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Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV-positive individuals.

ABSTRACT: Decisions about when to start or switch a therapy often depend on the frequency with which individuals are monitored or tested. For example, the optimal time to switch antiretroviral therapy depends on the frequency with which HIV-positive individuals have HIV RNA measured. This paper describes an approach to use observational data for the comparison of joint monitoring and treatment strategies and applies the method to a clinically relevant question in HIV research: when can monitoring frequency be decreased and when should individuals switch from a first-line treatment regimen to a new regimen? We outline the target trial that would compare the dynamic strategies of interest and then describe how to emulate it using data from HIV-positive individuals included in the HIV-CAUSAL Collaboration and the Centers for AIDS Research Network of Integrated Clinical Systems. When, as in our example, few individuals follow the dynamic strategies of interest over long periods of follow-up, we describe how to leverage an additional assumption: no direct effect of monitoring on the outcome of interest. We compare our results with and without the "no direct effect" assumption. We found little differences on survival and AIDS-free survival between strategies where monitoring frequency was decreased at a CD4 threshold of 350 cells/?l compared with 500 cells/?l and where treatment was switched at an HIV-RNA threshold of 1000 copies/ml compared with 200 copies/ml. The "no direct effect" assumption resulted in efficiency improvements for the risk difference estimates ranging from an 7- to 53-fold increase in the effective sample size.

SUBMITTER: Caniglia EC

PROVIDER: S-EPMC6499640 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV-positive individuals.

Caniglia Ellen C EC Caniglia Ellen C EC Robins James M JM Cain Lauren E LE Sabin Caroline C Logan Roger R Abgrall Sophie S Mugavero Michael J MJ Hernández-Díaz Sonia S Meyer Laurence L Seng Remonie R Drozd Daniel R DR Seage Iii George R GR Bonnet Fabrice F Le Marec Fabien F Moore Richard D RD Reiss Peter P van Sighem Ard A Mathews William C WC Jarrín Inma I Alejos Belén B Deeks Steven G SG Muga Roberto R Boswell Stephen L SL Ferrer Elena E Eron Joseph J JJ Gill John J Pacheco Antonio A Grinsztejn Beatriz B Napravnik Sonia S Jose Sophie S Phillips Andrew A Justice Amy A Tate Janet J Bucher Heiner C HC Egger Matthias M Furrer Hansjakob H Miro Jose M JM Casabona Jordi J Porter Kholoud K Touloumi Giota G Crane Heidi H Costagliola Dominique D Saag Michael M Hernán Miguel A MA

Statistics in medicine 20190318 13

Decisions about when to start or switch a therapy often depend on the frequency with which individuals are monitored or tested. For example, the optimal time to switch antiretroviral therapy depends on the frequency with which HIV-positive individuals have HIV RNA measured. This paper describes an approach to use observational data for the comparison of joint monitoring and treatment strategies and applies the method to a clinically relevant question in HIV research: when can monitoring frequenc ...[more]

