To summarize the randomized evidence regarding the association between acyclovir use and HIV-1 replication as measured by plasma HIV-1 RNA viral load among individuals coinfected with herpes simplex virus (HSV)-2.
Meta-analysis of seven randomized trials conducted between 2000 and 2009. Inclusion criteria composed of acyclovir or valacyclovir use as prophylaxis among individuals coinfected with HIV-1 and HSV-2 who were ineligible for highly active antiretroviral therapy. HIV-1 viral load was the outcome.
Random-effects summarization was used to combine treatment effect estimates. Stratified and meta-regression analyses were used to compare estimated treatment effects by characteristics of trials and participants.
The summary treatment effect estimate was −0.33 (95% confidence interval: −0.56, −0.10, 95% population effects interval: −0.74, 0.08) log10 copies, an approximate halving of plasma viral load. However, there was marked heterogeneity (P < 0.001). Older median age, valacyclovir, higher compliance, earlier publication, and shorter study length were associated with a larger decrease in viral load as compared with their counterparts.
Current evidence suggests a range of favorable effects of acyclovir on plasma HIV-1 viral load among persons coinfected with HSV-2.
acyclovir; herpes simplex virus; HIV; meta-analysis
Studies have suggested that exposure to ultraviolet (UV) light may increase risk of herpes simplex virus (HSV) recurrence. Between 1993 and 1997, the Herpetic Eye Disease Study (HEDS) randomized 703 participants with ocular HSV to receipt of acyclovir or placebo for prevention of ocular HSV recurrence. Of these, 308 HEDS participants (48% female and 85% white; median age, 49 years) were included in a nested study of exposures thought to cause recurrence and were followed for up to 15 months. We matched weekly UV index values from the National Oceanic and Atmospheric Administration to each participant's study center and used marginal structural Cox models to account for time-varying psychological stress and contact lens use and selection bias from dropout. There were 44 recurrences of ocular HSV, yielding an incidence of 4.3 events per 1,000 person-weeks. Weighted hazard ratios comparing persons with ≥8 hours of time outdoors to those with less exposure were 0.84 (95% confidence interval (CI): 0.27, 2.63) and 3.10 (95% CI: 1.14, 8.48) for weeks with a UV index of <4 and ≥4, respectively (ratio of hazard ratios = 3.68, 95% CI: 0.43, 31.4). Though results were imprecise, when the UV index was higher (i.e., ≥4), spending 8 or more hours per week outdoors was associated with increased risk of ocular HSV recurrence.
cohort studies; herpes simplex virus; recurrence; sunlight; ultraviolet light; UV index
The method of maximum likelihood is widely used in epidemiology, yet many epidemiologists receive little or no education in the conceptual underpinnings of the approach. Here we provide a primer on maximum likelihood and some important extensions which have proven useful in epidemiologic research, and which reveal connections between maximum likelihood and Bayesian methods. For a given data set and probability model, maximum likelihood finds values of the model parameters that give the observed data the highest probability. As with all inferential statistical methods, maximum likelihood is based on an assumed model and cannot account for bias sources that are not controlled by the model or the study design. Maximum likelihood is nonetheless popular, because it is computationally straightforward and intuitive and because maximum likelihood estimators have desirable large-sample properties in the (largely fictitious) case in which the model has been correctly specified. Here, we work through an example to illustrate the mechanics of maximum likelihood estimation and indicate how improvements can be made easily with commercial software. We then describe recent extensions and generalizations which are better suited to observational health research and which should arguably replace standard maximum likelihood as the default method.
epidemiologic methods; maximum likelihood; modeling; penalized estimation; regression; statistics
Estimate the effect of alcohol consumption on HIV acquisition while appropriately accounting for confounding by time-varying risk factors.
African American injection drug users in the AIDS Link to Intravenous Experience cohort study. Participants were recruited and followed with semiannual visits in Baltimore, Maryland between 1988 and 2008.
Marginal structural models were used to estimate the effect of alcohol consumption on HIV acquisition.
