Modelling the association between patient characteristics and the change over time in a disease measure using observational cohort data

The Effect of HIV Treatment Interruption on Subsequent Immunological Response

Recovery of CD4-positive T lymphocyte count after initiation of antiretroviral therapy (ART) has been thoroughly examined among people with human immunodeficiency virus infection. However, immunological response after restart of ART following care interruption is less well studied. We compared CD4 cell-count trends before disengagement from care and after ART reinitiation. Data were obtained from the East Africa International Epidemiology Databases to Evaluate AIDS (IeDEA) Collaboration (2001-2011; n = 62,534). CD4 cell-count trends before disengagement, during disengagement, and after ART reinitiation were simultaneously estimated through a linear mixed model with 2 subject-specific knots placed at the times of disengagement and treatment reinitiation. We also estimated CD4 trends conditional on the baseline CD4 value. A total of 10,961 patients returned to care after disengagement from care, with the median gap in care being 2.7 (interquartile range, 2.1-5.4) months. Our model showed that CD4 cell-count increases after ART reinitiation were much slower than those before disengagement. Assuming that disengagement from care occurred 12 months after ART initiation and a 3-month treatment gap, CD4 counts measured at 3 years since ART initiation would be lower by 36.5 cells/μL than those obtained under no disengagement. Given that poorer CD4 restoration is associated with increased mortality/morbidity, specific interventions targeted at better retention in care are urgently required.

Changes in Body Mass Index after Initiation of Antiretroviral Treatment: Differences by Class of Core Drug

Recent research on antiretroviral treatment (ART) for HIV suggests that integrase strand transfer inhibitors (INSTIs) cause faster weight gain compared to other drug classes. Here, we investigated changes in body mass index (BMI) and obesity prevalence after treatment initiation and corresponding differences between drug classes. Data were derived from a large collaborative cohort in Greece. Included individuals were adults who started ART, in or after 2010, while previously ART naïve and achieved virologic response within the first year of ART. Data were analysed using mixed fractional polynomial models. INSTI regimens led to the more pronounced BMI increases, followed by boosted PI and NNRTI based regimens. Individuals with normal initial BMI are expected to gain 6 kg with an INSTI regimen compared to 4 kg with a boosted PI and less than 3 kg with a NNRTI regimen after four years of treatment. Prevalence of obesity was 5.7% at ART initiation and 12.2%, 14.2% and 18.1% after four years of treatment with NNRTIs, PIs, and INSTIs, respectively. Dolutegravir or Raltegravir were associated with marginally faster BMI increase compared to Elvitegravir. INSTIs are associated with faster weight gain. INSTIs' increased risk of treatment emergent obesity and, possibly, weight-related co-morbidities should be judged against their improved efficacy and tolerability but increased clinical attention is required.

Precision MRI phenotyping enables detection of small changes in body composition for longitudinal cohorts

Longitudinal studies provide unique insights into the impact of environmental factors and lifespan issues on health and disease. Here we investigate changes in body composition in 3088 free-living participants, part of the UK Biobank in-depth imaging study. All participants underwent neck-to-knee MRI scans at the first imaging visit and after approximately two years (second imaging visit). Image-derived phenotypes for each participant were extracted using a fully-automated image processing pipeline, including volumes of several tissues and organs: liver, pancreas, spleen, kidneys, total skeletal muscle, iliopsoas muscle, visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue, as well as fat and iron content in liver, pancreas and spleen. Overall, no significant changes were observed in BMI, body weight, or waist circumference over the scanning interval, despite some large individual changes. A significant decrease in grip strength was observed, coupled to small, but statistically significant, decrease in all skeletal muscle measurements. Significant increases in VAT and intermuscular fat in the thighs were also detected in the absence of changes in BMI, waist circumference and ectopic-fat deposition. Adjusting for disease status at the first imaging visit did not have an additional impact on the changes observed. In summary, we show that even after a relatively short period of time significant changes in body composition can take place, probably reflecting the obesogenic environment currently inhabited by most of the general population in the United Kingdom.

