Early Antiretroviral Therapy Not Associated With Higher Cryptococcal Meningitis Mortality in People With Human Immunodeficiency Virus in High-Income Countries: An International Collaborative Cohort Study.

BACKGROUND: Randomized controlled trials (RCTs) from low- and middle-income settings suggested that early initiation of antiretroviral therapy (ART) leads to higher mortality rates among people with HIV (PWH) who present with cryptococcal meningitis (CM). There is limited information about the impact of ART timing on mortality rates in similar people in high-income settings. METHODS: Data on ART-naive PWH with CM diagnosed from 1994 to 2012 from Europe/North America were pooled from the COHERE, NA-ACCORD, and CNICS HIV cohort collaborations. Follow-up was considered to span from the date of CM diagnosis to earliest of the following: death, last follow-up, or 6 months. We used marginal structural models to mimic an RCT comparing the effects of early (within 14 days of CM) and late (14-56 days after CM) ART on all-cause mortality, adjusting for potential confounders. RESULTS: Of 190 participants identified, 33 (17%) died within 6 months. At CM diagnosis, their median age (interquartile range) was 38 (33-44) years; the median CD4+ T-cell count, 19/µL (10-56/µL); and median HIV viral load, 5.3 (4.9-5.6) log10 copies/mL. Most participants (n = 157 [83%]) were male, and 145 (76%) started ART. Mimicking an RCT, with 190 people in each group, there were 13 deaths among participants with an early ART regimen and 20 deaths among those with a late ART regimen. The crude and adjusted hazard ratios comparing late with early ART were 1.28 (95% confidence interval, .64-2.56) and 1.40 (.66-2.95), respectively. CONCLUSIONS: We found little evidence that early ART was associated with higher mortality rates among PWH presenting with CM in high-income settings, although confidence intervals were wide.

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

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/µl compared with 500 cells/µl 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.

Boosted lopinavir- versus boosted atazanavir-containing regimens and immunologic, virologic, and clinical outcomes: a prospective study of HIV-infected individuals in high-income countries.

BACKGROUND: Current clinical guidelines consider regimens consisting of either ritonavir-boosted atazanavir or ritonavir-boosted lopinavir and a nucleoside reverse transcriptase inhibitor (NRTI) backbone among their recommended and alternative first-line antiretroviral regimens. However, these guidelines are based on limited evidence from randomized clinical trials and clinical experience. METHODS: We compared these regimens with respect to clinical, immunologic, and virologic outcomes using data from prospective studies of human immunodeficiency virus (HIV)-infected individuals in Europe and the United States in the HIV-CAUSAL Collaboration, 2004-2013. Antiretroviral therapy-naive and AIDS-free individuals were followed from the time they started a lopinavir or an atazanavir regimen. We estimated the 'intention-to-treat' effect for atazanavir vs lopinavir regimens on each of the outcomes. RESULTS: A total of 6668 individuals started a lopinavir regimen (213 deaths, 457 AIDS-defining illnesses or deaths), and 4301 individuals started an atazanavir regimen (83 deaths, 157 AIDS-defining illnesses or deaths). The adjusted intention-to-treat hazard ratios for atazanavir vs lopinavir regimens were 0.70 (95% confidence interval [CI], .53-.91) for death, 0.67 (95% CI, .55-.82) for AIDS-defining illness or death, and 0.91 (95% CI, .84-.99) for virologic failure at 12 months. The mean 12-month increase in CD4 count was 8.15 (95% CI, -.13 to 16.43) cells/µL higher in the atazanavir group. Estimates differed by NRTI backbone. CONCLUSIONS: Our estimates are consistent with a lower mortality, a lower incidence of AIDS-defining illness, a greater 12-month increase in CD4 cell count, and a smaller risk of virologic failure at 12 months for atazanavir compared with lopinavir regimens.

Ixazomib Versus Placebo as Postinduction Maintenance Therapy in Newly Diagnosed Multiple Myeloma Patients: An Analysis by Age and Frailty Status of the TOURMALINE-MM4 Study.

