Dataset Information

Using observational data to emulate a randomized trial of dynamic treatment-switching strategies: an application to antiretroviral therapy.

ABSTRACT:

Background

When a clinical treatment fails or shows suboptimal results, the question of when to switch to another treatment arises. Treatment switching strategies are often dynamic because the time of switching depends on the evolution of an individual's time-varying covariates. Dynamic strategies can be directly compared in randomized trials. For example, HIV-infected individuals receiving antiretroviral therapy could be randomized to switching therapy within 90 days of HIV-1 RNA crossing above a threshold of either 400 copies/ml (tight-control strategy) or 1000 copies/ml (loose-control strategy).

Methods

We review an approach to emulate a randomized trial of dynamic switching strategies using observational data from the Antiretroviral Therapy Cohort Collaboration, the Centers for AIDS Research Network of Integrated Clinical Systems and the HIV-CAUSAL Collaboration. We estimated the comparative effect of tight-control vs. loose-control strategies on death and AIDS or death via inverse-probability weighting.

Results

Of 43 803 individuals who initiated an eligible antiretroviral therapy regimen in 2002 or later, 2001 met the baseline inclusion criteria for the mortality analysis and 1641 for the AIDS or death analysis. There were 21 deaths and 33 AIDS or death events in the tight-control group, and 28 deaths and 41 AIDS or death events in the loose-control group. Compared with tight control, the adjusted hazard ratios (95% confidence interval) for loose control were 1.10 (0.73, 1.66) for death, and 1.04 (0.86, 1.27) for AIDS or death.

Conclusions

Although our effective sample sizes were small and our estimates imprecise, the described methodological approach can serve as an example for future analyses.

SUBMITTER: Cain LE

PROVIDER: S-EPMC5841611 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Publications

Using observational data to emulate a randomized trial of dynamic treatment-switching strategies: an application to antiretroviral therapy.

Cain Lauren E LE Saag Michael S MS Petersen Maya M May Margaret T MT Ingle Suzanne M SM Logan Roger R Robins James M JM Abgrall Sophie S Shepherd Bryan E BE Deeks Steven G SG John Gill M M Touloumi Giota G Vourli Georgia G Dabis François F Vandenhende Marie-Anne MA Reiss Peter P van Sighem Ard A Samji Hasina H Hogg Robert S RS Rybniker Jan J Sabin Caroline A CA Jose Sophie S Del Amo Julia J Moreno Santiago S Rodríguez Benigno B Cozzi-Lepri Alessandro A Boswell Stephen L SL Stephan Christoph C Pérez-Hoyos Santiago S Jarrin Inma I Guest Jodie L JL D'Arminio Monforte Antonella A Antinori Andrea A Moore Richard R Campbell Colin Nj CN Casabona Jordi J Meyer Laurence L Seng Rémonie R Phillips Andrew N AN Bucher Heiner C HC Egger Matthias M Mugavero Michael J MJ Haubrich Richard R Geng Elvin H EH Olson Ashley A Eron Joseph J JJ Napravnik Sonia S Kitahata Mari M MM Van Rompaey Stephen E SE Teira Ramón R Justice Amy C AC Tate Janet P JP Costagliola Dominique D Sterne Jonathan Ac JA Hernán Miguel A MA

International journal of epidemiology 20161201 6

<h4>Background</h4>When a clinical treatment fails or shows suboptimal results, the question of when to switch to another treatment arises. Treatment switching strategies are often dynamic because the time of switching depends on the evolution of an individual's time-varying covariates. Dynamic strategies can be directly compared in randomized trials. For example, HIV-infected individuals receiving antiretroviral therapy could be randomized to switching therapy within 90 days of HIV-1 RNA crossi ...[more]

