There are few published examples of absolute risk estimated from epidemiologic data subject to censoring and competing risks with adjustment for multiple confounders. We present an example estimating the effect of injection drug use on 6-year risk of acquired immunodeficiency syndrome (AIDS) after initiation of combination antiretroviral therapy between 1998 and 2012 in an 8-site US cohort study with death before AIDS as a competing risk. We estimate the risk standardized to the total study sample by combining inverse probability weights with the cumulative incidence function; estimates of precision are obtained by bootstrap. In 7,182 patients (83% male, 33% African American, median age of 38 years), we observed 6-year standardized AIDS risks of 16.75% among 1,143 injection drug users and 12.08% among 6,039 nonusers, yielding a standardized risk difference of 4.68 (95% confidence interval: 1.27, 8.08) and a standardized risk ratio of 1.39 (95% confidence interval: 1.12, 1.72). Results may be sensitive to the assumptions of exposure-version irrelevance, no measurement bias, and no unmeasured confounding. These limitations suggest that results be replicated with refined measurements of injection drug use. Nevertheless, estimating the standardized risk difference and ratio is straightforward, and injection drug use appears to increase the risk of AIDS.
AIDS; cohort study; competing risks; HIV; survival function
The epidemiologist primarily studies transitions between states of health and disease. The purpose of the present article is to define a foundational parameter for such studies, namely risk. We begin simply and build to the setting in which there is more than 1 event type (i.e., competing risks or competing events), as well as more than 1 treatment or exposure level of interest. In the presence of competing events, the risks are a set of counterfactual cumulative incidence functions for each treatment. These risks can be depicted visually and summarized numerically. We use an example from the study of human immunodeficiency virus to illustrate concepts.
causal inference; cohort study; semi-Bayes method; semiparametric inference; survival analysis
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
Viral load is an important tool for assessing antiretroviral treatment efficacy. However, the most common viral load endpoint, virologic failure, may be flawed. We illustrate an alternative endpoint that estimates the average time patients spent suppressed prior to rebound in the AIDS Clinical Trials Group A5095 trial. Patients averaged 644 days suppressed in the 3-drug arm and 686 days suppressed in the 4-drug arm, for a difference of 42 days in favor of the 4-drug regimen (95% CI: −11, 96). These results agree with results using virologic failure as the endpoint but better emphasize the separate suppression and rebound processes.
Inequalities in survival from colorectal cancer (CRC) across socioeconomic groups and by area of residence have been described in various health care settings. Few population-wide datasets which include clinical and treatment information are available in Australia to investigate disparities. This study examines socio-demographic differences in survival for CRC patients in South Australia (SA), using a population-wide database derived via linkage of administrative and surveillance datasets.
The study population comprised all cases of CRC diagnosed in 2003-2008 among SA residents aged 50-79 yrs in the SA Central Cancer Registry. Measures of socioeconomic status (area level), geographical remoteness, clinical characteristics, comorbid conditions, treatments and outcomes were derived through record linkage of central cancer registry, hospital-based clinical registries, hospital separations, and radiotherapy services data sources. Socio-demographic disparities in CRC survival were examined using competing risk regression analysis.
Four thousand six hundred and forty one eligible cases were followed for an average of 4.7 yrs, during which time 1525 died from CRC and 416 died from other causes. Results of competing risk regression indicated higher risk of CRC death with higher grade (HR high v low =2.25, 95 % CI 1.32-3.84), later stage (HR C v A = 7.74, 95 % CI 5.75-10.4), severe comorbidity (HR severe v none =1.21, 95 % CI 1.02-1.44) and receiving radiotherapy (HR = 1.41, 95 % CI 1.18-1.68). Patients from the most socioeconomically advantaged areas had significantly better outcomes than those from the least advantaged areas (HR =0.75, 95 % 0.62-0.91). Patients residing in remote locations had significantly worse outcomes than metropolitan residents, though this was only evident for stages A-C (HR = 1.35, 95 % CI 1.01-1.80). These disparities were not explained by differences in stage at diagnosis between socioeconomic groups or area of residence. Nor were they explained by differences in patient factors, other tumour characteristics, comorbidity, or treatment modalities.
Socio-economic and regional disparities in survival following CRC are evident in SA, despite having a universal health care system. Of particular concern is the poorer survival for patients from remote areas with potentially curable CRC. Reasons for these disparities require further exploration to identify factors that can be addressed to improve outcomes.
Colorectal cancer; Socio-demographic inequalities; Stage; Survival
To compare the performance of a new blood test for colorectal cancer (CRC) to an established fecal immunochemical test (FIT) in a study population with the full range of neoplastic and non-neoplastic pathologies encountered in the colon and rectum.