BACKGROUND: The TOURMALINE-MM4 trial demonstrated a significant and clinically meaningful progression-free survival (PFS) benefit with ixazomib versus placebo as postinduction maintenance in nontransplant, newly-diagnosed multiple myeloma patients, with a manageable and well-tolerated toxicity profile. MATERIALS AND METHODS: In this subgroup analysis, efficacy and safety were assessed by age (< 65, 65-74, and ≥ 75 years) and frailty status (fit, intermediate-fit, and frail). RESULTS: In this analysis, PFS benefit with ixazomib versus placebo was seen across age subgroups, including patients aged < 65 years (hazard ratio [HR], 0.576; 95% confidence interval [CI], 0.299-1.108; P = .095), 65-74 years (HR, 0.615; 95% CI, 0.467-0.810; P < .001), and ≥ 75 years (HR, 0.740; 95% CI, 0.537-1.019; P = .064). PFS benefit was also seen across frailty subgroups, including fit (HR, 0.530; 95% CI, 0.387-0.727; P < .001), intermediate-fit (HR, 0.746; 95% CI, 0.526-1.058; P = .098), and frail (HR, 0.733; 95% CI, 0.481-1.117; P = .147) patients. With ixazomib versus placebo, rates of grade ≥ 3 treatment-emergent adverse events (TEAEs; 28-44% vs. 10-36%), serious TEAEs (15-29% vs. 3-29%), and discontinuation due to TEAEs (7-19% vs. 5-11%) were higher or similar across age and frailty subgroups, and generally somewhat higher in older age groups and intermediate-fit/frail patients in both arms. Treatment with ixazomib versus placebo did not adversely affect patient-reported quality-of-life scores across age and frailty status subgroups. CONCLUSION: Ixazomib is a feasible and effective maintenance option for prolonging PFS across this heterogeneous patient population.

When to initiate combined antiretroviral therapy to reduce mortality and AIDS-defining illness in HIV-infected persons in developed countries: an observational study.

BACKGROUND: Most clinical guidelines recommend that AIDS-free, HIV-infected persons with CD4 cell counts below 0.350 × 10(9) cells/L initiate combined antiretroviral therapy (cART), but the optimal CD4 cell count at which cART should be initiated remains a matter of debate. OBJECTIVE: To identify the optimal CD4 cell count at which cART should be initiated. DESIGN: Prospective observational data from the HIV-CAUSAL Collaboration and dynamic marginal structural models were used to compare cART initiation strategies for CD4 thresholds between 0.200 and 0.500 × 10(9) cells/L. SETTING: HIV clinics in Europe and the Veterans Health Administration system in the United States. PATIENTS: 20, 971 HIV-infected, therapy-naive persons with baseline CD4 cell counts at or above 0.500 × 10(9) cells/L and no previous AIDS-defining illnesses, of whom 8392 had a CD4 cell count that decreased into the range of 0.200 to 0.499 × 10(9) cells/L and were included in the analysis. MEASUREMENTS: Hazard ratios and survival proportions for all-cause mortality and a combined end point of AIDS-defining illness or death. RESULTS: Compared with initiating cART at the CD4 cell count threshold of 0.500 × 10(9) cells/L, the mortality hazard ratio was 1.01 (95% CI, 0.84 to 1.22) for the 0.350 threshold and 1.20 (CI, 0.97 to 1.48) for the 0.200 threshold. The corresponding hazard ratios were 1.38 (CI, 1.23 to 1.56) and 1.90 (CI, 1.67 to 2.15), respectively, for the combined end point of AIDS-defining illness or death. LIMITATIONS: CD4 cell count at cART initiation was not randomized. Residual confounding may exist. CONCLUSION: Initiation of cART at a threshold CD4 count of 0.500 × 10(9) cells/L increases AIDS-free survival. However, mortality did not vary substantially with the use of CD4 thresholds between 0.300 and 0.500 × 10(9) cells/L.