At entry, 28% of 1,525 participants were female with a median (quartiles) age of 37 (32; 42) years and 10 (10; 12) years of formal education. During follow up, 155 participants acquired HIV and alcohol consumption was 24%, 24%, 26%, 17%, and 9% for 0, 1–5, 6–20, 21–50 and 51–140 drinks/week over the prior two years, respectively. In analyses accounting for socio-demographic factors, drug use, and sexual activity, hazard ratios for participants reporting 1–5, 6–20, 21–50, and 51–140 drinks/week in the prior two years compared to participants who reported 0 drinks/week were 1.09 (0.60, 1.98), 1.18 (0.66, 2.09), 1.66 (0.94, 2.93) and 2.12 (1.15, 3.90), respectively. A trend test indicated a dose-response relationship between alcohol consumption and HIV acquisition (P value for trend = 9.7×10−4).
A dose-response relationship between alcohol consumption and subsequent HIV acquisition is indicated, independent of measured known risk factors.
Alcohol consumption; HIV infection; Bias; Cohort studies; Injection drug users
Although it is clear that there are short-term effects of sodium intake on blood pressure, little is known about the most relevant timing of sodium exposure for the onset of hypertension. This question can only be addressed in cohorts with repeated measures of sodium intake.
Using up to 7 measures of dietary sodium intake and blood pressure between 1991 and 2009, we compared baseline, the mean of all measures, and the most recent sodium intake in association with incident hypertension, in 6578 adults enrolled in the China Health and Nutrition Survey aged 18 to 65 free of hypertension at baseline. We used survival methods that account for the interval-censored nature of this study, and inverse probability weights to generate adjusted survival curves and time-specific cumulative risk differences; hazard ratios were also estimated.
For mean and most recent measures, the probability of hypertension-free survival was the lowest among those in the highest intake sodium group compared to all other intake groups across the entire follow-up. In addition, the most recent sodium intake measure had a positive dose-response association with incident hypertension [Risk Difference at 11 years of follow-up = 0.04 (95%CI −0.01, 0.09), 0.06 (0.00, 0.13), 0.18 (0.12, 0.24) and 0.20 (0.12, 0.27) for the second to fifth sodium intake groups compared to the lowest group respectively]. Baseline sodium intake was not associated with incident hypertension.
These results suggest caution when using baseline sodium intake measures with long-term follow up.
China; sodium intake; incident hypertension; interval-censored; adjusted survival curves
In a multicenter cohort, unmasking immune reconstitution inflammatory syndrome (IRIS) was observed in 12% of HIV-associated lymphomas. Presentation and survival for lymphoma IRIS were similar to non-IRIS, with possibly increased early mortality among IRIS cases.
Background. Lymphoma incidence is increased among human immunodeficiency virus (HIV)–infected individuals soon after antiretroviral therapy (ART), perhaps due to unmasking immune reconstitution inflammatory syndrome (IRIS). Clinical characteristics and survival for unmasking lymphoma IRIS have not been described.
Methods. We studied lymphoma patients in the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) from 1996 until 2011. Unmasking lymphoma IRIS was defined as lymphoma within 6 months after ART accompanied by a ≥0.5 log10 copies/mL HIV RNA reduction. Differences in presentation and survival were examined between IRIS and non-IRIS cases.
Results. Of 482 lymphoma patients, 56 (12%) met criteria for unmasking lymphoma IRIS. Of these, 12 (21%) had Hodgkin lymphoma, 22 (39%) diffuse large B-cell lymphoma, 5 (9%) Burkitt lymphoma, 10 (18%) primary central nervous system lymphoma, and 7 (13%) other non-Hodgkin lymphoma. Median CD4 cell count at lymphoma diagnosis among IRIS cases was 173 cells/µL (interquartile range, 73–302), and 48% had suppressed HIV RNA <400 copies/mL. IRIS cases were similar overall to non-IRIS cases in histologic distribution and clinical characteristics, excepting more frequent hepatitis B and C (30% vs 19%, P = .05), and lower HIV RNA at lymphoma diagnosis resulting from the IRIS case definition. Overall survival at 5 years was similar between IRIS (49%; 95% confidence interval [CI], 37%–64%) and non-IRIS (44%; 95% CI, 39%–50%), although increased early mortality was suggested among IRIS cases.
