Use of predicted vital status to improve survival analysis of multidrug-resistant tuberculosis cohorts

Tuberculosis treatment loss to follow-up in children exposed at home: A prospective cohort study

Background

Loss to follow-up (LTFU) from tuberculosis (TB) treatment and care is a significant public health problem. It is important to understand what drives LTFU in children - a population whose treatment and management depend on an adult caregiver - to better provide support services to families affected by TB.

Methods

We conducted a prospective cohort study of household contacts in Lima, Peru (2009-12). Using multilevel logistic regression analysis, we explored individual-level characteristics of children and their adult household members with TB disease to identify risk factors for LTFU among children initiated on treatment for TB.

Results

A total of 154 child (0-14 years) household contacts were diagnosed with TB and initiated on treatment. While most (n = 133, 86.4%) had a successful outcome, 20 (13.0%) children were LTFU. Six (30.0%) children were LTFU within three months, nine (45.0%) between five to seven months, and three (15.0%) after seven months of treatment being initiated. In univariable analysis, children with index patients above 25 years of age had decreased odds of being LTFU (odds ratio = 0.26; 95% confidence interval = 0.08-0.84) compared to children with index patients 25 years or younger.

Conclusions

In this cohort, more than 10% of children sick with TB who were exposed to the disease at home were LTFU. An integrated, family-centred TB prevention and management approach may reduce barriers to a child completing their course of TB treatment.

Association of HIV infection and antiretroviral therapy with the occurrence of an unfavorable TB treatment outcome in a rural district hospital in Eastern Cape, South Africa: A retrospective cohort study

Background

Our objective was to assess differences in TB treatment outcomes between individuals who were HIV negative, HIV positive on anti-retroviral treatment (ART) and HIV positive not on ART, at TB treatment initiation at a rural district hospital in Eastern Cape, South Africa.

Methods

This was a retrospective cohort study of individuals diagnosed with TB between January 2017 and April 2020 at a district hospital. Adults 15 years and over with reported HIV status and treatment outcome were included (N = 711). A categorical outcome with three levels was considered: unfavorable, down referral, and success. We report descriptive statistics for the association between HIV and ART status and treatment outcome using Chi-square and Fisher’s exact tests. A multinomial baseline logit model was used to estimate odds ratios for treatment outcomes.

Results

Overall, 59% of included patients were HIV positive with 75% on ART. Eighty-eight patients 12% had an unfavorable outcome. Half of all patients were down referred with an additional 37% having a successful outcome. Individuals without HIV were more likely to be down referred (versus unfavorable) compared to individuals with untreated HIV (2.90 OR, 1.36, 6.17 95% CI). There was a greater likelihood for individuals without HIV having a successful TB treatment outcome compared to individuals with untreated HIV (4.98 OR, 2.07, 11.25 95% CI).

Conclusion

The majority of individuals had positive TB treatment outcomes (down referred or success). However, people without HIV had nearly five times greater odds of having successful outcomes than those with untreated HIV.

A systematic review of the quality of conduct and reporting of survival analyses of tuberculosis outcomes in Africa

BACKGROUND

Survival analyses methods (SAMs) are central to analysing time-to-event outcomes. Appropriate application and reporting of such methods are important to ensure correct interpretation of the data. In this study, we systematically review the application and reporting of SAMs in studies of tuberculosis (TB) patients in Africa. It is the first review to assess the application and reporting of SAMs in this context.

METHODS

Systematic review of studies involving TB patients from Africa published between January 2010 and April 2020 in English language. Studies were eligible if they reported use of SAMs. Application and reporting of SAMs were evaluated based on seven author-defined criteria.

RESULTS

Seventy-six studies were included with patient numbers ranging from 56 to 182,890. Forty-three (57%) studies involved a statistician/epidemiologist. The number of published papers per year applying SAMs increased from two in 2010 to 18 in 2019 (P = 0.004). Sample size estimation was not reported by 67 (88%) studies. A total of 22 (29%) studies did not report summary follow-up time. The survival function was commonly presented using Kaplan-Meier survival curves (n = 51, (67%) studies) and group comparisons were performed using log-rank tests (n = 44, (58%) studies). Sixty seven (91%), 3 (4.1%) and 4 (5.4%) studies reported Cox proportional hazard, competing risk and parametric survival regression models, respectively. A total of 37 (49%) studies had hierarchical clustering, of which 28 (76%) did not adjust for the clustering in the analysis. Reporting was adequate among 4.0, 1.3 and 6.6% studies for sample size estimation, plotting of survival curves and test of survival regression underlying assumptions, respectively. Forty-five (59%), 52 (68%) and 73 (96%) studies adequately reported comparison of survival curves, follow-up time and measures of effect, respectively.

CONCLUSION

The quality of reporting survival analyses remains inadequate despite its increasing application. Because similar reporting deficiencies may be common in other diseases in low- and middle-income countries, reporting guidelines, additional training, and more capacity building are needed along with more vigilance by reviewers and journal editors.

Comparison of censoring assumptions to reduce bias in tuberculosis treatment cohort analyses

Objective

Observational tuberculosis cohort studies are often limited by a lack of long-term data characterizing survival beyond the initial treatment outcome. Though Cox proportional hazards models are often applied to these data, differential risk of long-term survival, dependent on the initial treatment outcome, can lead to violations of model assumptions. We evaluate the performance of two alternate censoring approaches on reducing bias in treatment effect estimates.

Design

We simulate a typical multidrug-resistant tuberculosis cohort study and use Cox proportional hazards models to assess the relationship of an aggressive treatment regimen with hazard of death. We compare three assumptions regarding censored observations to determine which produces least biased treatment effect estimates: conventional non-informative censoring, an extension of short-term survival informed by literature, and incorporation of predicted long-term vital status.

Results

The treatment regimen’s protective effect on death is consistently underestimated by the conventional censoring method, up to 7.6%. Models using the two alternative censoring techniques produce treatment effect estimates consistently stronger and less biased than the conventional method, underestimating the treatment effect by less than 2.4% across all scenarios.

Conclusions

When model assumptions are violated, alternative censoring techniques can more accurately estimate associations between treatment and long-term survival. In multidrug-resistant tuberculosis cohort analyses, this bias reduction may yield more accurate and, larger effect estimates. This bias reduction can be achieved through use of standard statistical procedures with a simple re-coding of the censoring indicator.