Effectiveness of early antiretroviral therapy initiation to improve survival among HIV-infected adults with tuberculosis: a retrospective cohort study.

BACKGROUND: Randomized clinical trials examining the optimal time to initiate combination antiretroviral therapy (cART) in HIV-infected adults with sputum smear-positive tuberculosis (TB) disease have demonstrated improved survival among those who initiate cART earlier during TB treatment. Since these trials incorporated rigorous diagnostic criteria, it is unclear whether these results are generalizable to the vast majority of HIV-infected patients with TB, for whom standard diagnostic tools are unavailable. We aimed to examine whether early cART initiation improved survival among HIV-infected adults who were diagnosed with TB in a clinical setting. METHODS AND FINDINGS: We retrospectively reviewed charts for 308 HIV-infected adults in Rwanda with a CD4 count ≤ 350 cells/µl and a TB diagnosis. We estimated the effect of cART on survival using marginal structural models and simulated 2-y survival curves for the cohort under different cART strategies:start cART 15, 30, 60, or 180 d after TB treatment or never start cART. We conducted secondary analyses with composite endpoints of (1) death, default, or lost to follow-up and (2) death, hospitalization, or serious opportunistic infection. Early cART initiation led to a survival benefit that was most marked for individuals with low CD4 counts. For individuals with CD4 counts of 50 or 100 cells/µl, cART initiation at day 15 yielded 2-y survival probabilities of 0.82 (95% confidence interval: [0.76, 0.89]) and 0.86 (95% confidence interval: [0.80, 0.92]), respectively. These were significantly higher than the probabilities computed under later start times. Results were similar for the endpoint of death, hospitalization, or serious opportunistic infection. cART initiation at day 15 versus later times was protective against death, default, or loss to follow-up, regardless of CD4 count. As with any observational study, the validity of these findings assumes that biases from residual confounding by unmeasured factors and from model misspecification are small. CONCLUSIONS: Early cART reduced mortality among individuals with low CD4 counts and improved retention in care, regardless of CD4 count. Please see later in the article for the Editors' Summary.

Real-world outcomes and factors impacting treatment choice in relapsed and/or refractory multiple myeloma (RRMM): a comparison of VRd, KRd, and IRd.

Lack of head-to-head trials highlights a need for comparative real-world evidence of proteasome inhibitors plus Rd.Methods: In this retrospective, US population-representative EHR study of RRMM patients initiating IRd, KRd, or VRd in line of therapy (LOT) ≥2 between 1/2014 and 9/30/2018, 664 patients were treated in LOT ≥2 with: IRd, n = 168; KRd, n = 208; VRd, n = 357. Median age was 71/65/71 years; 67%/70%/75% had a frailtymodified score of intermediate/frail; 20%/28%/13% had high cytogenetic risk in I-/K-/V-Rd groups. Risk of PI-triplet discontinuation was lower for I- vs. K-Rd (HR: 0.71) and I- vs. V-Rd (HR: 0.85); unadjusted, median TTNTs (months): 12.7/8.6/14.2 (LOT ≥2) and 16.8/9.5/14.6 (LOT 2-3) (I-/K-/V-Rd). Adjusted TTNT was comparable between I-/K-/V-Rd in LOT ≥2 with a TTNT benefit among intermediate/frail patients for I- (HR: 0.70; P=0.04) and V- (HR: 0.73; P<0.05) vs. K-Rd. I/K/V-Rd triplets were comparable in TTNT overall, but IRd and VRd were associated with longer TTNT in intermediate/frail patients than KRd. The results suggest a trial-efficacy/real-world-effectiveness gap, especially for KRd, underlining the limited generalizability of trial results where >50% of patients are excluded. Individualized treatment based on patient characteristics, such as frailty status, is especially pertinent in an elderly RRMM population.

Effect of highly active antiretroviral therapy on incident AIDS using calendar period as an instrumental variable.