PMID: 26721599

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Project description:Background/aimsThere has been growing interest in better understanding the potential of observational research methods in medical product evaluation and regulatory decision-making. Previously, we used linked claims and electronic health record data to emulate two ongoing randomized controlled trials, characterizing the populations and results of each randomized controlled trial prior to publication of its results. Here, our objective was to compare the populations and results from the emulated trials with those of the now-published randomized controlled trials.MethodsThis study compared participants' demographic and clinical characteristics and study results between the emulated trials, which used structured data from OptumLabs Data Warehouse, and the published PRONOUNCE and GRADE trials. First, we examined the feasibility of implementing the baseline participant characteristics included in the published PRONOUNCE and GRADE trials' using real-world data and classified each variable as ascertainable, partially ascertainable, or not ascertainable. Second, we compared the emulated trials and published randomized controlled trials for baseline patient characteristics (concordance determined using standardized mean differences <0.20) and results of the primary and secondary endpoints (concordance determined by direction of effect estimates and statistical significance).ResultsThe PRONOUNCE trial enrolled 544 participants, and the emulated trial included 2226 propensity score-matched participants. In the PRONOUNCE trial publication, one of the 32 baseline participant characteristics was listed as an exclusion criterion on ClinicalTrials.gov but was ultimately not used. Among the remaining 31 characteristics, 9 (29.0%) were ascertainable, 11 (35.5%) were partially ascertainable, and 10 (32.2%) were not ascertainable using structured data from OptumLabs. For one additional variable, the PRONOUNCE trial did not provide sufficient detail to allow its ascertainment. Of the nine variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 6 (66.7%). The primary endpoint of time from randomization to the first major adverse cardiovascular event and secondary endpoints of nonfatal myocardial infarction and stroke were concordant between the emulated trial and published randomized controlled trial. The GRADE trial enrolled 5047 participants, and the emulated trial included 7540 participants. In the GRADE trial publication, 8 of 34 (23.5%) baseline participant characteristics were ascertainable, 14 (41.2%) were partially ascertainable, and 11 (32.4%) were not ascertainable using structured data from OptumLabs. For one variable, the GRADE trial did not provide sufficient detail to allow for ascertainment. Of the eight variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 4 (50.0%). The primary endpoint of time to hemoglobin A1c ≥7.0% was mostly concordant between the emulated trial and the published randomized controlled trial.ConclusionDespite challenges, observational methods and real-world data can be leveraged in certain important situations for a more timely evaluation of drug effectiveness and safety in more diverse and representative patient populations.

Project description:ImportanceObservational (nonexperimental) studies that aim to emulate a randomized trial (ie, the target trial) are increasingly informing medical and policy decision-making, but it is unclear how these studies are reported in the literature. Consistent reporting is essential for quality appraisal, evidence synthesis, and translation of evidence to policy and practice.ObjectiveTo assess the reporting of observational studies that explicitly aimed to emulate a target trial.Evidence reviewWe searched Medline, Embase, PsycINFO, and Web of Science for observational studies published between March 2012 and October 2022 that explicitly aimed to emulate a target trial of a health or medical intervention. Two reviewers double-screened and -extracted data on study characteristics, key predefined components of the target trial protocol and its emulation (eligibility criteria, treatment strategies, treatment assignment, outcome[s], follow-up, causal contrast[s], and analysis plan), and other items related to the target trial emulation.FindingsA total of 200 studies that explicitly aimed to emulate a target trial were included. These studies included 26 subfields of medicine, and 168 (84%) were published from January 2020 to October 2022. The aim to emulate a target trial was explicit in 70 study titles (35%). Forty-three studies (22%) reported use of a published reporting guideline (eg, Strengthening the Reporting of Observational Studies in Epidemiology). Eighty-five studies (43%) did not describe all key items of how the target trial was emulated and 113 (57%) did not describe the protocol of the target trial and its emulation.Conclusion and relevanceIn this systematic review of 200 studies that explicitly aimed to emulate a target trial, reporting of how the target trial was emulated was inconsistent. A reporting guideline for studies explicitly aiming to emulate a target trial may improve the reporting of the target trial protocols and other aspects of these emulation attempts.

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:To investigate the responses to switching to second-line regimens among patients who had received a long-term first-line antiretroviral therapy.Patients switching to second-line regimens from June 2008 to June 2015 were enrolled from an observational cohort. In addition, patients continuing first-line therapy and had a viral load <1000 copies/mL were included as controls in July 2012. All these patients were followed-up for 36 months or until June 2016. The virological, immunological outcomes, and drug resistance were evaluated. Virological failure was defined as viral load ≥1000 copies/mL after 6 months of treatment since the start of the study.There were 304 patients switching to second-line regimens and 46 patients remaining on first-line therapy enrolled while having received first-line therapy for a median of 7.6 years. Patients with plasma viral load (VL) ≥1000 copies/mL before switching to second-line regimens had a sharp decline in the proportion of virological failure with 26.7%, 20.4%, and 17.0% at 12, 24, and 36 months after regimen switch, respectively (trend test, P < .001). Among these patients, individuals with drug resistance (DR) had a better virological responses as compared with those without DR after regimen switching. While patients with VL <1000 copies/mL at inclusion remained a high rate of viral suppression after switching to second-line regimens. So did patients continuing first-line therapy. Among patients with VL ≥1000 copies/mL before switching to second-line regimens, the rates of drug resistance were decreased from 79.4% at inclusion to 7.5% at 36 months of regimen switch, with the proportion of NRTI- and NNRTI-related drug resistance from 67.2% and 79.4% to 5.4% and 7.5%, respectively. No PI-related resistance was found. Having self-reported missing doses within a month at follow-ups were independently associated with virological failure at 36 months of switching.HIV-infected patients had viral load ≥1000 copies/mL at regimen switch after a long duration of first-line therapy had good virological responses to second-line regimens, especially those harbored drug resistant variants at regimen switch. However, patients with suppressive first-line therapy did not appear to benefit virologically from switching to second-line regimens.

