tool in the common setting of a highly heterogeneous population for predicting isoniazid-induced hepatic toxicity. Larger prospective randomized trials are needed to confirm these results.

Detection of latent tuberculosis in immunosuppressed patients with autoimmune diseases: performance of a Mycobacterium tuberculosis antigen-specific interferon gamma assay

OBJECTIVE: To analyse the performance of a new M. tuberculosis-specific interferon gamma (IFNgamma) assay in patients with chronic inflammatory diseases who receive immunosuppressive drugs, including tumour necrosis factor alpha (TNFalpha) inhibitors. METHODS: Cellular immune responses to the M. tuberculosis-specific antigens ESAT-6, CFP-10, TB7.7 were prospectively studied in 142 consecutive patients treated for inflammatory rheumatic conditions. Results were compared with tuberculin skin tests (TSTs). Association of both tests with risk factors for latent M. tuberculosis infection (LTBI) and BCG vaccination were determined and the influence of TNFalpha inhibitors, corticosteroids, and disease modifying antirheumatic drugs (DMARDs) on antigen-specific and mitogen-induced IFNgamma secretion was analysed. RESULTS: 126/142 (89%) patients received immunosuppressive therapy. The IFNgamma assay was more closely associated with the presence of risk factors (odds ratio (OR) = 23.8 (95% CI 5.14 to 110) vs OR = 2.77 (1.22 to 6.27), respectively; p = 0.009), but less associated with BCG vaccination than the TST (OR = 0.47 (95% CI 0.15 to 1.47) vs OR = 2.44 (0.74 to (8.01), respectively; p = 0.025). Agreement between the IFNgamma assay and TST results was low (kappa = 0.17; 95% CI 0.02 to 0.32). The odds for a positive IFNgamma assay strongly increased with increasing prognostic relevance of LTBI risk factors. Neither corticosteroids nor conventional DMARDs significantly affected IFNgamma responses, but the odds for a positive IFNgamma assay were decreased in patients treated with TNFalpha inhibitors (OR = 0.21 (95% CI 0.07 to 0.63), respectively; p = 0.006). CONCLUSIONS: These results demonstrate that the performance of the M. tuberculosis antigen-specific IFNgamma ELISA is better than the classic TST for detection of LTBI in patients receiving immunosuppressive therapy for treatment of systemic autoimmune disorders.

Distinguishing phenotypes of childhood wheeze and cough using latent class analysis

Airway disease in childhood comprises a heterogeneous group of disorders. Attempts to distinguish different phenotypes have generally considered few disease dimensions. The present study examines phenotypes of childhood wheeze and chronic cough, by fitting a statistical model to data representing multiple disease dimensions. From a population-based, longitudinal cohort study of 1,650 preschool children, 319 with parent-reported wheeze or chronic cough were included. Phenotypes were identified by latent class analysis using data on symptoms, skin-prick tests, lung function and airway responsiveness from two preschool surveys. These phenotypes were then compared with respect to outcome at school age. The model distinguished three phenotypes of wheeze and two phenotypes of chronic cough. Subsequent wheeze, chronic cough and inhaler use at school age differed clearly between the five phenotypes. The wheeze phenotypes shared features with previously described entities and partly reconciled discrepancies between existing sets of phenotype labels. This novel, multidimensional approach has the potential to identify clinically relevant phenotypes, not only in paediatric disorders but also in adult obstructive airway diseases, where phenotype definition is an equally important issue.

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.