Human immunodeficiency virus (HIV) researchers often use calendar periods as an imperfect proxy for highly active antiretroviral therapy (HAART) when estimating the effect of HAART on HIV disease progression. The authors report on 614 HIV-positive homosexual men followed from 1984 to 2007 in 4 US cities. During 5,321 person-years, 268 of 614 men incurred acquired immunodeficiency syndrome, 49 died, and 90 were lost to follow-up. Comparing the pre-HAART calendar period (<1996) with the HAART calendar period (>or=1996) resulted in a naive rate ratio of 3.62 (95% confidence limits: 2.67, 4.92). However, this estimate is likely biased because of misclassification of HAART use by calendar period. Simple calendar period approaches may circumvent confounding by indication at the cost of inducing exposure misclassification. To correct this misclassification, the authors propose an instrumental-variable estimator analogous to ones previously used for noncompliance corrections in randomized clinical trials. When the pre-HAART calendar period was compared with the HAART calendar period, the instrumental-variable rate ratio was 5.02 (95% confidence limits: 3.45, 7.31), 39% higher than the naive result. Weighting by the inverse probability of calendar period given age at seroconversion, race/ethnicity, and time since seroconversion did not appreciably alter the results. These methods may help resolve discrepancies between observational and randomized evidence.

Foot morphology and foot/ankle injury in indoor football.

While the pronated foot is implicated as a risk factor for sports injury in some studies, others suggest that a supinated foot posture increases the risk of overuse lower limb injuries. Athletes in a given sports discipline may tend to have a similar foot morphology, which varies from that observed elsewhere. Further, the foot morphology that is beneficial for performance in a sport may be detrimental with regard to injury. Intra- and inter-rater reliability of the Foot Posture Index (FPI-6) as a measure of foot morphology was determined (ICC (2,1) 0.88 and 0.69 respectively). Thereafter, in a prospective cohort study using the FPI-6, 76 adolescent male indoor football (Futsal) players were measured and followed monthly over one competition season. Coach-rated ability and reports of any overuse injuries at the ankle and/or foot over this period were obtained. A significant negative linear relationship was found between the mean FPI-6 scores and coach-rated ability (p=0.008), with supinated and under-pronated postures related to higher ability level. Overall, 33% of injuries at the ankle and/or foot were classified as overuse. Foot Posture Index scores of less than 2, indicating the supinated and under-pronated feet, were found to be associated with a significant increase in the risk of overuse injury (p=0.008). The greater rigidity of these foot types may assist adolescent, male, indoor football players to perform at a higher level in their sport. Unfortunately, these players are also more likely to sustain ankle and/or foot overuse injuries.

Comparison of dynamic monitoring strategies based on CD4 cell counts in virally suppressed, HIV-positive individuals on combination antiretroviral therapy in high-income countries: a prospective, observational study.

BACKGROUND: Clinical 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. METHODS: In 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. FINDINGS: 47 635 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. INTERPRETATION: Decreasing 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. FUNDING: National Institutes of Health.

Efavirenz versus boosted atazanavir-containing regimens and immunologic, virologic, and clinical outcomes: A prospective study of HIV-positive individuals.

