The Impact of Implementation Fidelity on Mortality Under a CD4-Stratified Timing Strategy for Antiretroviral Therapy in Patients With Tuberculosis

To Adapt or Not to Adapt: The Association between Implementation Fidelity and the Effectiveness of Diabetes Self-Management Education

Self-management education (SME) is a key determinant of diabetes treatment outcomes. While SME programs are often adapted for implementation, the impact of adaptations on diabetes SME effectiveness is not well documented. This study evaluated the impact of the implementation fidelity of diabetes SME programs on program effectiveness, exploring which factors influence implementation fidelity. Data from 33 type 2 diabetes SME program providers and 166 patients were collected in 8 countries (Austria, Belgium, Germany, Ireland, UK, Israel, Taiwan and USA). Program providers completed a questionnaire assessing their adherence to the program protocol and factors that influenced the implementation. Patients answered a pre–post questionnaire assessing their diabetes-related health literacy, self-care behavior, general health and well-being. Associations between implementation fidelity and outcomes were estimated through logistic regressions and repeated measures MANOVA, controlling for potential confounders. Adaptations of the program protocol regarding content, duration, frequency and/or coverage were reported by 39% of the providers and were associated with better, not worse, outcomes than strict adherence. None of the factors related to the participants, facilitating strategies, provider or context systematically influenced the implementation fidelity. Future research should focus on individual and contextual factors that may influence decisions to adapt SME programs for diabetes.

A review of time scale fundamentals in the g-formula and insidious selection bias

PURPOSE OF REVIEW

We review recent examples of data analysis with the g-formula, a powerful tool for analyzing longitudinal data and survival analysis. Specifically, we focus on the common choices of time scale and review inferential issues that may arise.

RECENT FINDINGS

Researchers are increasingly engaged with questions that require time scales subject to left-truncation and right-censoring. The assumptions necessary for allowing right-censoring are well defined in the literature, whereas similar assumptions for left-truncation are not well defined. Policy and biologic considerations sometimes dictate that observational data must be analyzed on time scales that are subject to left-truncation, such as age.

SUMMARY

Further consideration of left-truncation is needed, especially when biologic or policy considerations dictate that age is the relevant time scale of interest. Methodologic development is needed to reduce potential for bias when left-truncation may occur.

Tuberculosis Treatment Outcomes Among HIV/TB-Coinfected Children in the International Epidemiology Databases to Evaluate AIDS (IeDEA) Network

INTRODUCTION

Management of tuberculosis (TB) is challenging in HIV/TB-coinfected children. The World Health Organization recommends nucleic acid amplification tests for TB diagnosis, a 4-drug regimen including ethambutol during intensive phase (IP) of treatment, and initiation of antiretroviral therapy (ART) within 8 weeks of TB diagnosis. We investigated TB treatment outcomes by diagnostic modality, IP regimen, and ART status.

METHODS

We conducted a retrospective cohort study among HIV/TB-coinfected children enrolled at the International Epidemiology Databases to Evaluate AIDS treatment sites from 2012 to 2014. We modeled TB outcome using multivariable logistic regression including diagnostic modality, IP regimen, and ART status.

RESULTS

Among the 386 HIV-infected children diagnosed with TB, 20% had microbiologic confirmation of TB, and 20% had unfavorable TB outcomes. During IP, 78% were treated with a 4-drug regimen. Thirty-one percent were receiving ART at the time of TB diagnosis, and 32% were started on ART within 8 weeks of TB diagnosis. Incidence of ART initiation within 8 weeks of TB diagnosis was higher for those with favorable TB outcomes (64%) compared with those with unfavorable outcomes (40%) (P = 0.04). Neither diagnostic modality (odds ratio 1.77; 95% confidence interval: 0.86 to 3.65) nor IP regimen (odds ratio 0.88; 95% confidence interval: 0.43 to 1.80) was associated with TB outcome.

DISCUSSION

In this multinational study of HIV/TB-coinfected children, many were not managed as per World Health Organization guidelines. Children with favorable TB outcomes initiated ART sooner than children with unfavorable outcomes. These findings highlight the importance of early ART for children with HIV/TB coinfection, and reinforce the need for implementation research to improve pediatric TB management.