Volunteers were asked to complete a FIT prior to colonoscopy. Blood was collected after bowel preparation but prior to colonoscopy, and plasma was assayed for the presence of methylated BCAT1 and IKZF1 DNA using a multiplex real-time PCR assay. Sensitivity and specificity estimates for the blood test were calculated from true- and false-positive rates for neoplasia and compared with FIT at a range of fecal hemoglobin (Hb) concentration positivity thresholds.
In total, 1,381 volunteers (median age 64 years; 49% male) completed both tests prior to colonoscopy. Estimated sensitivity of the BCAT1/IKZF1 blood test for CRC was 62% (41/66; 95% confidence interval 49–74%) with a specificity of 92% (1207/1315; 90–93%). FIT returned the same specificity at a cutoff of 60 μg Hb/g, at which its corresponding sensitivity for cancer was 64% (42/66; 51–75%). In the range of commonly used FIT cutoffs, respective cancer sensitivity and specificity estimates with FIT were: 59% (46–71%) and 93% (92–95%) at 80 μg Hb/g, and 79% (67–88%) and 81% (78–83%) at 10 μg Hb/g. Although estimated sensitivities were not significantly different between the two tests for any stage of cancer, FIT showed a significantly higher sensitivity for advanced adenoma at the lower cutoffs. Specificity of FIT, but not of the BCAT1/IKZF1 blood test, deteriorated substantially in people with overt blood in the feces. When combining FIT (cutoff 10 μg Hb/g) with the BCAT1/IKZF1 blood test, sensitivity for cancer was 89% (79–96%) at 74% (72–77%) specificity.
A test based on detection of methylated BCAT1/IKZF1 DNA in blood has comparable sensitivity but better specificity for CRC than FIT at the commonly used positivity threshold of 10 μg Hb/g. Further evaluation of the new test relative to FIT in the population screening context is now required to fully understand the potential advantages and disadvantages of these biomarkers in screening.
In an observational study with a time-to-event outcome, the standard analytical approach is the Cox proportional hazards regression model. As an alternative to the standard Cox model, in this article we present a method that uses inverse probability (IP) weights to estimate the effect of a baseline exposure on a time-to-event outcome. IP weighting can be used to adjust for multiple measured confounders of a baseline exposure in order to estimate marginal effects, which compare the distribution of outcomes when the entire population is exposed versus when the entire population is unexposed. For example, IP-weighted Cox models allow for estimation of the marginal hazard ratio and marginal survival curves. IP weights can also be employed to adjust for selection bias due to loss to follow-up. This approach is illustrated using an example that estimates the effect of injection drug use on time until AIDS or death among HIV-infected women.
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
We propose a joint model for longitudinal and survival data with time-varying covariates subject to detection limits and intermittent missingness at random (MAR). The model is motivated by data from the Multicenter AIDS Cohort Study (MACS), in which HIV+ subjects have viral load and CD4 cell count measured at repeated visits along with survival data. We model the longitudinal component using a normal linear mixed model, modeling the trajectory of CD4 cell count by regressing on viral load and other covariates. The viral load data are subject to both left-censoring due to detection limits (17%) and intermittent missingness (27%). The survival component of the joint model is a Cox model with time-dependent covariates for death due to AIDS. The longitudinal and survival models are linked using the trajectory function of the linear mixed model. A Bayesian analysis is conducted on the MACS data using the proposed joint model. The proposed method is shown to improve the precision of estimates when compared to alternative methods.
Detection Limit; Joint Modeling; Missing Data; Multicenter AIDS Cohort Study
Missed HIV care visits have independent prognostic value for clinical events beyond core indicators of retention in care. As this information is readily available and immediately actionable, missed HIV care visits should be incorporated into clinical, programmatic, and policy initiatives.
Background. The continuum of care is at the forefront of the domestic human immunodeficiency virus (HIV) agenda, with the Institute of Medicine (IOM) and Department of Health and Human Services (DHHS) recently releasing clinical core indicators. Core indicators for retention in care are calculated based on attended HIV care clinic visits. Beyond these retention core indicators, we evaluated the additional prognostic value of missed clinic visits for all-cause mortality.
Methods. We conducted a multisite cohort study of 3672 antiretroviral-naive patients initiating antiretroviral therapy (ART) during 2000–2010. Retention in care was measured by the IOM and DHHS core indicators (2 attended visits at defined intervals per 12-month period), and also as a count of missed primary HIV care visits (no show) during a 24-month measurement period following ART initiation. All-cause mortality was ascertained by query of the Social Security Death Index and/or National Death Index, with adjusted survival analyses starting at 24 months after ART initiation.