Conclusions. In a large HIV-associated lymphoma cohort, 12% of patients met a uniformly applied unmasking lymphoma IRIS case definition. Detailed studies of lymphoma IRIS might identify immunologic mechanisms of lymphoma control.
HIV/AIDS; lymphoma; Hodgkin lymphoma; non-Hodgkin lymphoma; immune reconstitution inflammatory syndrome
Clostridium difficile is a health care–associated infection of increasing importance. The purpose of this study was to estimate the time until death from any cause and time until release among patients with C. difficile, comparing the burden of those in the intensive care unit (ICU) with those in the general hospital population.
A parametric mixture model was used to estimate event times, as well as the case-fatality ratio in ICU and non-ICU patients within a cohort of 609 adult incident cases of C. difficile in the Southeastern United States between 1 July 2009 and 31 December 2010.
ICU patients had twice the median time to death (relative time = 1.97 [95% confidence interval (CI) = 0.96–4.01]) and nearly twice the median time to release (1.88 [1.40–2.51]) compared with non-ICU patients. ICU patients also experienced 3.4 times the odds of mortality (95% CI = 1.8–6.2). Cause-specific competing risks analysis underestimated the relative survival time until death (0.65 [0.36–1.17]) compared with the mixture model.
Patients with C. difficile in the ICU experienced higher mortality and longer lengths of stay within the hospital. ICU patients with C. difficile infection represent a population in need of particular attention, both to prevent adverse patient outcomes and to minimize transmission of C. difficile to other hospitalized patients.
Racial disparities in clinic attendance may contribute to racial disparities in plasma human immunodeficiency virus type 1 (HIV-1) RNA levels among HIV-positive patients in care. Data from 946 African American and 535 Caucasian patients receiving HIV care at the University of North Carolina Center for AIDS Research HIV clinic between January 1, 1999, and August 1, 2012, were used to estimate the association between African American race and HIV virological suppression (i.e., undetectable HIV-1 RNA) when racial disparities in clinic attendance were lessened. Clinic attendance was measured as the proportion of scheduled clinic appointments attended (i.e., visit adherence) or the proportion of six 4-month intervals with at least 1 attended scheduled clinic appointment (i.e., visit constancy). In analyses accounting for patient characteristics, the risk ratio for achieving suppression when comparing African Americans with Caucasians was 0.91 (95% confidence interval: 0.85, 0.98). Lessening disparities in adherence or constancy lowered disparities in virological suppression by up to 44.4% and 11.1%, respectively. Interventions that lessen disparities in adherence may be more effective in eliminating disparities in suppression than interventions that lessen disparities in constancy. Given that gaps in care were limited to be no more than 2 years for both attendance measures, the impact of lessening disparities in adherence may be overstated.
clinic visits; cohort studies; health status disparities; human immunodeficiency virus; viral load
Non-Hodgkin lymphoma incidence is high in HIV-infected patients successfully treated with antiretroviral therapy. HIV replication, even at low levels, may be an important modifiable risk factor for non-Hodgkin lymphoma.
Background. The incidence of non-Hodgkin lymphoma (NHL) in human immunodeficiency virus (HIV)–infected patients remains high despite treatment with antiretroviral therapy (ART).
Methods. We evaluated NHL incidence in HIV-infected patients followed in the Centers for AIDS Research Network of Integrated Clinical Systems who started combination ART and achieved suppression of HIV. We estimated the hazard ratio for NHL by time-varying HIV viremia categories, accounting for time-varying CD4 cell count using marginal structural models.
Results. We observed 37 incident NHL diagnoses during 21 607 person-years of follow-up in 6036 patients (incidence rate, 171 per 100 000 person-years; 95% confidence interval [CI], 124–236). NHL incidence was high even among patients with nadir CD4 cell count >200 cells/µL (140 per 100 000 person-years [95% CI, 80–247]). Compared with ≤50 copies/mL, hazard ratios (HRs) for NHL were higher among those with HIV viremia of 51–500 copies/mL (HR current = 1.66 [95% CI, .70–3.94]; HR 3-month lagged = 2.10 [95% CI, .84–5.22]; and HR 6-month lagged = 1.46 [95% CI, .60–3.60]) and >500 copies/mL (HR current = 2.39 [95% CI, .92–6.21]; HR 3-month lagged = 3.56 [95% CI, 1.21–10.49]; and HR 6-month lagged = 2.50 [95% CI, .91–6.84]). Current HIV RNA as a continuous variable was also associated with NHL (HR = 1.42 per log10 copies/mL [95% CI, 1.05–1.92]).
