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R L Prentice

Publications and source records attributed to R L Prentice.

At least 19 recordsLinked to original sources
PubMed2000

Future possibilities in the prevention of breast cancer: fat and fiber and breast cancer research.

The potential for a reduction in dietary fat or for an increase in dietary fiber to reduce breast cancer risk has been debated for some years. It is argued here that available research data, even though extensive, leave open hypotheses ranging from little or no potential to major public health potential for breast cancer prevention by means of these dietary maneuvers. Some elements of a research strategy for testing these and other dietary breast cancer prevention hypotheses are described.

Adult↗
PubMed2000

Dependence estimation over a finite bivariate failure time region.

This article concerns nonparametric estimation of association between bivariate failure times. In the presence of independent right censoring, the support for failure time variates may be restricted and measures of dependence over a finite failure time region may be of particular interest. To this end, the reciprocal cross ratio function, weighted by the bivariate failure time density, is proposed as a summary measure of dependence over a failure time region. This 'relative risk' estimator is shown to be consistent and asymptotically normally distributed, with consistent bootstrap variance estimator. A finite-region version of Kendall's tau, which is suitable for censored failure time data, is also proposed, and corresponding asymptotic distribution theory is noted. The accuracy of these asymptotic approximations is studied in simulations and an illustration is provided.

Adolescent↗
PubMed2000

Results of testing for anti-GM1 antibodies.

We used an ELISA technique to measure IgG and IgM antibodies to the ganglioside GM1, with the results expressed in arbitrary units. We tested 1007 sera from patients with peripheral neuropathy or muscle weakness. For IgG and IgM antibodies, the distribution of results differed significantly from a normal distribution. In the patient group, 81 of 1007 sera had elevated levels of IgG antibodies (> 10 units). Of these, 11 patients had very high levels (> 50 units). These 11 patients had diagnoses of GBS (4), motor neurone disease (3) or non-specific idiopathic neuropathy (4). For IgM antibodies, 115 of 1007 sera were positive (> 20 units). Of these, 18 patients had very high levels (> 50 units). These 18 patients had diagnoses of Guillain-Barré syndrome or Miller Fisher syndrome (4), multifocal motor neuropathy (4), motor neurone disease (2), non-specific neuropathy (2). We conclude that anti-GM1 antibodies in high titre are uncommon. Patients with multifocal motor neuropathy have high levels of antibody. However, patients with other disorders may also have high levels, so that anti-GM1 antibody levels alone are not a specific test for multifocal motor neuropathy. We found that antibodies to GM1 were present in the sera of patients with chronic idiopathic neuropathy, leading us to suggest that these antibodies may sometimes arise as a secondary response to disease.

Adult↗
PubMed1999

Study of diet, biomarkers and cancer risk in the United States, China and Costa Rica.

One striking paradox in epidemiologic research is the strong association between diet and cancer in ecologic studies compared with the weaker associations reported in many within-country case-control and cohort studies. However, most ecologic studies have relied on indirect measures of dietary intake, such as food disappearance data. The objectives of our study were to assess the feasibility of collecting dietary and biomarker data from individuals living in countries having markedly different dietary patterns and cultures and to examine the magnitude of the between-country variation in their measurement. Adults surveyed in Shanghai (China), Costa Rica and King County (Washington, USA) completed a 24-hr dietary recall, a cancer risk factor survey, and provided a blood sample. We analyzed a subset of the blood specimens for vitamins C, E, carotenoids and phospholipid fatty acids. We observed substantial differences in nutrient intakes and in mean plasma concentrations of dietary biomarkers across the study populations. For example, King County participants had the highest daily intake of vitamin C (mean 78.3 +/- 12.2 mg compared with 42.6 +/- 38.3 mg in Shanghai and 34.8 +/- 43.8 mg in Costa Rica). The mean plasma vitamin C level in King County was also the highest of the 3 study sites: 927.9 +/- 43.9 microg/dl in King County, 585.7 +/- 35.9 microg/dl in Shanghai and 461.1 +/- 33.1 microg/dl in Costa Rica. Plasma trans fatty acids (a biomarker of a diet high in hydrogenated fats) were highest in King County and lowest in Shanghai.

Adult↗
PubMed1999

Individually randomized intervention trials for disease prevention and control.

