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R Brookmeyer

Publications and source records attributed to R Brookmeyer.

At least 37 records · Page 2Linked to original sources
PubMed1996

Bivariate frailty model for the analysis of multivariate survival time.

Because of limitations of the univariate frailty model in analysis of multivariate survival data, a bivariate frailty model is introduced for the analysis of bivariate survival data. This provides tremendous flexibility especially in allowing negative associations between subjects within the same cluster. The approach involves incorporating into the model two possibly correlated frailties for each cluster. The bivariate lognormal distribution is used as the frailty distribution. The model is then generalized to multivariate survival data with two distinguished groups and also to alternating process data. A modified EM algorithm is developed with no requirement of specification of the baseline hazards. The estimators are generalized maximum likelihood estimators with subject-specific interpretation. The model is applied to a mental health study on evaluation of health policy effects for inpatient psychiatric care.

Algorithms↗
PubMed1996

Differences in the incidence of hepatitis B and human immunodeficiency virus infections among injecting drug users.

Both hepatitis B virus (HBV) and human immunodeficiency virus (HIV) type 1 seroconversions have been considered as outcome measures to evaluate the effectiveness of needle exchange programs. To assess the relationships between incident HBV and HIV infections among injecting drug users (IDUs), seroconversions were prospectively studied among a cohort of 240 HBV- and HIV- seronegative IDUs. The incidence of HBV seroconversion declined from 24.41/100 person-years in 1988 to 0 seroconversions in 1992. In contrast, HIV seroconversion rates varied little from the overall rate of 3.29/100 person-years. HBV seroconversion predicted subsequent HIV seroconversion among male IDUs (relative incidence [RI]= 4.23) but not among female IDUs (RI=0.86). Because of different transmission dynamics, HBV seroconversion probably has limited utility as a surrogate outcome measure for incident HIV. However, HBV seroconversion itself is an appropriate and important outcome measure for evaluation of prevention programs among IDUs.

Adult↗
PubMed1996

Statistical issues in prevention and therapeutic trials of Alzheimer disease.

Relatively little attention has been given to the proper design and statistical analysis of prevention and therapeutic trials of Alzheimer disease (AD). A number of important methodological issues arise in studies of AD that do not typically arise in studies of other chronic diseases. These issues include: the definition of the primary study endpoint that is simple to measure and easy to interpret; proper design of trials that take into account that the patient population is very old; and the proper statistical analysis that addresses the high drop out rate and the multiple ways of measuring disease severity. Addressing these issues will speed the progress of the evaluation of promising compounds to prevent and treat AD.

Alzheimer Disease↗
PubMed1996

AIDS, epidemics, and statistics.

Statistical thinking has made significant contributions to our understanding of epidemics. Examples where statistics has played an important role in the Acquired Immunodeficiency Syndrome (AIDS) epidemic include estimating the number of individuals infected with the human immunodeficiency virus, estimating the incubation period of the disease, studying the etiology of the disease, and monitoring and forecasting the course of the epidemic. Some parallels with other epidemics in history are drawn. The AIDS epidemic has also raised important questions about the design of clinical studies and whether classical approaches are sufficiently flexible to provide timely answers to therapeutic questions in a growing epidemic. In a public crisis, there is a sense of urgency and data may be collected with unusual sampling schemes and inherent biases. Attention needs to be paid as much to sampling variation as to systematic sources of bias. Accurate disease surveillance data and methods for analyzing such data are crucial for detecting and monitoring future epidemics. There will almost certainly be new epidemics in the future, either of old diseases resurfacing or of new diseases, and statistical reasoning will continue to play a significant role in addressing the challenges of these public health crises.

Acquired Immunodeficiency Syndrome↗
PubMed1995

The AIDS epidemic in India: a new method for estimating current human immunodeficiency virus (HIV) incidence rates.

Human immunodeficiency virus (HIV) incidence rates in India were estimated using a new method that accounts for follow-up bias. Follow-up bias arises in epidemiologic cohort studies when the incidence rate among individuals who do and do not return for follow-up are different. The new method combines data on the prevalence of p24 antigenemia among all those initially screened together with the longitudinal follow-up data on the subset of patients who returned for follow-up. Using these methods, the current HIV incidence rate among patients attending sexually transmitted disease clinics in Pune, India, was 18.6% per year. It was found that follow-up bias can cause significant underestimation in HIV incidence rates, perhaps by as much as 60%. These incidence estimates, together with other HIV seroprevalence studies, suggest the HIV epidemic in India is growing rapidly.