Conclusions. Our findings demonstrate a high incidence of NHL among HIV-infected patients on ART and suggest a role of HIV viremia in the pathogenesis of NHL. Earlier initiation of potent ART and maximal continuous suppression of HIV viremia may further reduce NHL risk.
non-Hodgkin lymphoma; HIV; antiretroviral therapy; incidence; viremia
Alcohol Drinking; HIV Seropositivity; Men who Have Sex with Men; Prospective Studies; Sexual Behavior
To estimate the association between immunologic response to antiretroviral therapy (ART) and non-AIDS-defining cancer (NADC) incidence in HIV-infected patients.
Prospective cohort including patients with ≥1 CD4 count and HIV-1 RNA measure after ART initiation between 1996 and 2011 in the Centers for AIDS Research Network of Integrated Clinical Systems, a collaboration of 8 HIV clinics at major academic medical centers in the United States.
Measures of immunologic response were six-month CD4 post-ART, latest CD4, and CD4 count-years, a cumulative measure of CD4 lymphopenia. Cox regression with inverse probability-of-exposure weights was used to calculate adjusted hazard ratios (HR) of virus-related and virus-unrelated NADC incidence.
Among 9389 patients at ART initiation, median CD4 count was 200 cells/mm3 (IQR=60–332), and median HIV-1 RNA was 4.8 log10copies/ml (IQR=4.3–5.4). Median follow-up was 3.3 years (IQR=1.5–6.5). After six months of ART, median CD4 count was 304 cells/mm3 (IQR=163–469). 164 NADCs were diagnosed during study follow-up; 65 (40%) considered virus-related. Virus-related NADCs were inversely associated with six-month CD4 (HR per 100 cells/mm3 increase=0.71), latest CD4 (HR per 100 cells/mm3 increase=0.70), and CD4 count-years (HR per 200 cell-years/mm3 increase=0.91) independent of CD4 at ART initiation, age, and HIV-1 RNA response. No associations were found with virus-unrelated NADCs.
Poor CD4 response was strongly associated with virus-related NADC incidence, suggesting an important role for T-cell-mediated immunity in pathogenesis. Lower CD4 proximal to cancer diagnosis may be a result of subclinical cancer. Intensified cancer screening should be considered for patients on ART with low CD4 counts.
Antiretroviral therapy; Cancers; HIV infections; Immune reconstitution; CD4; Tumor virus infections
Previous studies suggest that indicators of central adiposity such as waist-to-hip ratio (WHR) and waist circumference may be altered by HIV infection, antiretroviral (ARV) treatment or both.
Waist and hip circumference and body mass index (BMI) were measured among participants of the Women’s Interagency HIV Study (WIHS) semiannually from 1999 to 2004. Generalized linear models evaluated longitudinal patterns of these measures and associations with demographic and clinical characteristics.
WHR was significantly larger while BMI, waist and hip circumference were significantly smaller at almost all eleven semiannual visits among 942 HIV-infected compared to 266 HIV-uninfected women. Among HIV-uninfected women, mean waist and hip circumference and BMI increased over the 5 year study period (waist: +4.1 cm or 4.4%, hip: +3.76 cm or 3.5% and BMI +2.43 kg/m2 or 8.2%), while WHR remained stable. Among the HIV-infected women, waist and hip circumference, BMI and WHR did not significantly change.
Independent predictors of smaller BMI among HIV-infected women included White race, HCV seropositivity, current smoking, higher viral load and lower CD4. Independent predictors of larger WHR among HIV-infected women included age, White and Other non-African-American race, higher CD4 and PI use. Use of a HAART regimen was not an independent predictor of either BMI or WHR..
