Adjusting the effect of integrating antiretroviral therapy and tuberculosis treatment on mortality for non-compliance : an instrumental variables analysis using a time-varying exposure.
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Date
2018
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Abstract
In South Africa and elsewhere, research has shown that the integration of antiretroviral therapy
(ART) and tuberculosis (TB) treatment saves lives. The randomised controlled trials (RCTs)
which provided this compelling evidence used intent-to-treat (ITT) strategy as part of their primary
analysis. As much as ITT is protected against selection bias caused by both measured and
unmeasured confounders, but it is capable of drawing results towards the null and underestimate
the e ectiveness of treatment if there is too much non-compliance. To adjust for non-compliance,
\as-treated"and \per-protocol"comparisons are commonly made. These contrast study participants
according to their received treatment, regardless of the treatment arm to which they
were assigned, or limit the analysis to participants who followed the protocol. Such analyses are
generally biased because the subgroups which they compare often lack comparability.
In view of the shortcomings of the \as-treated"and \per-protocol"analyses, our objective was
to account for non-compliance by using instrumental variables (IV) analysis to estimate the
e ect of ART initiation during TB treatment on mortality. Furthermore, to capture the full
complexity of compliance behaviour outside the TB treatment duration, we developed a novel
IV-methodology for a time-varying measure of compliance to ART. This is an important contribution
to the IV literature since IV-methodology for the e ect of a time-varying exposure
on a time-to-event endpoint is currently lacking. In RCTs, IV analysis enable us to make use
of the comparability o ered by randomisation and thereby have the capability of adjusting for
unmeasured and measured confounders; they have the further advantage of yielding results that
are less sensitive to random measurement error in the exposure.
In order to carry out IV analysis, one needs to identify a variable called an instrument, which
needs to satisfy three important assumptions. To apply the IV methodology, we used data from
Starting Antiretroviral Therapy at Three Points in Tuberculosis (SAPiT) trial which was conducted
by the Centre for the AIDS Programme of Research in South Africa. This trial enrolled
HIV and TB co-infected patients who were assigned to start ART either early or late during TB
treatment or after TB treatment completion. The results from IV analysis demonstrate that
survival bene t of fully integrating TB treatment and ART is even higher than what has been
reported in the ITT analysis since non-compliance has been accounted for.
Description
Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.