Acquired Immunodeficiency Syndrome↗
PubMed1995

Estimation of current human immunodeficiency virus incidence rates from a cross-sectional survey using early diagnostic tests.

In sharp contrast to the considerable worldwide epidemiologic data available on acquired immunodeficiency syndrome incidence and human immunodeficiency virus (HIV) seroprevalence, there is relatively little information about current levels of HIV incidence rates. The authors suggest a novel approach for estimating current HIV incidence rates based on a single cross-sectional survey and on an epidemiologic model. The approach is based on diagnostic tests for HIV p24 antigen to identify individuals in the preantibody or window period (time between exposure to HIV and appearance of detectable HIV antibodies). Individuals in the preantibody period are likely to have been infected very recently because the duration of the preantibody period is relatively short. The authors report data on the duration of p24 antigenemia prior to HIV seroconversion. This duration together with the prevalence of p24 antigenemia obtained from a cross-sectional survey are used in an epidemiologic model to estimate current incidence rates. This approach of estimating incidence rates may be especially useful in developing countries and high-risk populations in which it is difficult to follow cohorts to identify seroconverters, and in the design of vaccine efficacy studies in which current incidence rates are crucial for calculating sample sizes.

Cross-Sectional Studies↗
PubMed1995

Managed mental health care and patterns of inpatient utilization for treatment of affective disorders.

In this analysis we made use of a large data base of individuals insured by large American corporations to estimate the impact of managed care provision on hospital care for depression. Data on 6,348 individuals hospitalized for depression were examined to assess the effect of managed care techniques on the cost per episode and the likelihood of rehospitalization. Preadmission certification programs were found to lead to significant long- and short-run savings for payers.

Adult↗
PubMed1995

Sources of variability in prevalence rates of Alzheimer's disease.

OBJECTIVE: To investigate potential methodological reasons for the differences in published Alzheimer's disease (AD) prevalence rates. BACKGROUND: Studies reporting prevalence rates of AD have been published worldwide. These rates differ considerably, but may greatly reflect methodological differences. METHODS: All studies published between 1984 and 1993 that reported age-specific AD rates and sample sizes were included. Logistic regression identified variables that contribute to the variation in rates. Estimates of extrabinomial variation were also calculated. RESULTS: Studies characterized by the following features yielded significantly higher rates: inclusion of mild cases, use of laboratory studies, ascertainment of a sample rather than the total population, inclusion of both urban and rural populations, non-use of computerized tomography (CT) scans, non-use of the Hachinski Ischemic Score, and no adjustment for false negatives. The odds of having AD increased 18% for every year of age. The variation in the age-specific prevalence rates of AD was approximately 15 times that expected by sampling variation. However, approximately 76% of this excess variation in rates could be accounted for by methodological differences. CONCLUSIONS: After accounting for age, much of the variability in prevalence rates of AD in the published literature may be explained by differences in methodology. Some unexplained variation in prevalence rates, however, still remains.

Age Factors↗
PubMed1995

Reliability of the Blessed Telephone Information-Memory-Concentration Test.

In-person cognitive evaluations can be costly and labor intensive in geographically widespread populations. Reliable telephone instruments that screen for cognitive status would greatly facilitate epidemiologic and other longitudinal studies. We evaluated the reliability of the Blessed Information-Memory-Concentration (IMC) test when administered by telephone. Eighty-four subjects with a wide range of cognitive abilities were administered the Blessed IMC twice over a 3-week interval. Forty-nine of the subjects were administered the test both by telephone and in-person, and 35 of the subjects were tested twice by telephone. Spearman's rank correlation was used to compare scores of the different administrations (.96; P < .001) and to examine test-retest reliability (.96; P < .001). The Blessed Telephone IMC (TIMC) test exhibits excellent reliability both when compared to in-person administration as well as in test-retest results. The Blessed TIMC appears to be a practical instrument for population and longitudinal studies when in-person assessment is not feasible.