Results. Among participants, 64% and 59% met the IOM and DHHS retention core indicators, respectively, at 24 months. Subsequently, 332 patients died during 16 102 person-years of follow-up. Failure to achieve the IOM and DHHS indicators through 24 months following ART initiation increased mortality (hazard ratio [HR] = 2.23; 95% confidence interval [CI], 1.79–2.80 and HR = 2.36; 95% CI, 1.89–2.96, respectively). Among patients classified as retained by the IOM or DHHS clinical core indicators, >2 missed visits further increased mortality risk (HR = 3.61; 95% CI, 2.35–5.55 and HR = 3.62; 95% CI, 2.30–5.68, respectively).
Conclusions. Beyond HIV retention core indicators, missed clinic visits were independently associated with all-cause mortality. Caution is warranted in relying solely upon retention in care core indicators for policy, clinical, and programmatic purposes.
HIV; AIDS; antiretroviral therapy; engagement in care; continuum of care
In a recent issue of the Journal, Kirkeleit et al. (Am J Epidemiol. 2013;177(11):1218–1224) provided empirical evidence for the potential of the healthy worker effect in a large cohort of Norwegian workers across a range of occupations. In this commentary, we provide some historical context, define the healthy worker effect by using causal diagrams, and use simulated data to illustrate how structural nested models can be used to estimate exposure effects while accounting for the healthy worker survivor effect in 4 simple steps. We provide technical details and annotated SAS software (SAS Institute, Inc., Cary, North Carolina) code corresponding to the example analysis in the Web Appendices, available at http://aje.oxfordjournals.org/.
causal inference; healthy worker effect; marginal structural models; occupational epidemiology; structural nested models
Workers' smoking histories are not measured in many occupational cohort studies. Here we discuss the use of negative control outcomes to detect and adjust for confounding in analyses that lack information on smoking. We clarify the assumptions necessary to detect confounding by smoking and the additional assumptions necessary to indirectly adjust for such bias. We illustrate these methods using data from 2 studies of radiation and lung cancer: the Colorado Plateau cohort study (1950–2005) of underground uranium miners (in which smoking was measured) and a French cohort study (1950–2004) of nuclear industry workers (in which smoking was unmeasured). A cause-specific relative hazards model is proposed for estimation of indirectly adjusted associations. Among the miners, the proposed method suggests no confounding by smoking of the association between radon and lung cancer—a conclusion supported by adjustment for measured smoking. Among the nuclear workers, the proposed method suggests substantial confounding by smoking of the association between radiation and lung cancer. Indirect adjustment for confounding by smoking resulted in an 18% decrease in the adjusted estimated hazard ratio, yet this cannot be verified because smoking was unmeasured. Assumptions underlying this method are described, and a cause-specific proportional hazards model that allows easy implementation using standard software is presented.
cohort studies; lung cancer; smoking
Traditional regression analysis techniques used to estimate associations between occupational radon exposure and lung cancer focus on estimating the effect of cumulative radon exposure on lung cancer, while public health interventions are typically based on regulating radon concentration rather than workers’ cumulative exposure. Moreover, estimating the direct effect of cumulative occupational exposure on lung cancer may be difficult in situations vulnerable to the healthy worker survivor bias.
Workers in the Colorado Plateau Uranium Miners cohort (N=4,134) entered the study between 1950 and 1964 and were followed for lung cancer mortality through 2005. We use the parametric g-formula to compare the observed lung cancer mortality to the potential lung cancer mortality had each of 3 policies to limit monthly radon exposure been in place throughout follow-up.
There were 617 lung cancer deaths over 135,275 person-years of follow-up. With no intervention on radon exposure, estimated lung cancer mortality by age 90 was 16%. Lung cancer mortality was reduced for all interventions considered, and larger reductions in lung cancer mortality were seen for interventions with lower monthly radon exposure limits. The most stringent guideline, the Mine Safety and Health Administration standard of 0.33 working level months, reduced lung cancer mortality from 16% to 10% (risk ratio 0.67; 95% confidence interval 0.61, 0.73).
This work illustrates the utility of the parametric g-formula for estimating the effects of policies regarding occupational exposures, particularly in situations vulnerable to the healthy worker survivor bias.
radon; lung neoplasms; occupational health; healthy worker effect; epidemiologic methods
Guidelines for prevention of mother-to-child transmission of HIV have developed rapidly, yet little is known about how outcomes of HIV-exposed infants have changed over time. We describe HIV-exposed infant outcomes in Kinshasa, Democratic Republic of Congo, between 2007 and 2013.