HIV-infected women had higher WHR compared to HIV-uninfected women, despite lower BMI, waist and hip measurements. BMI, waist and hip circumference increased over 5 years among the HIV-uninfected women, but remained stable in the HIV-infected women. Among HIV-infected women, PI use was associated with larger WHR, although HAART use itself was not appreciably associated with either BMI or WHR.
anthropometrics; HIV; women; waist-to-hip ratio
In Australia, bowel cancer screening participation using faecal occult blood testing (FOBT) is low. Decision support tailored to psychological predictors of participation may increase screening. The study compared tailored computerised decision support to non-tailored computer or paper information. The primary outcome was FOBT return within 12 weeks. Additional analyses were conducted on movement in decision to screen and change on psychological variables.
A parallel, randomised controlled, trial invited 25,511 people aged 50–74 years to complete an eligibility questionnaire. Eligible respondents (n = 3,408) were assigned to Tailored Personalised Decision Support (TPDS), Non-Tailored PDS (NTPDS), or Control (CG) (intention-to-treat, ITT sample). TPDS and NTPDS groups completed an on-line baseline survey (BS) and accessed generic information. The TPDS group additionally received a tailored intervention. CG participants completed a paper BS only. Those completing the BS (n = 2270) were mailed an FOBT and requested to complete an endpoint survey (ES) that re-measured BS variables (per-protocol, PP sample).
FOBT return: In the ITT sample, there was no significant difference between any group (χ2(2) = 2.57, p = .26; TPDS, 32.5%; NTPDS, 33%; and CG, 34.5%). In the PP sample, FOBT return in the internet groups was significantly higher than the paper group (χ2(2) = 17.01, p < .001; TPDS, 80%; NTPDS, 83%; and CG, 74%). FOBT completion by TPDS and NTPDS did not differ (χ2(1) = 2.23, p = .13). Age was positively associated with kit return.
Decision to screen: 2227/2270 of the PP sample provided complete BS data. Participants not wanting to screen at baseline (1083/2227) and allocated to TPDS and NTPDS were significantly more likely to decide to screen and return an FOBT than those assigned to the CG. FOBT return by TPDS and NTPDS did not differ from one another (OR = 1.16, p = .42).
Change on psychosocial predictors: Analysis of change indicated that salience and coherence of screening and self-efficacy were improved and faecal aversion decreased by tailored messaging.
Online information resources may have a role in encouraging internet-enabled people who are uncommitted to screening to change their attitudes, perceptions and behaviour.
Australian New Zealand Clinical Trials Registry ACTRN12610000095066
Randomised controlled trial; Decision support; Bowel cancer; Faecal occult blood test; Cancer screening; Tailored messages
To estimate the association of antiretroviral therapy initiation with incident acquired immunodeficiency syndrome (AIDS) or death while accounting for time-varying confounding in a cost-efficient manner, the authors combined a case-cohort study design with inverse probability-weighted estimation of a marginal structural Cox proportional hazards model. A total of 950 adults who were positive for human immunodeficiency virus type 1 were followed in 2 US cohort studies between 1995 and 2007. In the full cohort, 211 AIDS cases or deaths occurred during 4,456 person-years. In an illustrative 20% random subcohort of 190 participants, 41 AIDS cases or deaths occurred during 861 person-years. Accounting for measured confounders and determinants of dropout by inverse probability weighting, the full cohort hazard ratio was 0.41 (95% confidence interval: 0.26, 0.65) and the case-cohort hazard ratio was 0.47 (95% confidence interval: 0.26, 0.83). Standard multivariable-adjusted hazard ratios were closer to the null, regardless of study design. The precision lost with the case-cohort design was modest given the cost savings. Results from Monte Carlo simulations demonstrated that the proposed approach yields approximately unbiased estimates of the hazard ratio with appropriate confidence interval coverage. Marginal structural model analysis of case-cohort study designs provides a cost-efficient design coupled with an accurate analytic method for research settings in which there is time-varying confounding.
