Publications by authors named "Etzioni R"

In case-control studies of screening to prevent cancer mortality, exposure is ideally defined as screening that takes place within that period prior to diagnosis during which the cancer is potentially detectable using the screening modality under study. This interval has been called the detectable preclinical period (DPP). Misspecifying the duration of the DPP can bias the results of such studies.

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Accurate estimation of quality of life is critical to cost-effectiveness analysis. Nevertheless, development of sampling algorithms to maximize the accuracy and efficiency of estimated quality of life has received little consideration to date. This paper presents a method to optimize sampling strategies for estimating quality-adjusted life years.

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The intervention protocol for an ovarian cancer screening trial should be efficient as well as effective, because it may become the standard of care if the trial demonstrates mortality reduction. To identify an efficient ovarian cancer screening protocol, the effectiveness and cost-effectiveness of selected single modality and multimodal screening strategies were estimated using a stochastic simulation model. Screening was simulated over a 30-year period in a hypothetical cohort of 1 million women aged 50 at the beginning of the period.

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Estimation of the average total cost for treating patients with a particular disease is often complicated by the fact that the survival times are censored on some study subjects and their subsequent costs are unknown. The naive sample average of the observed costs from all study subjects or from the uncensored cases only can be severely biased, and the standard survival analysis techniques are not applicable. To minimize the bias induced by censoring, we partition the entire time period of interest into a number of small intervals and estimate the average total cost either by the sum of the Kaplan-Meier estimator for the probability of dying in each interval multiplied by the sample mean of the total costs from the observed deaths in that interval or by the sum of the Kaplan-Meier estimator for the probability of being alive at the start of each interval multiplied by an appropriate estimator for the average cost over the interval conditional on surviving to the start of the interval.

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Many chronic diseases, including AIDS and cancer, do not manifest themselves clinically until some time after their inception. In studies of disease natural history, the duration of the asymptomatic period is of interest-in AIDS, to predict the epidemic's course, and in cancer, to develop efficient screening strategies. This article provides a bridge between the two fields with respect to estimation of the asymptomatic period.

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Objectives: This study analyzed methods of prostate cancer early detection in community settings throughout the United States against standards and findings of earlier studies conducted at academic medical centers.

Methods: The study was conducted at 148 clinical centers during Prostate Cancer Awareness Week in September 1993 and continued through June 1994. A total of 31,953 eligible subjects were tested by both digital rectal examination (DRE) and prostate-specific antigen (PSA).

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A review of the past five years finds four efforts to model decisions regarding localized prostate cancer. Sequentially, each model is described and evaluated in terms of its strengths and weaknesses. We found that all models of localized prostate cancer decision making suffer from a number of problems, most notably due to a previously noted lack of unbiased data concerning the natural history of the disease but also due to flaws in the design of the models and the use of available data.

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Background: Our objective was to compare expected survival benefits when screening for prostate cancer with PSA, using an age-specific bound relative to a cutoff of 4.0 ng/ml.

Methods: We used a decision analysis modeling the cancer yield in a cohort screened by both screening tests, and the survival of cancer cases given screen detection and in the absence of screening.

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This article is concerned with the methodological issues that arise when estimating the expected costs attributable to a disease. In particular, the article considers methods appropriate for handling incomplete or censored cost and survival data, incorporating discounting, and computing attributable costs. After motivating the need for an estimate of the average, present value of the attributable costs, we present the Kaplan-Meier sample-average (KMSA) estimator, which takes into account the censored nature of the data that are typically available.

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Background: To reduce breast cancer mortality, ways to promote the use of mammography screening among women age 50 and above are needed. Community organization may be a useful approach.

Methods: The Washington State Community Breast Cancer Screening Project involved implementation of promotional activities initiated by physician and lay community boards in two communities.

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The pharmacokinetics, safety, and efficacy in marrow transplantation of FK506-based immunosuppression for graft-versus-host disease (GVHD) prophylaxis was evaluated in an open label pilot study of 18 patients. Patients more than 12 years of age (median, 35 years; range, 15 to 50 years) with advanced hematologic malignancies receiving HLA-matched sibling marrow grafts were randomized to receive FK506 alone, FK506 and methotrexate (MTX), or FK506 and methyl-prednisolone. Of 17 evaluable patients, all had evidence of sustained marrow engraftment.