PMID: 30883859

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Project description:BackgroundClinical guidelines vary with respect to the optimal monitoring frequency of HIV-positive individuals. We compared dynamic monitoring strategies based on time-varying CD4 cell counts in virologically suppressed HIV-positive individuals.MethodsIn this observational study, we used data from prospective studies of HIV-positive individuals in Europe (France, Greece, the Netherlands, Spain, Switzerland, and the UK) and North and South America (Brazil, Canada, and the USA) in The HIV-CAUSAL Collaboration and The Centers for AIDS Research Network of Integrated Clinical Systems. We compared three monitoring strategies that differ in the threshold used to measure CD4 cell count and HIV RNA viral load every 3-6 months (when below the threshold) or every 9-12 months (when above the threshold). The strategies were defined by the threshold CD4 counts of 200 cells per μL, 350 cells per μL, and 500 cells per μL. Using inverse probability weighting to adjust for baseline and time-varying confounders, we estimated hazard ratios (HRs) of death and of AIDS-defining illness or death, risk ratios of virological failure, and mean differences in CD4 cell count.Findings47 635 individuals initiated an antiretroviral therapy regimen between Jan 1, 2000, and Jan 9, 2015, and met the eligibility criteria for inclusion in our study. During follow-up, CD4 cell count was measured on average every 4·0 months and viral load every 3·8 months. 464 individuals died (107 in threshold 200 strategy, 157 in threshold 350, and 200 in threshold 500) and 1091 had AIDS-defining illnesses or died (267 in threshold 200 strategy, 365 in threshold 350, and 459 in threshold 500). Compared with threshold 500, the mortality HR was 1·05 (95% CI 0·86-1·29) for threshold 200 and 1·02 (0·91·1·14) for threshold 350. Corresponding estimates for death or AIDS-defining illness were 1·08 (0·95-1·22) for threshold 200 and 1·03 (0·96-1·12) for threshold 350. Compared with threshold 500, the 24 month risk ratios of virological failure (viral load more than 200 copies per mL) were 2·01 (1·17-3·43) for threshold 200 and 1·24 (0·89-1·73) for threshold 350, and 24 month mean CD4 cell count differences were 0·4 (-25·5 to 26·3) cells per μL for threshold 200 and -3·5 (-16·0 to 8·9) cells per μL for threshold 350.InterpretationDecreasing monitoring to annually when CD4 count is higher than 200 cells per μL compared with higher than 500 cells per μL does not worsen the short-term clinical and immunological outcomes of virally suppressed HIV-positive individuals. However, more frequent virological monitoring might be necessary to reduce the risk of virological failure. Further follow-up studies are needed to establish the long-term safety of these strategies.FundingNational Institutes of Health.

Project description:ImportanceWith immune recovery following early initiation of antiretroviral therapy (ART), the risk of tuberculosis (TB) reactivation among individuals with HIV could be reduced. The current strategy of annual latent TB infection (LTBI) testing should be revisited to increase cost-effectiveness and reduce the intensity of testing for individuals.ObjectiveTo analyze the cost-effectiveness of LTBI testing strategies for individuals in Hong Kong with HIV who had negative LTBI test results at baseline.Design, setting, and participantsThis decision analytical model study using a cost-effectiveness analysis included 3130 individuals with HIV in Hong Kong, China, which has an intermediate TB burden and a low incidence of HIV-TB coinfection. A system dynamics model of individuals with HIV attending a major HIV specialist clinic in Hong Kong was developed and parameterized by longitudinal clinical and LTBI testing records of patients during a 15-year period. The study population was stratified by age group, CD4 lymphocyte level, ART status, and right of abode. Alternative strategies for LTBI testing after a baseline test were compared with annual testing under different coverages of ART, LTBI testing, and LTBI treatment scenarios in the model. An annual discounting rate of 3.5% was used in cost-effectiveness analysis.Main outcomes and measuresProportion of new TB cases averted above base case scenario, discounted quality-adjusted life-years gained (QALYG), incremental cost, and incremental cost-effectiveness ratios in 2017 to 2023.ResultsA total of 3130 patients with HIV (2740 [87.5%] male and 2800 [89.5%] younger than 50 years at HIV diagnosis) with 16?630 person-years of follow-up data from 2002 to 2017 were analyzed. Of these, 94 patients (0.67 [95% CI, 0.51-0.91] per 100 person-years) developed TB. Model estimates of cumulative number of TB cases would reach 146 by 2023, with the annual number of new TB diagnoses ranging from 6 to 8. For patients who had negative LTBI test results at baseline, subsequent LTBI testing strategies were ranked by ascending effectiveness as follows: (1) no testing, (2) test by risk factors, (3) biennial testing for all, (4) up to 3 tests for all, and (5) annual testing for all. Applying a willingness-to-pay threshold of $50?000 per QALYG, none of the subsequent testing strategies were cost-effective. Test by risk factors and up to 3 tests for all were cost-effective only if the willingness-to-pay threshold was increased to $100?000 per QALYG and $200?000 per QALYG, respectively. More new TB cases would be averted by expanding LTBI testing and/or treatment coverage.Conclusions and relevanceChanging the current testing strategy to less intense testing strategies is likely to be cost-effective in the presence of an increased coverage of baseline LTBI testing and/or treatment.

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Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV-positive individuals.

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Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV-positive individuals.

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