An Illustration of Inverse Probability Weighting to Estimate Policy-Relevant Causal Effects

Traditional epidemiologic approaches allow us to compare counterfactual outcomes under 2 exposure distributions, usually 100% exposed and 100% unexposed. However, to estimate the population health effect of a proposed intervention, one may wish to compare factual outcomes under the observed exposure distribution to counterfactual outcomes under the exposure distribution produced by an intervention. Here, we used inverse probability weights to compare the 5-year mortality risk under observed antiretroviral therapy treatment plans to the 5-year mortality risk that would had been observed under an intervention in which all patients initiated therapy immediately upon entry into care among patients positive for human immunodeficiency virus in the US Centers for AIDS Research Network of Integrated Clinical Systems multisite cohort study between 1998 and 2013. Therapy-naïve patients (n = 14,700) were followed from entry into care until death, loss to follow-up, or censoring at 5 years or on December 31, 2013. The 5-year cumulative incidence of mortality was 11.65% under observed treatment plans and 10.10% under the intervention, yielding a risk difference of -1.57% (95% confidence interval: -3.08, -0.06). Comparing outcomes under the intervention with outcomes under observed treatment plans provides meaningful information about the potential consequences of new US guidelines to treat all patients with human immunodeficiency virus regardless of CD4 cell count under actual clinical conditions.

Impact of WHO 2010 Guidelines on Antiretroviral Therapy Initiation among Patients with HIV-Associated Tuberculosis in Clinics with and without Onsite HIV Services in the Democratic Republic of Congo

Background. We assessed the impact of WHO's 2010 guidelines that removed the requirement of CD4 count before ART, on timely initiation of ART among HIV/TB patients in the Democratic Republic of Congo (DRC). Methods. Data collected to monitor implementation of provider initiated HIV testing and counseling (PITC) and linkage to HIV care from 65 and 13 TB clinics in Kinshasa and Kisangani, respectively, between November 2010 and June 2013. Results. Prior to the WHO's 2010 guidelines, in Kinshasa, 79.1% (401/507) of HIV/TB patients referred for HIV services were initiated on ART in clinics with onsite ART services compared to 50.0% (63/123) in clinics without. Following the implementation of the new guidelines, 89.8% (714/795) and 93.0% (345/371) of HIV/TB patients referred for HIV services were initiated on ART, respectively, in clinics with onsite and without onsite ART services. Similarly, in Kisangani, 69.7% (53/120) and 36.4% (16/44) in clinics with and without onsite ART service, respectively, were initiated on ART prior to the 2010 guidelines and 88.8% (135/152) and 72.6% (106/146), respectively, after the new guidelines. Conclusion. Though implementation of the 2010 guidelines increased the proportion of HIV/TB patients initiated on ART substantially, it remained below the 100% target, particularly in clinics without onsite ART services.

HIV treatment cascade in tuberculosis patients

PURPOSE OF REVIEW

Globally, the number of deaths associated with tuberculosis (TB) and HIV coinfection remains unacceptably high. We review the evidence around the impact of strengthening the HIV treatment cascade in TB patients and explore recent findings about how best to deliver integrated TB/HIV services.

RECENT FINDINGS

There is clear evidence that the timely provision of antiretroviral therapy (ART) reduces mortality in TB/HIV coinfected adults. Despite this, globally in 2013, only around a third of known HIV-positive TB cases were treated with ART. Although there is some recent evidence exploring the barriers to achieve high coverage of HIV testing and ART initiation in TB patients, our understanding of which factors are most important and how best to address these within different health systems remains incomplete. There are some examples of good practice in the delivery of integrated TB/HIV services to improve the HIV treatment cascade. However, evidence of the impact of such strategies is of relatively low quality for informing integrated TB/HIV programming more broadly. In most settings, there remain barriers to higher-level organizational and functional integration.

SUMMARY

There remains a need for commitment to patient-centred integrated TB/HIV care in countries affected by the dual epidemic. There is a need for better quality evidence around how best to deliver integrated services to strengthen the HIV treatment cascade in TB patients, both at primary healthcare level and within community settings.

Imputation approaches for potential outcomes in causal inference

BACKGROUND

The fundamental problem of causal inference is one of missing data, and specifically of missing potential outcomes: if potential outcomes were fully observed, then causal inference could be made trivially. Though often not discussed explicitly in the epidemiological literature, the connections between causal inference and missing data can provide additional intuition.

METHODS

We demonstrate how we can approach causal inference in ways similar to how we address all problems of missing data, using multiple imputation and the parametric g-formula.

RESULTS

We explain and demonstrate the use of these methods in example data, and discuss implications for more traditional approaches to causal inference.

CONCLUSIONS

Though there are advantages and disadvantages to both multiple imputation and g-formula approaches, epidemiologists can benefit from thinking about their causal inference problems as problems of missing data, as such perspectives may lend new and clarifying insights to their analyses.