Analysis of failure time data with dependent interval censoring

This article develops a method for the analysis of screening data for which the chance of being screened is dependent on the event of interest (informative censoring). Because not all subjects make all screening visits, the data on the failure of interest is interval censored. We propose a model that will properly adjust for the dependence to obtain an unbiased estimate of the nonparametric failure time function, and we provide an extension for applying the method for estimation of the regression parameters from a (discrete time) proportional hazards regression model. The method is applied on a data set from an observational study of cytomegalovirus shedding in a population of HIV-infected subjects who participated in a trial conducted by the AIDS Clinical Trials Group.     

Applying the Cox proportional hazards model when the change time of a binary time-varying covariate is interval censored

This paper develops methodology for estimation of the effect of a binary time-varying covariate on failure times when the change time of the covariate is interval censored. The motivating example is a study of cytomegalovirus (CMV) disease in patients with human immunodeficiency virus (HIV) disease. We are interested in determining whether CMV shedding predicts an increased hazard for developing active CMV disease. Since a clinical screening test is needed to detect CMV shedding, the time that shedding begins is only known to lie in an interval bounded by the patient's last negative and first positive tests. In a Cox proportional hazards model with a time-varying covariate for CMV shedding, the partial likelihood depends on the covariate status of every individual in the risk set at each failure time. Due to interval censoring, this is not always known. To solve this problem, we use a Monte Carlo EM algorithm with a Gibbs sampler embedded in the E-step. We generate multiple completed data sets by drawing imputed exact shedding times based on the joint likelihood of the shedding times and event times under the Cox model. The method is evaluated using a simulation study and is applied to the data set described above.     

Generalized log-rank tests for partly interval-censored failure time data

In this paper, we consider incomplete survival data: partly interval-censored failure time data where observed data include both exact and interval-censored observations on the survival time of interest. We present a class of generalized log-rank tests for this type of survival data and establish their asymptotic properties. The method is evaluated using simulation studies and illustrated by a set of real data from a diabetes study.     

Regression analysis of multivariate interval-censored failure time data with application to tumorigenicity experiments

This paper discusses multivariate interval-censored failure time data that occur when there exist several correlated survival times of interest and only interval-censored data are available for each survival time. Such data occur in many fields. One is tumorigenicity experiments, which usually concern different types of tumors, tumors occurring in different locations of animals, or together. For regression analysis of such data, we develop a marginal inference approach using the additive hazards model and apply it to a set of bivariate interval-censored data arising from a tumorigenicity experiment. Simulation studies are conducted for the evaluation of the presented approach and suggest that the approach performs well for practical situations.     

A multistate model for bivariate interval-censored failure time data

SUMMARY: Interval-censored life-history data arise when the events of interest are only detectable at periodic assessments. When interest lies in the occurrence of two such events, bivariate-interval censored event time data are obtained. We describe how to fit a four-state Markov model useful for characterizing the association between two interval-censored event times when the assessment times for the two events may be generated by different inspection processes. The approach treats the two events symmetrically and enables one to fit multiplicative intensity models that give estimates of covariate effects as well as relative risks characterizing the association between the two events. An expectation-maximization (EM) algorithm is described for estimation in which the maximization step can be carried out with standard software. The method is illustrated by application to data from a trial of HIV patients where the events are the onset of viral shedding in the blood and urine among individuals infected with cytomegalovirus.     

Sieve Estimation for the Cox Model with Clustered Interval-Censored Failure Time Data

Clustered interval-censored failure time data occur when the failure times of interest are clustered into small groups and known only to lie in certain intervals. A number of methods have been proposed for regression analysis of clustered failure time data, but most of them apply only to clustered right-censored data. In this paper, a sieve estimation procedure is proposed for fitting a Cox frailty model to clustered interval-censored failure time data. In particular, a two-step algorithm for parameter estimation is developed and the asymptotic properties of the resulting sieve maximum likelihood estimators are established. The finite sample properties of the proposed estimators are investigated through a simulation study and the method is illustrated by the data arising from a lymphatic filariasis study.     