OBJECTIVE: To compare regimens consisting of either ritonavir-boosted atazanavir or efavirenz and a nucleoside reverse transcriptase inhibitor (NRTI) backbone with respect to clinical, immunologic, and virologic outcomes. DESIGN: Prospective studies of human immunodeficiency virus (HIV)-infected individuals in Europe and the United States included in the HIV-CAUSAL Collaboration. METHODS: HIV-positive, antiretroviral therapy-naive, and acquired immune deficiency syndrome (AIDS)-free individuals were followed from the time they started an atazanavir or efavirenz regimen. We estimated an analog of the "intention-to-treat" effect for efavirenz versus atazanavir regimens on clinical, immunologic, and virologic outcomes with adjustment via inverse probability weighting for time-varying covariates. RESULTS: A total of 4301 individuals started an atazanavir regimen (83 deaths, 157 AIDS-defining illnesses or deaths) and 18,786 individuals started an efavirenz regimen (389 deaths, 825 AIDS-defining illnesses or deaths). During a median follow-up of 31 months, the hazard ratios (95% confidence intervals) were 0.98 (0.77, 1.24) for death and 1.09 (0.91, 1.30) for AIDS-defining illness or death comparing efavirenz with atazanavir regimens. The 5-year survival difference was 0.1% (95% confidence interval: -0.7%, 0.8%) and the AIDS-free survival difference was -0.3% (-1.2%, 0.6%). After 12 months, the mean change in CD4 cell count was 20.8 (95% confidence interval: 13.9, 27.8) cells/mm lower and the risk of virologic failure was 20% (14%, 26%) lower in the efavirenz regimens. CONCLUSION: Our estimates are consistent with a smaller 12-month increase in CD4 cell count, and a smaller risk of virologic failure at 12 months for efavirenz compared with atazanavir regimens. No overall differences could be detected with respect to 5-year survival or AIDS-free survival.

When to Monitor CD4 Cell Count and HIV RNA to Reduce Mortality and AIDS-Defining Illness in Virologically Suppressed HIV-Positive Persons on Antiretroviral Therapy in High-Income Countries: A Prospective Observational Study.

OBJECTIVE: To illustrate an approach to compare CD4 cell count and HIV-RNA monitoring strategies in HIV-positive individuals on antiretroviral therapy (ART). DESIGN: Prospective studies of HIV-positive individuals in Europe and the USA in the HIV-CAUSAL Collaboration and The Center for AIDS Research Network of Integrated Clinical Systems. METHODS: Antiretroviral-naive individuals who initiated ART and became virologically suppressed within 12 months were followed from the date of suppression. We compared 3 CD4 cell count and HIV-RNA monitoring strategies: once every (1) 3 ± 1 months, (2) 6 ± 1 months, and (3) 9-12 ± 1 months. We used inverse-probability weighted models to compare these strategies with respect to clinical, immunologic, and virologic outcomes. RESULTS: In 39,029 eligible individuals, there were 265 deaths and 690 AIDS-defining illnesses or deaths. Compared with the 3-month strategy, the mortality hazard ratios (95% CIs) were 0.86 (0.42 to 1.78) for the 6 months and 0.82 (0.46 to 1.47) for the 9-12 month strategy. The respective 18-month risk ratios (95% CIs) of virologic failure (RNA >200) were 0.74 (0.46 to 1.19) and 2.35 (1.56 to 3.54) and 18-month mean CD4 differences (95% CIs) were -5.3 (-18.6 to 7.9) and -31.7 (-52.0 to -11.3). The estimates for the 2-year risk of AIDS-defining illness or death were similar across strategies. CONCLUSIONS: Our findings suggest that monitoring frequency of virologically suppressed individuals can be decreased from every 3 months to every 6, 9, or 12 months with respect to clinical outcomes. Because effects of different monitoring strategies could take years to materialize, longer follow-up is needed to fully evaluate this question.

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

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.

Are all biases missing data problems?

Estimating causal effects is a frequent goal of epidemiologic studies. Traditionally, there have been three established systematic threats to consistent estimation of causal effects. These three threats are bias due to confounders, selection, and measurement error. Confounding, selection, and measurement bias have typically been characterized as distinct types of biases. However, each of these biases can also be characterized as missing data problems that can be addressed with missing data solutions. Here we describe how the aforementioned systematic threats arise from missing data as well as review methods and their related assumptions for reducing each bias type. We also link the assumptions made by the reviewed methods to the missing completely at random (MCAR) and missing at random (MAR) assumptions made in the missing data framework that allow for valid inferences to be made based on the observed, incomplete data.

Antiretroviral penetration into the CNS and incidence of AIDS-defining neurologic conditions.