Aged↗
PubMed1995

Statistical analysis of passive surveillance disease registry data.

Passive surveillance disease data involve a registry of individuals who are at risk of disease and who are not under active follow up. The most serious limitations with such data are incomplete ascertainment of cases of disease and little or no follow-up information on patient vital status. This paper considers whether it is possible to estimate disease risk from such data and, if not, what additional information is required. In general, relative risks based on passive surveillance data will be biased even under the assumption that the probability of disease reporting and the hazard of death from other causes are the same for all individuals in the registry. However if the disease is rare, this bias is negligible. Methods are developed for estimating absolute disease incidence rates by combining passive surveillance data with a cohort study. Analytic approaches are proposed for the situations when death rates from all other causes are known and also unknown, and it is found that there is little loss in efficiency even if death rates are not known. There are considerable gains in efficiency for estimating absolute disease incidence rates by supplementing a cohort study with passive surveillance registry data compared to using the cohort study alone, especially if the exposure is rare and the cohort study is small relative to the size of the registry. Intuitively, the cohort data provides information about absolute rates of disease, while the passive surveillance data provides information about relative risks. The methods are applied to a registry of patients with an artificial heart valve that is at risk of breaking.

Cohort Studies↗
PubMed1995

An empirical Bayes approach to smoothing in backcalculation of HIV infection rates.

Backcalculation is a methodology to reconstruct the past human immunodeficiency virus (HIV) infection rates from the AIDS incidence data and incubation distribution by deconvolution. Smoothing has proved important in backcalculation, and a key question is how to choose the amount of smoothing. This paper proposes an empirical Bayes approach in which the smoothing parameter is estimated from the data. We introduce a family of priors that reflect the notion of closeness of neighboring infection rates. The variance parameter in the prior family plays the role of the smoothing parameter and is estimated by a method similar to the residual maximum likelihood in linear random effects model through an efficient EM (expectation/maximization) algorithm. A number of penalized likelihood functions that have been used in backcalculation have an empirical Bayes formulation. A bootstrap confidence interval for the infection rates is proposed. The methodology is illustrated with United States AIDS incidence data.

Acquired Immunodeficiency Syndrome↗
PubMed1993

The evolution of virus diseases: their emergence, epidemicity, and control.

The evolution of virus diseases, both their emergence and disappearance, involves complex interactions between the agent, the host, and the environment. These themes are illustrated by three examples, poliomyelitis of humans, bovine spongiform encephalopathy of cattle, and AIDS of humans. Emergence may be due to evolution of the virus genome, such as probably occurred in parvovirus infection of dogs and human immunodeficiency virus infection of humans. However, emergence of some new viral diseases can be traced to host or environmental factors with no change in the agent. Poliomyelitis, an enteric infection, probably emerged as an epidemic disease due to improvements in personal hygiene and public sanitation which led to a delay in the occurrence of initial infections from the perinatal period (when maternal antibody protected against paralysis) to later childhood when passive immunity had waned. Bovine spongiform encephalopathy is a common source epidemic which was transmitted through nutritional supplements which became contaminated due to a change in the method of production of bone meal supplements in rendering plants. The reduction of disappearance of virus diseases usually involves human intervention, as exemplified by immunization for smallpox and other virus diseases of humans and animals. Naturally occurring immunity may lead to fadeout of a virus as seen with measles in isolated island populations. Evolution of a virus can also result in waning of a disease as seen with myxomatosis among rabbits in Australia. The evolution of virus diseases is a provocative scientific topic and carries lessons relevant to the control of important diseases of humans, animals, and plants.

Acquired Immunodeficiency Syndrome↗
PubMed1993

Analysis of infectious disease data from partner studies with unknown source of infection.

Partner studies are useful for estimating the transmission probabilities of infectious diseases. However, it is often not known which partner was the source of the infection (the index case). The objective of this paper is to develop statistical methods for analyzing partner studies when it is uncertain which partners acquired the infection from sources outside the partnership. The approach involves simultaneously modelling the probability of acquisition of infection from outside the partnership, and the probability of transmission within the partnership as a function of covariates. An EM algorithm is presented. Efficiency and simulation results are given in some special situations involving heterosexual transmission studies. In heterosexual partner studies, the methods depend crucially on the availability of a covariate that provides information about which partner was the likely source of infection.