Analysis of doubly-censored survival data, with application to AIDS

This paper proposes nonparametric and weakly structured parametric methods for analyzing survival data in which both the time origin and the failure event can be right- or interval-censored. Such data arise in clinical investigations of the human immunodeficiency virus (HIV) when the infection and clinical status of patients are observed only at several time points. The proposed methods generalize the self-consistency algorithm proposed by Turnbull (1976, Journal of the Royal Statistical Society, Series B 38, 290-295) for singly-censored univariate data, and are illustrated with the results from a study of hemophiliacs who were infected with HIV by contaminated blood factor.     

Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty

A simple, validated protocol consisting of a battery of tests is available to identify elderly patients with frailty syndrome. This syndrome of decreased reserve and resistance to stressors increases in incidence with increasing age. In the elderly, frailty may pursue a step-wise loss of function from non-frail to pre-frail to frail. We studied frailty in HIV-infected patients and found that ~20% are frail using the Fried phenotype using stringent criteria developed for the elderly^1,2. In HIV infection the syndrome occurs at a younger age.HIV patients were checked for 1) unintentional weight loss; 2) slowness as determined by walking speed; 3) weakness as measured by a grip dynamometer; 4) exhaustion by responses to a depression scale; and 5) low physical activity was determined by assessing kilocalories expended in a week''s time. Pre-frailty was present with any two of five criteria and frailty was present if any three of the five criteria were abnormal.The tests take approximately 10-15 min to complete and they can be performed by medical assistants during routine clinic visits. Test results are scored by referring to standard tables. Understanding which of the five components contribute to frailty in an individual patient can allow the clinician to address relevant underlying problems, many of which are not evident in routine HIV clinic visits.     

A goodness-of-fit test for the marginal Cox model for correlated interval-censored failure time data

The marginal Cox model approach is perhaps the most commonly used method in the analysis of correlated failure time data (Cai, 1999; Cai and Prentice, 1995; Lin, 1994; Wei, Lin and Weissfeld, 1989). It assumes that the marginal distributions for the correlated failure times can be described by the Cox model and leaves the dependence structure completely unspecified. This paper discusses the assessment of the marginal Cox model for correlated interval-censored data and a goodness-of-fit test is presented for the problem. The method is applied to a set of correlated interval-censored data arising from an AIDS clinical trial.     

Maximum likelihood estimation for interval-censored data using a Weibull-based accelerated failure time model.

The accelerated failure time regression model is most commonly used with right-censored survival data. This report studies the use of a Weibull-based accelerated failure time regression model when left- and interval-censored data are also observed. Two alternative methods of analysis are considered. First, the maximum likelihood estimates (MLEs) for the observed censoring pattern are computed. These are compared with estimates where midpoints are substituted for left- and interval-censored data (midpoint estimator, or MDE). Simulation studies indicate that for relatively large samples there are many instances when the MLE is superior to the MDE. For samples where the hazard rate is flat or nearly so, or where the percentage of interval-censored data is small, the MDE is adequate. An example using Framingham Heart Study data is discussed.     

Inference for set-based effects in genetic association studies with interval-censored outcomes

The rapid acceleration of genetic data collection in biomedical settings has recently resulted in the rise of genetic compendiums filled with rich longitudinal disease data. One common feature of these data sets is their plethora of interval-censored outcomes. However, very few tools are available for the analysis of genetic data sets with interval-censored outcomes, and in particular, there is a lack of methodology available for set-based inference. Set-based inference is used to associate a gene, biological pathway, or other genetic construct with outcomes and is one of the most popular strategies in genetics research. This work develops three such tests for interval-censored settings beginning with a variance components test for interval-censored outcomes, the interval-censored sequence kernel association test (ICSKAT). We also provide the interval-censored version of the Burden test, and then we integrate ICSKAT and Burden to construct the interval censored sequence kernel association test—optimal (ICSKATO) combination. These tests unlock set-based analysis of interval-censored data sets with analogs of three highly popular set-based tools commonly applied to continuous and binary outcomes. Simulation studies illustrate the advantages of the developed methods over ad hoc alternatives, including protection of the type I error rate at very low levels and increased power. The proposed approaches are applied to the investigation that motivated this study, an examination of the genes associated with bone mineral density deficiency and fracture risk.     