acquired immunodeficiency syndrome; case-cohort studies; cohort studies; confounding bias; HIV; pharmacoepidemiology; selection bias
Bayesian posterior parameter distributions are often simulated using Markov chain Monte Carlo (MCMC) methods. However, MCMC methods are not always necessary and do not help the uninitiated understand Bayesian inference. As a bridge to understanding Bayesian inference, the authors illustrate a transparent rejection sampling method. In example 1, they illustrate rejection sampling using 36 cases and 198 controls from a case-control study (1976–1983) assessing the relation between residential exposure to magnetic fields and the development of childhood cancer. Results from rejection sampling (odds ratio (OR) = 1.69, 95% posterior interval (PI): 0.57, 5.00) were similar to MCMC results (OR = 1.69, 95% PI: 0.58, 4.95) and approximations from data-augmentation priors (OR = 1.74, 95% PI: 0.60, 5.06). In example 2, the authors apply rejection sampling to a cohort study of 315 human immunodeficiency virus seroconverters (1984–1998) to assess the relation between viral load after infection and 5-year incidence of acquired immunodeficiency syndrome, adjusting for (continuous) age at seroconversion and race. In this more complex example, rejection sampling required a notably longer run time than MCMC sampling but remained feasible and again yielded similar results. The transparency of the proposed approach comes at a price of being less broadly applicable than MCMC.
Bayes theorem; epidemiologic methods; inference; Monte Carlo method; posterior distribution; simulation
To evaluate survival and predictors of mortality after cancer diagnosis among HIV-infected persons receiving combination antiretroviral therapy (cART).
Multisite cohort study.
We examined all-cause mortality among HIV-infected patients treated with cART in routine care at eight US sites and diagnosed with cancer between 1996 and 2009, and predictors of mortality using Cox proportional hazards regression models. Non-AIDS-defining cancers (NADCs) were classified as related and unrelated to viral coinfections.
Out of 20 677 persons in the Centers for AIDS Research Network of Integrated Clinical Systems cohort, 650 cART-treated individuals developed invasive cancer. Of these, 305 died during 1480 person-years of follow-up; crude mortality rate was 20.6 per 100 person-years [95% confidence interval (CI) 18.4, 23.1] and overall 2-year survival was 58% (95% CI 54, 62). Highest mortality was seen in primary central nervous system non-Hodgkin’s lymphoma, liver, and lung cancer with rates of 90.6, 84.3, and 68.1 per 100 person-years, respectively. Adjusted hazard of death was higher among those who were older and had stage IV cancer. Adjusted hazard of death was lower among those with higher CD4 cell counts at cancer diagnosis, who achieved HIV-RNA suppression (≤400 copies/ml) on cART, received any cancer treatment, and had AIDS-defining cancer or infection-related NADCs compared to infection-unrelated NADCs.
Independent predictors of mortality after cancer diagnosis among HIV-infected persons include poor immune status, failure to suppress HIV-RNA on cART, cancer stage, and lack of cancer treatment. Modification of these factors with improved strategies for the prevention and treatment of HIV and HIV-associated malignancies are needed.
antiretroviral therapy; cancer; HIV; mortality; survival
In studies of the health effects of asbestos, lung cancer death is subject to misclassification. We used modified maximum likelihood to explore the effects of outcome misclassification on the rate ratio of lung cancer death per 100 fiber-years per milliliter of cumulative asbestos exposure in a cohort study of textile workers in Charleston, South Carolina, followed from 1940 to 2001. The standard covariate-adjusted estimate of the rate ratio was 1.94 (95% confidence interval: 1.55, 2.44), and modified maximum likelihood produced similar results when we assumed that the specificity of outcome classification was 0.98. With sensitivity assumed to be 0.80 and specificity assumed to be 0.95, estimated rate ratios were further from the null and less precise (rate ratio = 2.17; 95% confidence interval: 1.59, 2.98). In the present context, standard estimates for the effect of asbestos on lung cancer death were similar to estimates accounting for the limited misclassification. However, sensitivity analysis using modified maximum likelihood was needed to verify the robustness of standard estimates, and this approach will provide unbiased estimates in settings with more misclassification.