Project description:BackgroundWith expanding access to pediatric antiretroviral therapy, several patients in the developing world were switched to the second-line regimen, and some require third-line medications. A delay in a second-line switch is associated with an increased risk of mortality and other undesired therapeutic outcomes, drives up program costs, and challenges the pediatric antiretroviral therapy service. Nevertheless, there remain limited and often conflicting estimates on second-line antiretroviral therapy use during childhood, especially in resource-limited settings like Ethiopia. Thus, this study intended to determine the incidence and predictors of switching to second-line antiretroviral therapy among children.MethodsA retrospective cohort study was conducted by reviewing records of 424 randomly selected children on first-line antiretroviral therapy from January 2014 to December 2018 at public hospitals in the Central and Southern Zones of Tigray, Northern Ethiopia. Data were collected using extraction tool; entered into Epi-data; cleaned, and analyzed by STATA version-14. Kaplan-Meier curve, log-rank test, and life table were used for data description and adjusted hazard ratios and p-value for analysis by Cox proportional hazard regression. Variables at a P-value of ≤0.20 in the bi-variable analysis were taken to multivariable analysis. Finally, statistical significance was declared at a P-value of ≤0.05.Results and conclusionAnalysis was conducted on 424 charts with a total person-time observation of 11686.1 child-months and an incidence switch rate of 5.6 (95%CI: 4.36-7.09) per 1000 child-month-observations. Being orphan [AHR = 2.36; 95%CI: 1.10-5.07], suboptimal adherence [AHR = 2.10; 95% CI: 1.12-3.92], drug toxicity [AHR = 7.05; 95% CI: 3.61-13.75], advanced latest clinical stage [AHR = 2.75; 95%CI: 1.05-7.15], and tuberculosis co-infection at baseline [AHR = 3.08; 95%CI: 1.26-7.51] were significantly associated with switch to second-line antiretroviral therapy regimen. Moreover, a long duration of follow-up [AHR = 0.75; 95% CI: 0.71-0.81] was associated with decreased risk of switching. Hence, it is better to prioritize strengthening the focused evaluation of tuberculosis co-infection and treatment failure with continuous adherence monitoring. Further research is also needed to evaluate the effect of drug resistance.

Project description:BackgroundEvidence on the efficacy of antiretroviral therapy (ART) regimen switches on the mortality of patients with HIV drug resistance (HIVDR) is limited.ObjectiveWe aim to provide policy guidance for ART regimen selection and evaluate the effectiveness of ART regime switches for people living with HIV and HIV-1 drug resistance.MethodsThis retrospective observational cohort study included 179 people living with HIV and HIV-1 drug resistance from 2011 to 2020. The time that participants switched treatment regimens either to protease inhibitor (PI)-based ART regimens (PIs) or nonnucleoside reverse transcriptase inhibitor (NNRTI)-based ART regimens (NNRTIs) was taken as an observation starting point and followed up every 12 months. The parametric g-formula was used to estimate the 5-year risk of mortality under the situations of (1) natural course, (2) immediate switch to NNRTIs, (3) immediate switch to PIs, and (4) if CD4(+) T cells<200 switched to PIs.ResultsThe follow-up time of the 179 patients ranged from 30 to 119 months. The median follow-up time was 90 months. During a follow-up of 15,606 person-months, 27 individuals died in the cohort. The estimated 5-year risk of mortality under natural course, immediate switch to NNRTIs, immediate switch to PIs, and if CD4(+), and switch to PIs if T cells<200 were 11.62% (95% CI 7.82-17.11), 31.88% (95% CI 20.79-44.94), 2.87% (95% CI 0.32-7.07), and 5.30% (95% CI 2.07-10.21), respectively. The risk ratios (RRs) of immediate switch to NNRTIs, immediate switch to PIs, and switch to PIs if CD4(+) T cells<200, compared with natural course mortality rate, were 2.74 (95% CI 2.01-3.47), 0.25 (95% CI: 0.04-0.54), and 0.46 (95% CI 0.22-0.71), respectively. The risk differences were 20.26% (95% CI 10.96-28.61), -8.76% (95% CI -13.34 to -5.09) and -6.32% (95% CI -9.75 to -3.11), respectively.ConclusionsOur study found that a PI-based ART regimen was beneficial for reducing mortality in people living with HIV and HIV-1 drug resistance. More effort should be given to find HIV-1 drug resistance earlier to ensure a timely adjustment to PI-based ART, thereby maximizing the benefit of early switch treatment for people living with HIV and HIV-1 drug resistance.

Dataset Information

Using observational data to emulate a randomized trial of dynamic treatment-switching strategies: an application to antiretroviral therapy.

Background

Methods

Results

Conclusions

Publications

Using observational data to emulate a randomized trial of dynamic treatment-switching strategies: an application to antiretroviral therapy.

Similar Datasets

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