A highly virulent variant of HIV-1 circulating in the Netherlands

We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log₁₀ increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence.

Circulating Sphingolipids, Insulin, HOMA-IR, and HOMA-B: The Strong Heart Family Study

Experimental studies suggest ceramides may play a role in insulin resistance. However, the relationships of circulating ceramides and related sphingolipids with plasma insulin have been underexplored in humans. We measured 15 ceramide and sphingomyelin species in fasting baseline samples from the Strong Heart Family Study (SHFS), a prospective cohort of American Indians. We examined sphingolipid associations with both baseline and follow-up measures of plasma insulin, HOMA of insulin resistance (HOMA-IR), and HOMA of β-cell function (HOMA-B) after adjustment for risk factors. Among the 2,086 participants without diabetes, higher levels of plasma ceramides carrying the fatty acids 16:0 (16 carbons, 0 double bond), 18:0, 20:0, or 22:0 were associated with higher plasma insulin and higher HOMA-IR at baseline and at follow-up an average of 5.4 years later. For example, a twofold higher baseline concentration of ceramide 16:0 was associated with 14% higher baseline insulin (P < 0.0001). Associations between sphingomyelin species carrying 18:0, 20:0, 22:0, or 24:0 and insulin were modified by BMI (P < 0.003): higher levels were associated with lower fasting insulin, HOMA-IR, and HOMA-B among those with normal BMI. Our study suggests lowering circulating ceramides might be a target in prediabetes and targeting circulating sphingomyelins should take into account BMI.

Test-retest reliability of longitudinal task-based fMRI: Implications for developmental studies

Great advances have been made in functional Magnetic Resonance Imaging (fMRI) studies, including the use of longitudinal design to more accurately identify changes in brain development across childhood and adolescence. While longitudinal fMRI studies are necessary for our understanding of typical and atypical patterns of brain development, the variability observed in fMRI blood-oxygen-level dependent (BOLD) signal and its test-retest reliability in developing populations remain a concern. Here we review the current state of test-retest reliability for child and adolescent fMRI studies (ages 5–18 years) as indexed by intraclass correlation coefficients (ICC). In addition to highlighting ways to improve fMRI test-retest reliability in developmental cognitive neuroscience research, we hope to open a platform for dialogue regarding longitudinal fMRI study designs, analyses, and reporting of results.

Combined models for pre- and post-treatment longitudinal biomarker data: an application to CD4 counts in HIV-patients

BACKGROUND

There has been some debate in the literature as to whether baseline values of a measurement of interest at treatment initiation should be treated as an outcome variable as part of a model for longitudinal change or instead used as a predictive variable with respect to the response to treatment. We develop a new approach that involves a combined statistical model for all pre- and post-treatment observations of the biomarker of interest, in which the characteristics of response to treatment are treated as a function of the 'true' value of the biomarker at treatment initiation.

METHODS

The modelling strategy developed is applied to a dataset of CD4 counts from patients in the UK Register of HIV Seroconverters (UKR) cohort who initiated highly active antiretroviral therapy (HAART). The post-HAART recovery in CD4 counts for each individual is modelled as following an asymptotic curve in which the speed of response to treatment and long-term maximum are functions of the 'true' underlying CD4 count at initiation of HAART and the time elapsed since seroconversion. Following previous research in this field, the models developed incorporate non-stationary stochastic process components, and the possibility of between-patient differences in variability over time was also considered.

RESULTS

A variety of novel models were successfully fitted to the UKR dataset. These provide reinforcing evidence for findings that have previously been reported in the literature, in particular that there is a strong positive relationship between CD4 count at initiation of HAART and the long-term maximum in each patient, but also reveal potentially important features of the data that would not have been easily identified by other methods of analysis.