It is argued that randomized, controlled trials should fulfil a critical role in the identification of practical approaches to the prevention and control of chronic diseases. Because of the great public health potential of chemopreventive and behavioural approaches to chronic disease prevention there is need for a major interdisciplinary scientific effort aimed at intervention development. Because of the cost and duration of controlled trials to evaluate specific interventions there is a need for well-conducted feasibility, pilot and intermediate outcome trials, to inform and to justify corresponding full-scale trials having clinical disease outcomes. Compared to therapeutic trials, prevention trials need to have a greater emphasis on overall benefit versus risk assessment. Such trials need to be large enough, and of sufficient duration, to yield powerful tests of key hypotheses, and informative benefit versus risk summary statements. These requirements have a range of implications for intervention trial design, conduct, monitoring and reporting, which are reviewed and discussed. The clinical trial component of the ongoing Women's Health Initiative provides illustration throughout this discussion.

Aged↗
PubMed1998

Nontreatment and aggressive narcotic therapy among hospitalized pancreatic cancer patients.

OBJECTIVES: Strong feelings about patient autonomy as expressed in living wills, polls, and legislative referenda have been challenging the medical establishment to increase nontreatment, defined as foregoing a life-prolonging treatment, and even to provide treatments having life-shortening potential to selected patients. Because there are little data about the actual practice of these procedures, including aggressive narcotic therapy as defined herein, we studied the terminal management of 417 pancreatic cancer patients. DESIGN AND PARTICIPANTS: The medical records of 417 residents of King County, Washington, who died of pancreatic cancer in the time periods 1959-1962, 1969-1972, and 1985-1990, were reviewed to study the frequency of, and risk factors for, end-of-life nontreatment decisions and aggressive narcotic therapy decisions, defined here as the decision to administer treatment doses of narcotics or major sedatives to already comatose patients within 4 hours of death. RESULTS: Antibiotics were not provided to 71% of the 70 febrile patients (two readings >38.33-38.83 degrees C or one reading of 38.88 degrees C), intravenous fluid was not provided to 43% of 294 dehydrated patients (oral intake <500 mL/24 hours), transfusions were not provided to 39% of 57 severely anemic patients (hematocrit <20%), and laparotomy was not performed for 86% of 36 patients with abdominal emergencies (obstruction, bleeding, dehiscence). Also, 46% of the 118 patients who were comatose for at least 24 hours before death received aggressive narcotic therapy, as defined above. A total of 335 of the 417 patients had documentation of at least one of the above life-threatening conditions or were comatose for at least 24 hours before death, and 289 (86%) of these patients experienced nontreatment of one or more of these conditions or received aggressive narcotic therapy. Nontreatment decisions for febrile, dehydrated, or anemic patients tended to be more frequent if the patient was comatose (P=.004, .010, and .065, respectively), if there was a nontreatment statement in the medical record (P=.009, .035, and .001, respectively), or if the patient was described as terminal (P=.262, .029, and .002, respectively). Aggressive narcotic therapy in comatose patients was more common among patients who had regular visitors (P=.002), who had pre-coma pain (P=.006), who had nontreatment statements in their charts (P=.031), whose in-charge physician was an oncologist (P < .001), who were treated in a community nonprofit hospital compared with a Catholic hospital (P=.007), or who were treated in recent years (P=.011). CONCLUSION: Both nontreatment and aggressive narcotic therapy forms of medical management have been occurring commonly in terminal pancreatic cancer patients in King County, Washington, during the past 3 decades, the latter with greater frequency in recent years.

Adult↗
PubMed1998

On the accommodation of disease rate correlations in aggregate data studies of disease risk factors.

Prentice and Sheppard (1995, Biometrika 82, 113-125) proposed a method for estimating relative risks associated with poorly measured exposures using disease rates from multiple populations and exposure and confounding factor data from sample surveys of persons in each population. The method involved an assumption of independence of disease rates across populations, conditional on exposures and confounding factors. Here, this assumption is relaxed by allowing dependencies among the disease rates within a partition of the populations, perhaps defined on the basis of geographic proximity or cultural similarity. Such dependencies could, for example, derive from unmeasured risk factors that are shared among neighboring populations. Dependencies within an element of the partition are modeled by allowing a common correlation between the disease rates of contiguous populations and by inducing correlations between the rates for noncontiguous populations using a multivariate lognormal assumption. Estimating equations are proposed for relative risk parameter estimation, and robustness and efficiency properties are assessed through simulations. The relaxed estimation procedure is shown to yield useful efficiency gains when moderate or strong disease rate dependencies are present, especially when disease rate variances are large relative to binomial variance.