asbestos; bias; sensitivity and specificity
The causes of poor clinic attendance and incomplete virologic suppression among HIV+ African Americans (AAs) are not well understood. We estimated the effect of at-risk alcohol/drug use and associated treatment on attending scheduled appointments and virologic suppression among 576 HIV+ AA patients in the University of Alabama at Birmingham (UAB) 1917 Clinic Cohort who contributed 591 interviews to the analysis. At interview, 78% of patients were new to HIV care at UAB, 38% engaged in at-risk alcohol/drug use or received associated treatment in the prior year, while the median (quartiles) age and CD4 count were 36 (28; 46) years and 321 (142; 530) cells/μl, respectively. In the 2 years after an interview, half of the patients had attended at least 82% of appointments while half had achieved virologic suppression for at least 71% of RNA assessments. Compared to patients who did not use or receive treatment, the adjusted risk ratio (aRR) for attending appointments for patients who did use but did not receive treatment was 0.97 (95% confidence limits: 0.92, 1.03). The corresponding aRR for virologic suppression was 0.94 (0.86, 1.03). Compared to patients who did not receive treatment but did use, the aRR for attending appointments for patients who did receive treatment and did use was 0.86 (0.78, 0.95). The corresponding aRR for virologic suppression was 1.07 (0.92, 1.24). Use was negatively associated with attendance and virologic suppression among patients not in treatment. Among users, treatment was negatively associated with attendance yet positively associated with virologic suppression. However, aRR estimates were imprecise.
Most psychometric tests originate from Europe and North America and
have not been validated in other populations. We assessed the validity of
United States (US)-based norms for the Bayley Scales of Infant and Toddler
Development-III (BSID-III), a neurodevelopmental tool developed for and
commonly used in the US, in Malawian children.
We constructed BSID-III norms for cognitive, fine motor (FM), gross
motor (GM), expressive communication (EC) and receptive communication (RC)
subtests using 5 173 tests scores in 167 healthy Malawian children. Norms
were generated using Generalized Additive Models for location, scale and
shape, with age modeled continuously. Standard z-scores were used to
classify neurodevelopmental delay. Weighted kappa statistics were used to
compare the classification of neurological development using US-based and
For all subtests, the mean raw scores in Malawian children were
higher than the US normative scores at younger ages (approximately
<6 months) after which the mean curves crossed and the US normative
mean exceeded that of the Malawian sample and the age at which the curves
crossed differed by subtest. Weighted kappa statistics for agreement between
US and Malawian norms were 0.45 for cognitive, 0.48 for FM, 0.57 for GM,
0.50 for EC, and 0.44 for RC.
We demonstrate that population reference curves for the BSID-III
differ depending on the origin of the population. Reliance on US norm-based
standardized scores resulted in misclassification of the neurological
development of Malawian children, with the greatest potential for bias in
the measurement of cognitive and language skills.
Child development; testing norms; cross-cultural testing bias
In occupational epidemiologic studies, the healthy-worker survivor effect refers to a process that leads to bias in the estimates of an association between cumulative exposure and a health outcome. In these settings, work status acts both as an intermediate and confounding variable, and may violate the positivity assumption (the presence of exposed and unexposed observations in all strata of the confounder). Using Monte Carlo simulation, we assess the degree to which crude, work-status adjusted, and weighted (marginal structural) Cox proportional hazards models are biased in the presence of time-varying confounding and nonpositivity. We simulate data representing time-varying occupational exposure, work status, and mortality. Bias, coverage, and root mean squared error (MSE) were calculated relative to the true marginal exposure effect in a range of scenarios. For a base-case scenario, using crude, adjusted, and weighted Cox models, respectively, the hazard ratio was biased downward 19%, 9%, and 6%; 95% confidence interval coverage was 48%, 85%, and 91%; and root MSE was 0.20, 0.13, and 0.11. Although marginal structural models were less biased in most scenarios studied, neither standard nor marginal structural Cox proportional hazards models fully resolve the bias encountered under conditions of time-varying confounding and nonpositivity.