OBJECTIVE: The link between CNS penetration of antiretrovirals and AIDS-defining neurologic disorders remains largely unknown. METHODS: HIV-infected, antiretroviral therapy-naive individuals in the HIV-CAUSAL Collaboration who started an antiretroviral regimen were classified according to the CNS Penetration Effectiveness (CPE) score of their initial regimen into low (<8), medium (8-9), or high (>9) CPE score. We estimated "intention-to-treat" hazard ratios of 4 neuroAIDS conditions for baseline regimens with high and medium CPE scores compared with regimens with a low score. We used inverse probability weighting to adjust for potential bias due to infrequent follow-up. RESULTS: A total of 61,938 individuals were followed for a median (interquartile range) of 37 (18, 70) months. During follow-up, there were 235 cases of HIV dementia, 169 cases of toxoplasmosis, 128 cases of cryptococcal meningitis, and 141 cases of progressive multifocal leukoencephalopathy. The hazard ratio (95% confidence interval) for initiating a combined antiretroviral therapy regimen with a high vs low CPE score was 1.74 (1.15, 2.65) for HIV dementia, 0.90 (0.50, 1.62) for toxoplasmosis, 1.13 (0.61, 2.11) for cryptococcal meningitis, and 1.32 (0.71, 2.47) for progressive multifocal leukoencephalopathy. The respective hazard ratios (95% confidence intervals) for a medium vs low CPE score were 1.01 (0.73, 1.39), 0.80 (0.56, 1.15), 1.08 (0.73, 1.62), and 1.08 (0.73, 1.58). CONCLUSIONS: We estimated that initiation of a combined antiretroviral therapy regimen with a high CPE score increases the risk of HIV dementia, but not of other neuroAIDS conditions.

The effect of efavirenz versus nevirapine-containing regimens on immunologic, virologic and clinical outcomes in a prospective observational study.

OBJECTIVE: To compare regimens consisting of either efavirenz or nevirapine and two or more nucleoside reverse transcriptase inhibitors (NRTIs) among HIV-infected, antiretroviral-naive, and AIDS-free individuals with respect to clinical, immunologic, and virologic outcomes. DESIGN: Prospective studies of HIV-infected individuals in Europe and the US included in the HIV-CAUSAL Collaboration. METHODS: Antiretroviral therapy-naive and AIDS-free individuals were followed from the time they started an NRTI, efavirenz or nevirapine, classified as following one or both types of regimens at baseline, and censored when they started an ineligible drug or at 6 months if their regimen was not yet complete. We estimated the 'intention-to-treat' effect for nevirapine versus efavirenz regimens on clinical, immunologic, and virologic outcomes. Our models included baseline covariates and adjusted for potential bias introduced by censoring via inverse probability weighting. RESULTS: A total of 15 336 individuals initiated an efavirenz regimen (274 deaths, 774 AIDS-defining illnesses) and 8129 individuals initiated a nevirapine regimen (203 deaths, 441 AIDS-defining illnesses). The intention-to-treat hazard ratios [95% confidence interval (CI)] for nevirapine versus efavirenz regimens were 1.59 (1.27, 1.98) for death and 1.28 (1.09, 1.50) for AIDS-defining illness. Individuals on nevirapine regimens experienced a smaller 12-month increase in CD4 cell count by 11.49 cells/µl and were 52% more likely to have virologic failure at 12 months as those on efavirenz regimens. CONCLUSIONS: Our intention-to-treat estimates are consistent with a lower mortality, a lower incidence of AIDS-defining illness, a larger 12-month increase in CD4 cell count, and a smaller risk of virologic failure at 12 months for efavirenz compared with nevirapine.

Comparative effectiveness of dynamic treatment regimes: an application of the parametric g-formula.