Aged↗
PubMed1997

Population-based family study designs: an interdisciplinary research framework for genetic epidemiology.

Most complex traits such as cancer and coronary heart diseases are attributed either to heritable factors or to environmental factors or to both. Dissecting the genetic and environmental etiology of complex traits thus requires an interdisciplinary research strategy. Genetic studies generally involve families and investigate familial aggregations of traits, segregation of major disease genes, and locations of disease genes on the human genome, the latter of which can be identified via linkage analysis. Epidemiologic studies often use population-based case-control studies to establish the role of specific environmental factors. Integrating both objectives, genetic epidemiology is to assess the associations of environmental factors with disease status, to quantify the aggregation of cases within families, to characterize putative disease genes via segregation analysis, and to localize disease genes via linkage analysis with genetic markers. To accomplish these objectives through designed studies, we propose a class of population-based family study designs, which are formed by choosing among sampling designs at three stages. The objectives of sampling at these three stages are 1) combined aggregation and association analysis, 2) combined segregation, aggregation, and association analysis, and 3) combined linkage, segregation, aggregation, and association analysis. These designs form an interdisciplinary research framework for genetic epidemiology. Our preliminary exploration of this framework and related analytic methods indicates that population-based family study designs retain the efficiency of linkage analysis for localizing disease genes without losing the property of being population-based, and they will therefore allow an assessment of a joint contribution of genetic and environmental factors to complex traits.

Case-Control Studies↗
PubMed1997

Regression estimation using multivariate failure time data and a common baseline hazard function model.

Recent 'marginal' methods for the regression analysis of multivariate failure time data have mostly assumed Cox (1972) model hazard functions in which the members of the cluster have distinct baseline hazard functions. In some important applications, including sibling family studies in genetic epidemiology and group randomized intervention trials, a common baseline hazard assumption is more natural. Here we consider a weighted partial likelihood score equation for the estimation of regression parameters under a common baseline hazard model, and provide corresponding asymptotic distribution theory. An extensive series of simulation studies is used to examine the adequacy of the asymptotic distributional approximations, and especially the efficiency gain due to weighting, as a function of strength of dependency within cluster, and cluster size.

Animals↗
PubMed1997

Regression calibration in failure time regression.

In this paper we study a regression calibration method for failure time regression analysis when data on some covariates are missing or mismeasured. The method estimates the missing data based on the data structure estimated from a validation data set, a random subsample of the study cohort in which covariates are always observed. Ordinary Cox (1972; Journal of the Royal Statistical Society, Series B 34, 187-220) regression is then applied to estimate the regression coefficients, using the observed covariates in the validation data set and the estimated covariates in the nonvalidation data set. The method can be easily implemented. We present the asymptotic theory of the proposed estimator. Finite sample performance is examined and compared with an estimated partial likelihood estimator and other related methods via simulation studies, where the proposed method performs well even though it is technically inconsistent. Finally, we illustrate the method with a mouse leukemia data set.

Animals↗
PubMed1996

Measurement error and results from analytic epidemiology: dietary fat and breast cancer.