A simple local sensitivity analysis tool for nonignorable coarsening: application to dependent censoring

Right- and interval-censored data are common special cases of coarsened data (Heitjan and Rubin, 1991, Annals of Statistics19, 2244-2253). As with missing data, standard statistical methods that ignore the random nature of the coarsening mechanism may lead to incorrect inferences. We extend a simple sensitivity analysis tool, the index of local sensitivity to nonignorability (Troxel, Ma, and Heitjan, 2004, Statistica Sinica14, 1221-1237), to the evaluation of nonignorability of the coarsening process in the general coarse-data model. By converting this index into a simple graphical display one can easily assess the sensitivity of key inferences to nonignorable coarsening. We illustrate the validity of the method with a simulated example, and apply it to right-censored data from an observational study of cardiac transplantation and to interval-censored data on time to detectable viral load from a clinical trial in HIV disease.     

Persistent and selective deficiency of CD4+ T cell immunity to cytomegalovirus in immunocompetent young children

Healthy young children who acquire CMV have prolonged viral shedding into the urine and saliva, but whether this is attributable to limitations in viral-specific immune responses has not been explored. In this study, we found that otherwise immunocompetent young children after recent primary CMV infection accumulated markedly fewer CMV-specific CD4(+) T cells that produced IFN-gamma than did adults. These differences in CD4(+) T cell function persisted for more than 1 year after viral acquisition, and did not apply to CMV-specific IFN-gamma production by CD8(+) T cells. The IFN-gamma-producing CD4(+) T cells of children or adults that were reactive with CMV Ags were mainly the CCR7(low) cell subset of memory (CD45R0(high)CD45RA(low)) cells. The decreased IFN-gamma response to CMV in children was selective, because their CCR7(low) memory CD4(+) T cells and those of adults produced similar levels of this cytokine after stimulation with staphylococcal enterotoxin B superantigen. CD4(+) T cells from children also had reduced CMV-specific IL-2 and CD154 (CD40 ligand) expression, suggesting an early blockade in the differentiation of viral-specific CD4(+) T cells. Following CMV acquisition, children, but not adults, persistently shed virus in urine, and this was observable for at least 29 mo postinfection. Thus, CD4(+) T cell-mediated immunity to CMV in humans is generated in an age-dependent manner, and may have a substantial role in controlling renal viral replication and urinary shedding.     

Effect of Genital Herpes on Cervicovaginal HIV Shedding in Women Co-Infected with HIV AND HSV-2 in Tanzania

Objectives

To compare the presence and quantity of cervicovaginal HIV among HIV seropositive women with clinical herpes, subclinical HSV-2 infection and without HSV-2 infection respectively; to evaluate the association between cervicovaginal HIV and HSV shedding; and identify factors associated with quantity of cervicovaginal HIV.

Design

Four groups of HIV seropositive adult female barworkers were identified and examined at three-monthly intervals between October 2000 and March 2003 in Mbeya, Tanzania: (1) 57 women at 70 clinic visits with clinical genital herpes; (2) 39 of the same women at 46 clinic visits when asymptomatic; (3) 55 HSV-2 seropositive women at 60 clinic visits who were never observed with herpetic lesions; (4) 18 HSV-2 seronegative women at 45 clinic visits. Associations of genital HIV shedding with HIV plasma viral load (PVL), herpetic lesions, HSV shedding and other factors were examined.