CONCLUSION

Our proposed methodology provides a unified framework for the analysis of pre- and post-treatment longitudinal biomarker data that will be useful for epidemiological investigations and simulations in this context. The approach developed allows use of all relevant data from observational cohorts in which many patients are missing pre-treatment measurements and in which the timing and number of observations vary widely between patients.

Should Studies of Diabetes Treatment Stratification Correct for Baseline HbA1c?

Aims

Baseline HbA1c is a major predictor of response to glucose lowering therapy and therefore a potential confounder in studies aiming to identify other predictors. However, baseline adjustment may introduce error if the association between baseline HbA1c and response is substantially due to measurement error and regression to the mean. We aimed to determine whether studies of predictors of response should adjust for baseline HbA1c.

Methods

We assessed the relationship between baseline HbA1c and glycaemic response in 257 participants treated with GLP-1R agonists and assessed whether it reflected measurement error and regression to the mean using duplicate ‘pre-baseline’ HbA1c measurements not included in the response variable. In this cohort and an additional 2659 participants treated with sulfonylureas we assessed the relationship between covariates associated with baseline HbA1c and treatment response with and without baseline adjustment, and with a bias correction using pre-baseline HbA1c to adjust for the effects of error in baseline HbA1c.

Results

Baseline HbA1c was a major predictor of response (R² = 0.19,β = -0.44,p<0.001).The association between pre-baseline and response was similar suggesting the greater response at higher baseline HbA1cs is not mainly due to measurement error and subsequent regression to the mean. In unadjusted analysis in both cohorts, factors associated with baseline HbA1c were associated with response, however these associations were weak or absent after adjustment for baseline HbA1c. Bias correction did not substantially alter associations.

Conclusions

Adjustment for the baseline HbA1c measurement is a simple and effective way to reduce bias in studies of predictors of response to glucose lowering therapy.

The impact of transient combination antiretroviral treatment in early HIV infection on viral suppression and immunologic response in later treatment

Objective:

Effects of transient combination antiretroviral treatment (cART) initiated during early HIV infection (EHI) remain unclear. We investigate whether this intervention affects viral suppression and CD4⁺ cell count increase following its reinitiation in chronic infection (CHI).

Design:

Longitudinal observational study.

Methods:

We identified adult patients from Concerted Action of Seroconversion to AIDS and Death in Europe who seroconverted after 1/1/2000, had a 12 months or less HIV test interval and initiated cART from naive. We classified individuals as ‘pretreated in EHI’ if treated within 6 months of seroconversion, interrupted for at least 12 weeks, and reinitiated during CHI. Statistical analysis was performed using survival analysis methods and mixed models.

Results:

Pretreated and initiated in CHI groups comprised 202 and 4263 individuals, with median follow-up after CHI treatment 4.5 and 3 years, respectively. Both groups had similar virologic response and relapse rates (P = 0.585 and P = 0.206) but pretreated individuals restarted treatment with higher baseline CD4⁺ cell count (∼80 cells/μl; P < 0.001) and retained significantly higher CD4⁺ cell count for more than 3 years after treatment (re)initiation. Assuming common baseline CD4⁺ cell count, differences in CD4⁺ cell count slopes were nonsignificant. Immunovirologic response to CHI treatment was not associated with timing or duration of the transient treatment.

Conclusion:

Although treatment interruptions are not recommended, stopping cART initiated in EHI does not seem to reduce the chance of a successful outcome of treatment in CHI.

Immunologic response in treatment-naïve HIV-2-infected patients: the IeDEA West Africa cohort

INTRODUCTION

Response to antiretroviral therapy (ART) among individuals infected with HIV-2 is poorly described. We compared the immunological response among patients treated with three nucleoside reverse-transcriptase inhibitors (NRTIs) to boosted protease inhibitor (PI) and unboosted PI-based regimens in West Africa.

METHODS

This prospective cohort study enrolled treatment-naïve HIV-2-infected patients within the International Epidemiological Databases to Evaluate AIDS collaboration in West Africa. We used mixed models to compare the CD4 count response to treatment over 12 months between regimens.