Cohort study of mother–infant pairs enrolled in family-centered comprehensive HIV care.
Accounting for competing risks, we estimated the cumulative incidences of early infant diagnosis, HIV transmission, death, loss to follow-up, and combination antiretroviral therapy (cART) initiation for infants enrolled in three periods (2007–2008, 2009–2010, and 2011–2012).
1707 HIV-exposed infants enrolled at a median age of 2.6 weeks. Among infants whose mothers had recently enrolled into HIV care (N = 1411), access to EID by age two months increased from 28% (95% confidence limits [CL]: 24,34%) among infants enrolled in 2007-2008 to 63% (95% CL: 59,68%) among infants enrolled in 2011–2012 (Gray's p-value <0.01). The 18-month cumulative incidence of HIV declined from 16% (95% CL: 11,22%) for infants enrolled in 2007–2008 to 11% (95% CL: 8,16%) for infants enrolled in 2011–2012 (Gray's p-value = 0.19). The 18-month cumulative incidence of death also declined, from 8% (95% CL: 5,12%) to 3% (95% CL: 2,5%) (Gray's p-value = 0.02). LTFU did not improve, with 18-month cumulative incidences of 19% (95% CL: 15,23%) for infants enrolled in 2007-2008 and 22% (95% CL: 18,26%) for infants enrolled in 2011–2012 (Gray's p-value = 0.06). Among HIV-infected infants, the 24-month cumulative incidence of cART increased from 61% (95% CL: 43,75%) to 97% (95% CL: 82,100%) (Gray's p-value < 0.01); the median age at cART decreased from 17.9 to 9.3 months. Outcomes were better for infants whose mothers enrolled before pregnancy.
We observed encouraging improvements, but continued efforts are needed.
Democratic Republic of Congo; HIV-exposed infant; mother-infant pair; pediatric HIV; prevention of mother-to-child HIV transmission/vertical transmission
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
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
To estimate the clinical benefit of HAART initiation versus deferral in a given month among patients with CD4 counts <800 cells/µL.
In this observational cohort study of HIV-1 seroconverters from CASCADE, we constructed monthly sequential nested subcohorts from 1/1996 to 5/2009 including all eligible HAART-naïve, AIDS-free individuals with a CD4 count <800 cells/uL. The primary outcome was time to AIDS or death among those who initiated HAART in the baseline month compared to those who did not, pooled across subcohorts and stratified by CD4. Using inverse-probability-of-treatment-weighted survival curves and Cox proportional hazards models, we estimated the absolute and relative effect of treatment with robust 95% confidence intervals (in parentheses).
Of 9,455 patients with 52,268 person-years of follow-up, 812 (8.6%) developed AIDS and 544 (5.8%) died. Within CD4 strata of 200–349, 350–499, and 500–799 cells/µL, HAART initiation was associated with adjusted hazard ratios for AIDS/death of 0.59 (0.43,0.81), 0.75 (0.49,1.14), and 1.10 (0.67,1.79), respectively; and with adjusted 3-year cumulative risk differences of −4.8% (−7.0%,−2.6%), −2.9% (−5.0%,−0.9%), and 0.3% (−3.7%,4.2%), respectively. In the analysis of all-cause mortality, HAART initiation was associated with adjusted hazard ratios of 0.71 (0.44,1.15), 0.51 (0.33,0.80) and 1.02 (0.49,2.12), respectively. Numbers needed to treat to prevent one AIDS event or death within 3 years were 21 (14,38) and 34 (20,115) in CD4 strata of 200–349 and 350–499 cells/µL, respectively.
Compared to deferring in a given month, HAART initiation at CD4 counts <500 (but not 500–799) cells/µL was associated with slower disease progression.
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.
Positivity, or the experimental treatment assignment assumption, requires that there be both exposed and unexposed participants at every combination of the values of the observed confounders in the population under study. Positivity is essential for inference but is often overlooked in practice by epidemiologists. This issue of the Journal includes 2 articles featuring discussions related to positivity. Here the authors define positivity, distinguish between deterministic and random positivity, and discuss the 2 relevant papers in this issue. In addition, the commentators illustrate positivity in simple 2 × 2 tables, as well as detail some ways in which epidemiologists may examine their data for nonpositivity and deal with violations of positivity in practice.
causality; causal inference; confounding factors (epidemiology); epidemiologic methods; exchangeability; identifiability; multilevel analysis; propensity score
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
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