Results

Prevalence of detectable genital HIV RNA varied from 73% in HSV-2 seronegative women to 94% in women with herpetic lesions (geometric means 1634 vs 3339 copies/ml, p = 0.03). In paired specimens from HSV-2 positive women, genital HIV viral shedding was similar during symptomatic and asymptomatic visits. On multivariate regression, genital HIV RNA (log₁₀ copies/mL) was closely associated with HIV PVL (β = 0.51 per log₁₀ copies/ml increase, 95%CI:0.41–0.60, p<0.001) and HSV shedding (β = 0.24 per log₁₀ copies/ml increase, 95% CI:0.16–0.32, p<0.001) but not the presence of herpetic lesions (β = −0.10, 95%CI:−0.28–0.08, p = 0.27).

Conclusions

HIV PVL and HSV shedding were more important determinants of genital HIV than the presence of herpetic lesions. These data support a role of HSV-2 infection in enhancing HIV transmissibility.     

Low Levels of Mannan-Binding Lectin or Ficolins Are Not Associated with an Increased Risk of Cytomegalovirus Disease in HIV-Infected Patients

Background

In HIV-infected patients, prediction of Cytomegalovirus (CMV) disease remains difficult. A protective role of mannan-binding lectin (MBL) and ficolins against CMV disease has been reported after transplantation, but the impact in HIV-infected patients is unclear.

Methods

In a case-control study nested within the Swiss HIV Cohort Study, we investigated associations between plasma levels of MBL/ficolins and CMV disease. We compared HIV-infected patients with CMV disease (cases) to CMV-seropositive patients without CMV disease (controls) matched for CD4 T-cells, sampling time, and use of combination antiretroviral therapy. MBL and M-ficolin, L-ficolin, and H-ficolin were quantified using ELISA.

Results

We analysed 105 cases and 105 matched controls. CMV disease was neither associated with MBL (odds ratio [OR] 1.03 per log₁₀ ng/mL increase (95% CI 0.73–1.45)) nor with ficolins (OR per log₁₀ ng/mL increase 0.66 (95% CI 0.28–1.52), 2.34 (95% CI 0.44–12.36), and 0.89 (95% CI 0.26–3.03) for M-ficolin, L-ficolin, and H-ficolin, respectively). We found no evidence of a greater association between MBL and CMV disease in patients with low CD4 counts; however in the multivariable analysis, CMV disease was more likely in patients with an increased HIV RNA (OR 1.53 per log₁₀ copies/mL; 95% CI 1.08–2.16), or a shorter duration of HIV-infection (OR 0.91 per year; 95% CI 0.84–0.98).

Conclusions

CMV disease is not associated with low levels of MBL/ficolins, suggesting a lack of a protective role in HIV-infected patients.     

Cytomegalovirus Replication and the Host Immune Response

Cytomegalovirus (CMV) is closely associated with host cellular structures, and this has a significant impact upon the immunologic response following infection. CMV may be recovered from a variety of body secretions and fluids during acute infection, and protracted shedding may supervene in some instances. The reasons for a variable host response to CMV infection remain unclear, and the mechanisms responsible for the establishment of persistence have not been worked out. CMV persistence and latency are discussed, and some recently derived relevant data are presented. An animal model has been developed consistent with clinical observations pertaining to CMV transmission with blood. Results obtained in the course of these and other studies support the concept of immunological activation of latent CMV. The timing of CMV infection relative to an unrelated antigenic challenge is probably critical in determining the emergence of immunodepression or enhancement. Some aspects of CMV sero-diagnosis are also reviewed.     

What Triggers a Diagnosis of HIV Infection in the Tokyo Metropolitan Area? Implications for Preventing the Spread of HIV Infection in Japan

Background

Japan has not succeeded in reducing the annual number of new HIV-infected patients, although the prevalence of HIV infection is low (0.02%).

Methods

A single-center observational study was conducted at the largest HIV clinic in Tokyo, which treats 15% of the total patients in Japan, to determine the reasons for having diagnostic tests in newly infected individuals. HIV-infected patients who visited our clinic for the first time between 2011 and 2014 were analyzed.