RESULTS

Of 422 HIV-2-infected patients, 285 (67.5%) were treated with a boosted PI-based regimen, 104 (24.6%) with an unboosted PI-based regimen and 33 (7.8%) with three NRTIs. Treatment groups were comparable with regard to gender (54.5% female) and median age at ART initiation (45.3 years; interquartile range 38.3 to 51.8). Treatment groups differed by clinical stage (21.2%, 16.8% and 17.3% at CDC Stage C or World Health Organization Stage IV for the triple NRTI, boosted PI and unboosted PI groups, respectively, p=0.02), median length of follow-up (12.9, 17.7 and 44.0 months for the triple NRTI, the boosted PI and the unboosted PI groups, respectively, p<0.001) and baseline median CD4 count (192, 173 and 129 cells/µl in the triple NRTI, the boosted PI and the unboosted PI-based regimen groups, respectively, p=0.003). CD4 count recovery at 12 months was higher for patients treated with boosted PI-based regimens than those treated with three NRTIs or with unboosted PI-based regimens (191 cells/µl, 95% CI 142 to 241; 110 cells/µl, 95% CI 29 to 192; 133 cells/µl, 95% CI 80 to 186, respectively, p=0.004).

CONCLUSIONS

In this observational study using African data, boosted PI-containing regimens had better immunological response compared to triple NRTI combinations and unboosted PI-based regimens at 12 months. A randomized clinical trial is still required to determine the best initial regimen for treating HIV-2 infected patients.

Does rapid HIV disease progression prior to combination antiretroviral therapy hinder optimal CD4+ T-cell recovery once HIV-1 suppression is achieved?

Objective:

This article compares trends in CD4⁺ T-cell recovery and proportions achieving optimal restoration (≥500 cells/μl) after viral suppression following combination antiretroviral therapy (cART) initiation between rapid and nonrapid progressors.

Methods:

We included HIV-1 seroconverters achieving viral suppression within 6 months of cART. Rapid progressors were individuals experiencing at least one CD4⁺ less than 200 cells/μl within 12 months of seroconverters before cART. We used piecewise linear mixed models and logistic regression for optimal restoration.

Results:

Of 4024 individuals, 294 (7.3%) were classified as rapid progressors. At the same CD4⁺ T-cell count at cART start (baseline), rapid progressors experienced faster CD4⁺ T-cell increases than nonrapid progressors in first month [difference (95% confidence interval) in mean increase/month (square root scale): 1.82 (1.61; 2.04)], which reversed to slightly slower increases in months 1–18 [−0.05 (−0.06; −0.03)] and no significant differences in 18–60 months [−0.003 (−0.01; 0.01)]. Percentage achieving optimal restoration was significantly lower for rapid progressors than nonrapid progressors at months 12 (29.2 vs. 62.5%) and 36 (47.1 vs. 72.4%) but not at month 60 (70.4 vs. 71.8%). These differences disappeared after adjusting for baseline CD4⁺ T-cell count: odds ratio (95% confidence interval) 0.86 (0.61; 1.20), 0.90 (0.38; 2.17) and 1.56 (0.55; 4.46) at months 12, 36 and 60, respectively.

Conclusion:

Among people on suppressive antiretroviral therapy, rapid progressors experience faster initial increases of CD4⁺ T-cell counts than nonrapid progressors, but are less likely to achieve optimal restoration during the first 36 months after cART, mainly because of lower CD4⁺ T-cell counts at cART initiation.

Impaired response to treatment with tumour necrosis factor α inhibitors in smokers with axial spondyloarthritis

OBJECTIVES

To investigate the impact of smoking on the response to treatment with a first tumour necrosis factor inhibitor (TNFi) in patients with axial spondyloarthritis (axSpA) in a real-life cohort.