In HIV-1 clinical trials the interest is often to compare how well treatments suppress the HIV-1 RNA viral load. The current practice in statistical analysis of such trials is to define a single ad hoc composite event which combines information about both the viral load suppression and the subsequent viral rebound, and then analyze the data using standard univariate survival analysis techniques. The main weakness of this approach is that the results of the analysis can be easily influenced by minor details in the definition of the composite event. We propose a straightforward alternative endpoint based on the probability of being suppressed over time, and suggest that treatment differences be summarized using the restricted mean time a patient spends in the state of viral suppression. A nonparametric analysis is based on methods for multiple endpoint studies. We demonstrate the utility of our analytic strategy using a recent therapeutic trial, in which the protocol specified a primary analysis using a composite endpoint approach.
AIDS; Clinical trial endpoint; Counting processes; Multistate models; Survival analysis
The parametric g-formula can be used to estimate the effect of a policy, intervention, or treatment. Unlike standard regression approaches, the parametric g-formula can be used to adjust for time-varying confounders that are affected by prior exposures. To date, there are few published examples in which the method has been applied.
We provide a simple introduction to the parametric g-formula and illustrate its application in analysis of a small cohort study of bone marrow transplant patients in which the effect of treatment on mortality is subject to time-varying confounding.
Standard regression adjustment yields a biased estimate of the effect of treatment on mortality relative to the estimate obtained by the g-formula.
The g-formula allows estimation of a relevant parameter for public health officials: the change in the hazard of mortality under a hypothetical intervention, such as reduction of exposure to a harmful agent or introduction of a beneficial new treatment. We present a simple approach to implement the parametric g-formula that is sufficiently general to allow easy adaptation to many settings of public health relevance.
Gene expression analyses indicate that breast cancer is a heterogeneous disease with at least 5 immunohistologic subtypes. Despite growing evidence that these subtypes are etiologically and prognostically distinct, few studies have investigated whether they have divergent genetic risk factors. To help fill in this gap in our understanding, we examined associations between breast cancer subtypes and previously established susceptibility loci among white and African-American women in the Carolina Breast Cancer Study.
We used Bayesian polytomous logistic regression to estimate odds ratios (ORs) and 95% posterior intervals (PIs) for the association between each of 78 single nucleotide polymorphisms (SNPs) and 5 breast cancer subtypes. Subtypes were defined using 5 immunohistochemical markers: estrogen receptors (ER), progesterone receptors (PR), human epidermal growth factor receptors 1 and 2 (HER1/2) and cytokeratin (CK) 5/6.
Several SNPs in TNRC9/TOX3 were associated with luminal A (ER/PR+, HER2−) or basal-like breast cancer (ER−, PR−, HER2−, HER1 or CK 5/6+), and one SNP (rs3104746) was associated with both. SNPs in FGFR2 were associated with luminal A, luminal B (ER/PR+, HER2+), or HER2+/ER− disease, but none were associated with basal-like disease. We also observed subtype differences in the effects of SNPs in 2q35, 4p, TLR1, MAP3K1, ESR1, CDKN2A/B, ANKRD16, and ZM1Z1.
Conclusion and Impact
We found evidence that genetic risk factors for breast cancer vary by subtype and further clarified the role of several key susceptibility genes.
breast cancer; single nucleotide polymorphisms; breast cancer subtypes; GWAS; Bayesian analysis
In this article, we present an overview and tutorial of statistical methods for meta-analysis of diagnostic tests under two scenarios: 1) when the reference test can be considered a gold standard; and 2) when the reference test cannot be considered a gold standard. In the first scenario, we first review the conventional summary receiver operating characteristics (ROC) approach and a bivariate approach using linear mixed models (BLMM). Both approaches require direct calculations of study-specific sensitivities and specificities. We next discuss the hierarchical summary ROC curve approach for jointly modeling positivity criteria and accuracy parameters, and the bivariate generalized linear mixed models (GLMM) for jointly modeling sensitivities and specificities. We further discuss the trivariate GLMM for jointly modeling prevalence, sensitivities and specificities, which allows us to assess the correlations among the three parameters. These approaches are based on the exact binomial distribution and thus do not require an ad hoc continuity correction. Last, we discuss a latent class random effects model for meta-analysis of diagnostic tests when the reference test itself is imperfect for the second scenario. A number of case studies with detailed annotated SAS code in procedures MIXED and NLMIXED are presented to facilitate the implementation of these approaches.
meta-analysis; diagnostic test; gold standard; generalized linear mixed models