Dataset Information

Impact of Isoniazid Preventive Therapy on Tuberculosis incidence among people living with HIV: A secondary data analysis using Inverse Probability Weighting of individuals attending HIV care and treatment clinics in Tanzania.

ABSTRACT:

Background

Information on how well Isoniazid Preventive Therapy (IPT) works on reducing TB incidence among people living with HIV (PLHIV) in routine settings using robust statistical methods to establish causality in observational studies is scarce.

Objectives

To evaluate the effectiveness of IPT in routine clinical settings by comparing TB incidence between IPT and non-IPT groups.

Methods

We used data from PLHIV enrolled in 315 HIV care and treatment clinic from January 2012 to December 2016. We used Inverse Probability of Treatment Weighting to adjust for the probability of receiving IPT; balancing the baseline covariates between IPT and non-IPT groups. The effectiveness of IPT on TB incidence was estimated using Cox regression using the weighted sample.

Results

Of 171,743 PLHIV enrolled in the clinics over the five years, 10,326 (6.01%) were excluded leaving 161,417 available for the analysis. Of the 24,800 who received IPT, 1.00% developed TB disease whereas of the 136,617 who never received IPT 6,085 (4.98%) developed TB disease. In 278,545.90 person-years of follow up, a total 7,052 new TB cases were diagnosed. Using the weighted sample, the overall TB incidence was 11.57 (95% CI: 11.09-12.07) per 1,000 person-years. The TB incidence among PLHIV who received IPT was 10.49 (95% CI: 9.11-12.15) per 1,000 person-years and 12.00 (95% CI: 11.69-12.33) per 1,000 person-years in those who never received IPT. After adjusting for other covariates there was 52% lower risk of developing TB disease among those who received IPT compared to those who never received IPT: aHR = 0.48 (95% CI: 0.40-0.58, P<0.001).

Conclusion

IPT reduced TB incidence by 52% in PLHIV attending routine CTC in Tanzania. IPTW adjusted the groups for imbalances in the covariates associated with receiving IPT to achieve comparable groups of IPT and non-IPT. This study has added evidence on the effectiveness of IPT in routine clinical settings and on the use of IPTW to determine impact of interventions in observational studies.

SUBMITTER: Maokola WM

PROVIDER: S-EPMC8277069 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Study questionDoes inverse probability weighting (IPW) provide a more valid estimate of the cumulative incidence of live birth after multiple cycles of IVF?Summary answerIPW can provide a more accurate estimate of treatment success for counseling and decision-making regarding IVF.What is known alreadyDifferent approaches have been used to define and calculate IVF success; however, many of these approaches have limitations and potentially violate statistical assumptions. IPW can address potential selection bias that arises when people do not continue IVF treatment after a failed cycle.Study design, size, durationData were derived from a cohort study of women undergoing their first fresh embryo transfer IVF cycle at our institution between 1 January 1995 and 31 December 2014. All autologous cycles (fresh and frozen) were included, up to six total cycles.Participants/materials, setting, methodsWe identified 20 015 women who underwent 47 079 IVF cycles and had 10 031 live births during the study period. The cumulative incidence of live birth was calculated using three approaches. First, we used a standard Kaplan-Meier approach, 'the optimistic approach', censoring women when they dropped out of treatment. Second, we used a 'conservative' Kaplan-Meier approach that assumed women who dropped out of treatment did not achieve a live birth. Finally, we used IPW to calculate the probability of remaining in treatment, while accounting for differences in treatment drop out. IPW up-weights the data of those remaining under observation who resembled the women who dropped out of treatment, thereby decreasing the potential selection bias resulting from loss to follow-up. The IPW was incorporated into a Kaplan-Meier approach.Main results and the role of chanceThe cumulative incidence of live birth was 72.1% (95% CI: 71.0-73.1%) for the optimistic approach, 50.1% (49.4-50.8%) for the conservative approach and 66.8% (65.5-68.1%) for the IPW approach. Among women < 38 years of age, the cumulative incidence of live birth calculated by the IPW was slightly higher than that calculated by the optimistic approach. For women 41-42 years of age, the IPW cumulative incidence of live birth was slightly lower. The IPW was similar to the optimistic approach for the other age groups. The conservative estimate was lowest for all age groups.Limitations, reasons for cautionOnly clinical data recorded by the providers during an IVF cycle were used to generate weights for IPW. Covariates included: age, gravidity and year at the start of the cycle; primary infertility diagnosis; procedure type (i.e. whether a fresh or frozen embryo was transferred); number of mature oocytes retrieved; number of embryos transferred; cycle cancellation; pregnancy loss in the cycle; and insurance status. We were unable to determine exact reasons for treatment drop out (e.g. cessation of IVF treatment, transfer to another institution or spontaneous pregnancy). Our IPW model was moderately predictive based on the c-statistic from the calculation of the denominator of the weight; however, residual selection bias may remain due to the limited range of covariate data.Wider implications of the findingsIPW can be used in a variety of settings to address selection bias introduced by differential loss to follow up or treatment drop out.Study funding/competing interest(s)AMM was supported by National Institutes of Health (NIH) T32 HD052458-Boston University Reproductive, Perinatal and Pediatric Epidemiology Training Program. The authors report no conflicts of interest.Trial registration numberN/A.