Ideally, randomized trials would be used to compare the long-term effectiveness of dynamic treatment regimes on clinically relevant outcomes. However, because randomized trials are not always feasible or timely, we often must rely on observational data to compare dynamic treatment regimes. An example of a dynamic treatment regime is "start combined antiretroviral therapy (cART) within 6 months of CD4 cell count first dropping below x cells/mm3 or diagnosis of an AIDS-defining illness, whichever happens first" where x can take values between 200 and 500. Recently, Cain et al (2011) used inverse probability (IP) weighting of dynamic marginal structural models to find the x that minimizes 5-year mortality risk under similar dynamic regimes using observational data. Unlike standard methods, IP weighting can appropriately adjust for measured time-varying confounders (e.g., CD4 cell count, viral load) that are affected by prior treatment. Here we describe an alternative method to IP weighting for comparing the effectiveness of dynamic cART regimes: the parametric g-formula. The parametric g-formula naturally handles dynamic regimes and, like IP weighting, can appropriately adjust for measured time-varying confounders. However, estimators based on the parametric g-formula are more efficient than IP weighted estimators. This is often at the expense of more parametric assumptions. Here we describe how to use the parametric g-formula to estimate risk by the end of a user-specified follow-up period under dynamic treatment regimes. We describe an application of this method to answer the "when to start" question using data from the HIV-CAUSAL Collaboration.

When to start treatment? A systematic approach to the comparison of dynamic regimes using observational data.

Dynamic treatment regimes are the type of regime most commonly used in clinical practice. For example, physicians may initiate combined antiretroviral therapy the first time an individual's recorded CD4 cell count drops below either 500 cells/mm3 or 350 cells/mm3. This paper describes an approach for using observational data to emulate randomized clinical trials that compare dynamic regimes of the form "initiate treatment within a certain time period of some time-varying covariate first crossing a particular threshold." We applied this method to data from the French Hospital database on HIV (FHDH-ANRS CO4), an observational study of HIV-infected patients, in order to compare dynamic regimes of the form "initiate treatment within m months after the recorded CD4 cell count first drops below x cells/mm3" where x takes values from 200 to 500 in increments of 10 and m takes values 0 or 3. We describe the method in the context of this example and discuss some complications that arise in emulating a randomized experiment using observational data.

Inverse probability-of-censoring weights for the correction of time-varying noncompliance in the effect of randomized highly active antiretroviral therapy on incident AIDS or death.

In 1996-1997, the AIDS Clinical Trial Group 320 study randomized 1156 HIV-infected U.S. patients to combination antiretroviral therapy (ART) or highly active ART with equal probability. Ninety-six patients incurred AIDS or died, 51 (4 per cent) dropped out, and 290 (= 51 + 239, 25 per cent) dropped out or stopped their assigned therapy for reasons other than toxicity during a 52-week follow-up. Such noncompliance likely results in null-biased estimates of intent-to-treat hazard ratios (HR) of AIDS or death comparing highly active ART with combination ART, which were 0.75 (95 per cent confidence limits [CL]: 0.43, 1.31), 0.30 (95 per cent CL: 0.15, 0.60), and 0.51 (95 per cent CL: 0.33, 0.77) for follow-up within 15 weeks, beyond 15 weeks, and overall, respectively. Noncompliance correction using Robins and Finkelstein's (RF) inverse probability-of-censoring weights (where participants are censored at dropout or when first noncompliant) yielded estimated HR of 0.46 (95 per cent CL: 0.25, 0.85), 0.43 (95 per cent CL: 0.19, 0.96), and 0.45 (95 per cent CL: 0.27, 0.74) for follow-up within 15 weeks, beyond 15 weeks, and overall, respectively. Weights were estimated conditional on measured age, sex, race, ethnicity, prior Zidovudine use, randomized arm, baseline and time-varying CD4 cell count, and time-varying HIV-related symptoms. Noncompliance corrected results were 63 and 13 per cent farther from the null value of one than intent-to-treat results within 15 weeks and overall, respectively, and resolve the apparent non-proportionality in intent-to-treat results. Inverse probability-of-censoring weighted methods could help to resolve discrepancies between compliant and noncompliant randomized evidence, as well as between randomized and observational evidence, in a variety of biomedical fields.