METHODS

Patients fulfilling the Assessment of SpondyloArthritis international Society (ASAS) classification criteria for axSpA in the Swiss Clinical Quality Management Cohort were included in this study. The potential association between smoking status and differential response to TNFi in terms of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Ankylosing Spondylitis Disease Activity Score (ASDAS) was analysed using multiple adjusted longitudinal mixed effect models. Binary response rates at 1 year were assessed with multiple adjusted logistic analyses.

RESULTS

A first TNFi was initiated in 698 patients with axSpA with available smoking status and a baseline or follow-up BASDAI assessment, of which 490 (70%) had complete covariate data. In comparison to non-smokers, current smokers demonstrated significantly smaller reductions in BASDAI and ASDAS scores upon treatment with TNFi (0.75 BASDAI units and 0.69 ASDAS units less, p=0.005 and 0.001, respectively) for patients with elevated baseline C-reactive protein (CRP) level. This effect was numerically smaller in patients with normal CRP. The odds for reaching a 50% improvement in BASDAI response or the ASAS criteria for 40% improvement after 1 year were significantly lower in current smokers than in non-smokers (0.54, 95% CI 0.31 to 0.95, p=0.03 and 0.43, 95% CI 0.24 to 0.76, p=0.004, respectively).

CONCLUSIONS

Current smoking is associated with an impaired response to TNFi in axSpA.

Rate of CD4 decline and HIV-RNA change following HIV seroconversion in men who have sex with men: a comparison between the Beijing PRIMO and CASCADE cohorts

OBJECTIVE

Little is known about the natural history of the HIV infection in men who have sex with men (MSM) in China.

METHODS

We compared changes in CD4+ T-cell count and HIV-RNA following seroconversion before starting antiretroviral therapy between MSM in China and in resource-rich countries using data from the Beijing PRIMO cohort and Concerted Action on SeroConversion to AIDS and Death in Europe (CASCADE), respectively. Linear mixed models were used to compare rates of CD4 decline (cubic root scale) and changes in HIV-RNA (log10 scale) in the first 3 years following seroconversion.

RESULTS

For 131 PRIMO and 3171 CASCADE MSM infected in 2001-2010, estimated CD4+ T-cell count at seroconversion was lower in PRIMO (504 cells/mm3; 95% confidence interval: 463 to 547) compared with CASCADE (554 cells/mm3; 544 to 564). CD4 decline was significantly faster for PRIMO men [-0.59 (-0.72 to -0.47) and - 0.41 (-0.44 to -0.38) cubic root of CD4 count/year for PRIMO and CASCADE, respectively], even after restricting to subtype B (P = 0.01). HIV-RNA at seroconversion was lower in PRIMO compared with CASCADE MSM [difference 0.425 log10/mL (0.249 to 0.603), P < 0.001]. After the first year of seroconversion, PRIMO MSM experienced a faster increase in HIV-RNA [0.830 log10/mL per year; (0.484 to 1.168)] compared with CASCADE MSM [0.018 (-0.035 to 0.067)] (P < 0.001).

CONCLUSIONS

CD4 decline and HIV-RNA increase are faster between MSM in China compared with MSM from resource-rich settings. Whether this is due to differences in host immunity or viral characteristics requires further exploration.

Accounting for baseline differences and measurement error in the analysis of change over time

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy.

Estimates of HIV-1 incidence based on serological methods: a brief methodological review

The paper reviews the serological methods employed in the estimation of HIV incidence based on cross-sectional studies, as well as the main findings from studies carried out in Brazil that have used such methods. Each method is briefly described, as well as their advantages and limitations. The different methods are also analyzed as a set of complementary but sometimes contradictory strategies under permanent criticism and review, still far from a gold standard. Finally, an additional question--central to the accurate monitoring of the AIDS epidemic using such methods--is discussed: whether the different methods should or should not be adjusted. The debate is open and controversy should be viewed as an unavoidable consequence of a very dynamic research field, informed by the progress in sciences as diverse as epidemiology, biostatistics, mathematical modeling and different branches of basic science, such as immunology, virology, and molecular biology.