BACKGROUND: International correlational analyses have suggested a strong positive association between fat consumption and breast cancer incidence, especially among post-menopausal women. However, case-control studies have been taken to indicate a weaker association, and a recent, pooled cohort analysis reported little evidence of an association. Differences among study results could be due to differences in the populations studied, differences in the control for total energy intake, recall bias in the case-control studies, and dietary measurement error biases. Existing measurement error models assume either that the sample data used to validate dietary self-report instruments are without measurements error or that any such error is independent of both the true dietary exposure and other study subject characteristics. However, growing evidence indicates that total energy and, presumably, both total fat and percent energy from fat are increasingly underreported as percent body fat increases. PURPOSE: A relaxed dietary measurement model is introduced that allows all measurement error parameters to depend on body mass index (weight in kilograms divided by the square of height in meters) and incorporates a random underreporting quantity that applies to each dietary self-report instrument. The model was applied to results from international correlational analyses to determine whether the differing associations between dietary fat and postmenopausal breast cancer can be explained by measurement errors in dietary assessment. METHODS: The relaxed measurement model was developed by use of data on total fat intake and percent energy from fat from 4-day food records (4DFRs) and food-frequency questionnaires (FFQs) from the original Women's Health Trial. This trial was a randomized, controlled, feasibility study of a low-fat dietary intervention carried out from 1985 through 1988 in Cincinnati (OH), Houston (TX), and Seattle (WA) among 303 women (184 intervention and 119 control) who were 45-69 years of age. The relaxed model was used to project results from the international correlational analyses onto 4DFR and FFQ fat-intake categories. RESULTS AND CONCLUSIONS: If measurement errors in dietary assessment are overlooked entirely, the projected relative risks (RRs) for breast cancer based on the international data vary substantially across percentiles of total fat intake. The projected RR for the 90% versus the 10% fat-intake percentile is 3.08 with the 4DFR and 4.00 with the FFQ. If random (i.e., noise) aspects of measurement error are acknowledged, the projected RR for the same comparison is reduced to 1.54 with the 4DFR and 1.42 with the FFQ. If both systematic and noise aspects of measurement error are acknowledged, the projected RR is reduced to about 1.10 with either instrument. Acknowledgment of measurement error also leads to a projected RR of about 1.10 for the 90% versus the 10% percentile of percent energy from fat with either dietary instrument. IMPLICATIONS: Dietary self-report instruments may be inadequate for analytic epidemiologic studies of dietary fat and disease risk because of measurement error biases.

Aged↗
PubMed1995

On the role, design, and analysis of disease prevention trials.

Some differences between prevention and therapeutic trials are reviewed, as are some of David Byar's contributions to the methodology and practice of prevention trials. This leads to a more detailed discussion of three more technical topics pertinent to prevention trials: (i) the role that aggregate data studies may be able to play to complement analytic epidemiologic studies and prevention trials in the identification of disease prevention strategies; (ii) the methods for analysis of correlated response data, as may arise in group randomized trials; and (iii) the importance of emphasizing overall benefits vs. risks in the design and conduct of disease prevention trials.

Biometry↗
PubMed1995

Design issues in cohort studies.

Some basic features of cohort studies are reviewed along with a brief discussion of relative risk estimation procedures. This background, and a discussion of factors influencing cohort study power, provides a context to examine various cohort study design choices, including the choice of study population, the selection of cohort size and follow-up duration, cohort ascertainment and subsampling choices, and decisions concerning validation and reliability substudies. It is noted that confounding issues, and especially issues related to measurement error in the assessment of primary exposure and confounding variables, may have a major influence on the precision and reliability of cohort study analyses. A brief discussion is provided of the role of cohort studies in relation to other observational and experimental research strategies.

Cohort Studies↗
PubMed1995

On the reliability and precision of within- and between- population estimates of relative rate parameters.

Comparisons of individual- and aggregate-level analyses of data from a multigroup observational study are made using an exponential form relative rate model. Stratified, analytic random effects, and aggregate random effects analyses are studied. Estimating equations are developed to give a consistent estimation procedure across analyses and corresponding information matrices are compared. Simulation studies provide insight into the efficiency and bias of relative rate parameter estimates with respect to covariate dispersion, confounding, and covariate measurement error.

Aged↗
PubMed1994

Surrogate and auxiliary endpoints in clinical trials, with potential applications in cancer and AIDS research.

Surrogate endpoints have been defined by Prentice as response variables that can substitute for a 'true' endpoint for the purpose of comparing specific interventions or treatments in a clinical trial. The applicability of this definition, and of related surrogate endpoint criteria, is discussed, with emphasis on cancer and AIDS research settings. Auxiliary endpoints are defined as response variables, or covariates, that can strengthen true endpoint analyses. Specifically, such response variables provide some additional information on true endpoint occurrence times for study subjects having censored values for such times. Auxiliary variables will very frequently be available, and they may be able to be used without making additional strong assumptions. Approaches to the use of auxiliary variables using ideas based on augmented score and augmented likelihood methods are described.

Acquired Immunodeficiency Syndrome↗