Results

The 598 study patients comprised one-third of the total reported number of new patients in Tokyo during the study period. 76% were Japanese MSM. The reasons for being tested which led to the diagnosis was voluntary testing in 32%, existing diseases in 53% (AIDS-defining diseases in 22%, sexually transmitted infections (STI) in 8%, diseases other than AIDS or STIs in 23%) and routine pre-surgery or on admission screening in 15%. 52% and 74% of the study patients and patients presented with AIDS, respectively, had never been tested. The median CD4 count in patients with history of previous testing (315/μL) was significantly higher than that of patients who had never been tested (203/μL, p<0.001).

Conclusions

Only 32% of the newly HIV diagnosed patients were diagnosed because of voluntary testing, and 53% were diagnosed due to presence of other diseases. These results remain unchanged from our previous report 10 years earlier (2000–2004) on newly diagnosed patients at the same clinic. HIV testing has not been widely used by newly diagnosed patients in the Tokyo metropolitan area.     

CMV+ Serostatus Associates Negatively with CD4:CD8 Ratio Normalization in Controlled HIV-Infected Patients on cART

Cytomegalovirus (CMV) infection is common among HIV-infected patients but its repercussion on the course of CD4+ and CD8+ T cells after cART initiation remains elusive. The French Dat''AIDS cohort enrolled 5,688 patients on first-line cART, from which we selected patients who achieved HIV suppression for at least 12 months without modification of cART, and for whom CMV serostatus was available. Five hundred and three patients fulfilled the selection criteria (74% male, median age 43 yrs, 15.5% CDC stage C), of whom 444 (88.3%) were seropositive for CMV (CMV+). Multivariate analyses using mixed-linear models adjusted for the time from HIV suppression, sex, age, transmission risk group, duration of HIV follow-up, the interaction between time from HIV suppression and CMV+ serology, and the nadir CD4 count revealed a negative correlation between CMV+ and CD4:CD8 ratio (coeff. = -0.16; p = 0.001). This correlation was also observed among patients displaying optimal CD4 recovery (≥500 cells/mm3 at M12; coeff. = -0.24; p = 0.002). Hence, CMV+ serostatus antagonizes normalization of the CD4:CD8 ratio, although further analyses of the impact of co-morbidities that associate with CMV serostatus, like HCV infection, are needed to elucidate this antagonism formally. However, this might reflect a premature T cell senescence, thus advocating for a close monitoring of T cells in CMV co-infected patients. In addition, our results raise the question of the benefit of treatment for asymptomatic CMV co-infection in HIV-infected patients.     

A semiparametric model for regression analysis of interval-censored failure time data

Left-, right-, and interval-censored response time data arise in a variety of settings, including the analyses of data from laboratory animal carcinogenicity experiments, clinical trials, and longitudinal studies. For such incomplete data, the usual regression techniques such as the Cox (1972, Journal of the Royal Statistical Society, Series B 34, 187-220) proportional hazards model are inapplicable. In this paper, we present a method for regression analysis which accommodates interval-censored data. We present applications of this methodology to data sets from a study of breast cancer patients who were followed for cosmetic response to therapy, a small animal tumorigenicity study, and a clinical trial.     

Survival analysis in clinical trials: past developments and future directions

The field of survival analysis emerged in the 20th century and experienced tremendous growth during the latter half of the century. The developments in this field that have had the most profound impact on clinical trials are the Kaplan-Meier (1958, Journal of the American Statistical Association 53, 457-481) method for estimating the survival function, the log-rank statistic (Mantel, 1966, Cancer Chemotherapy Report 50, 163-170) for comparing two survival distributions, and the Cox (1972, Journal of the Royal Statistical Society, Series B 34, 187-220) proportional hazards model for quantifying the effects of covariates on the survival time. The counting-process martingale theory pioneered by Aalen (1975, Statistical inference for a family of counting processes, Ph.D. dissertation, University of California, Berkeley) provides a unified framework for studying the small- and large-sample properties of survival analysis statistics. Significant progress has been achieved and further developments are expected in many other areas, including the accelerated failure time model, multivariate failure time data, interval-censored data, dependent censoring, dynamic treatment regimes and causal inference, joint modeling of failure time and longitudinal data, and Baysian methods.