Algorithms↗
PubMed1993

Statistical models for prevalent cohort data.

In prospective cohort studies individuals are sometimes recruited according to a certain cross-sectional sampling criterion. A prevalent cohort is defined as a group of individuals who have a certain disease at enrollment into the study. Statistical models for the analysis of prevalent cohort data are considered when the onset or diagnosis time of the disease is known. The incident proportional hazards model, where the time scale is duration with disease, is compared to the prevalent proportional hazards model, where the fundamental time scale is follow-up time. In certain cases the time of enrollment may coincide with another event (such as the initiation of treatment). This situation is also considered and its limitations highlighted. To illustrate the methodological ideas discussed in the paper, the analysis of data from an observational study of zidovudine (ZVD) in patients with the acquired immunodeficiency syndrome (AIDS) is presented.

Acquired Immunodeficiency Syndrome↗
PubMed1992

Projections of the number of persons diagnosed with AIDS and the number of immunosuppressed HIV-infected persons--United States, 1992-1994.

This report presents projections of the number of persons who will initially be diagnosed with a condition included in the 1987 surveillance definition for acquired immunodeficiency syndrome (AIDS) in the United States during the period 1992-1994. The report also presents estimates and projections of the prevalence of persons infected with the human immunodeficiency virus (HIV) who have CD4+ T-lymphocyte (T-cell) counts < 200/microL and who have not been diagnosed with a condition listed in the 1987 AIDS surveillance definition. These estimates and projections are used to predict the effect of expanding the AIDS surveillance definition to include all HIV-infected persons with a CD4+ T-cell count < 200/microL. Approximately 58,000 persons were diagnosed with AIDS in the United States during 1991. During the period 1992-1994, the number of persons newly diagnosed with AIDS is expected to increase by at most a few percent annually, with approximately 60,000-70,000 persons diagnosed per year. Although AIDS diagnoses among homosexual and bisexual men and among injecting drug users are projected to reach a plateau during this period, the number of AIDS diagnoses among persons whose HIV infection is attributed to heterosexual transmission of HIV is likely to continue to increase through 1994. The number of living persons who have been diagnosed with AIDS is expected to increase from approximately 90,000 in January 1992 to approximately 120,000 in January 1995. There is, however, considerable uncertainty in these projections. For example, the plausible range for the number of persons initially diagnosed with AIDS in 1994 is 43,000-93,000. CDC estimates that, as of January 1992, 115,000-170,000 U.S. residents had severe immunosuppression (a CD4+ T-cell count < 200 cells/microL without a diagnosis of AIDS in an HIV-infected person). Only about 50,000 of these persons were receiving medical care for HIV-related conditions and were known to have a CD4+ T-cell count < 200 cells/microL. The number of persons with severe immunosuppression is expected to increase to 130,000-205,000 by January 1995, with the actual number more likely to be in the lower half of this range than the upper half. The expanded AIDS surveillance definition, which includes severe immunosuppression, is predicted to result in an increase of approximately 75% in the number of persons reported during 1993, but an increase of < 20% in 1994 compared with the number of persons who would have been reported had the definition not been changed.(ABSTRACT TRUNCATED AT 400 WORDS)

Acquired Immunodeficiency Syndrome↗
PubMed1992

Effects of mid-point imputation on the analysis of doubly censored data.

Doubly censored data arise in some cohort studies of the AIDS incubation period because the time of infection may be known only up to an interval defined by two successive screening tests for HIV antibody. A simple analytic approach is to impute the infection time by the mid-point of the interval and then apply standard survival techniques for right censored data. The objective of this paper is to investigate the statistical properties of such a mid-point imputation approach. We investigated the asymptotic bias of the Kaplan-Meier estimate, coverage probabilities of associated confidence intervals, bias in hazard ratio, and the size of the logrank test. We show that the statistical properties of mid-point imputation depend strongly on the underlying distributions of infection times and the incubation periods, and the width of the interval between screening tests. In the absence of treatment, the median incubation period of HIV infection is approximately 10 years, and we conclude that, for this situation, mid-point imputation is a reasonable procedure for interval widths of 2 years or less.

Bias↗