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In randomized cancer screening trials, mortality rates for the screened group relative to those of the control group are not likely to be constant as a function of years from randomization due to the inherent lag between initiation of screening and any putative effects of screening on mortality. In this situation, a log rank test for differences in mortality between the randomization groups will not be optimal. Although optimality could potentially be recovered by use of a weighted log rank statistic, the optimal weights are difficult to specify a priori and the potential loss of power by use of poorly specified weights is great.

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In randomized cancer screening trials, the ratio of the mortality rate for the screened group to that for the control group is typically not constant as a function of years from randomization. This is due to an initial lag effect, but also to a dilution effect that results from the accrual of comparable cases in both groups after the end of the screening period. In order to combat the potential loss of power when applying conventional analysis tools, specifically the logrank test, Aron and Prorok (International Journal of Epidemiology 15, 36-43), have advocated analyzing the mortality experience using only the subcohort of cases ascertained within a given time period.

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This article reviews approaches to the design and analysis of cancer screening trials. After summarizing some basic screening concepts and potential pitfalls, we introduce several possible screening trial designs with examples from the literature. We review in detail methods for analyzing screening trial data, including testing for a significant difference in disease-specific mortality between the control and intervention groups, estimating the mortality differential if one exists, and evaluating the programme lead time, the screen sensitivity and the role of stage shifting.

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This article reviews the Bayesian statistical approach to the design and analysis of research studies in the health sciences. The central idea of the Bayesian method is the use of study data to update the state of knowledge about a quantity of interest. In study design, the Bayesian approach explicitly incorporates expressions for the loss resulting from an incorrect decision at the end of the study.

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Marrow transplants from human leukocyte antigen (HLA)-compatible unrelated volunteer donors have become feasible for more than 30% of patients without a family match and have allowed long-term, disease-free survival in 15-65% of patients with a variety of hematological disorders. However, unrelated donor transplants have a higher incidence of graft failure and graft versus host disease (GVHD) than do HLA-matched sibling transplants. This increase may be due to disparities between donor and recipient for undetected HLA determinants or for non-HLA histocompatibility genes.

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We consider monitoring a pilot toxicity study in which the adverse outcome is bivariate and the goal is to terminate the trial if evidence of excessive toxicity is encountered. We develop a Bayesian monitoring rule, based on the posterior probability that the frequency of either adverse outcome exceeds that observed under standard therapy. This rule is intuitive and ethical, and extends in a straightforward fashion from the univariate to the multivariate case.

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Graft rejection has been a problem after marrow grafts for patients with aplastic anemia who were conditioned with cyclophosphamide (CY). Rejection lessened when patients were given the marrow donor's peripheral blood buffy-coat cells in addition to the marrow, but this result was achieved at the price of more chronic graft-versus-host disease (GVHD). Results with second transplants suggested that CY alternating with antithymocyte globulin (ATG) was more immunosuppressive than CY alone.

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The utility of the MLC assay as a test of HLA-D region matching and predictor of acute graft-versus-host disease (GvHD) was evaluated in 157 patients receiving marrow grafts from HLA-A, B identical related haploidentical donors. All donors and recipients were tested by HLA-DR serology, by Dw phenotyping with homozygous typing cells (HTC) and by standard MLC. Ninety-nine of the donor-recipient pairs were mismatched for a serologically defined HLA-DR antigen while 109 pairs were mismatched for the HLA-DR region by HTC typing.

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In the late 1970s statisticians extended the methods for analysing loglinear and logit models for cross-classified categorical data to incorporate information about the ordinal structure of the categories corresponding to some of the classification variables. In this paper we review one class of such extensions known as association models. We consider association models with and without order restrictions on the parameters and we use these models to answer research questions about several medical examples involving ordered categorical data.

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Objective: This study was undertaken to define the incidence and etiology of small bowel obstruction (SBO) after nephrectomy for Wilms' tumor.

Summary Background Data: Intestinal obstruction is one of the most common postoperative complications after nephrectomy for nephroblastoma. However, few reports have evaluated risk factors for SBO.

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We reviewed the charts of 1,910 children enrolled in the Third National Wilms' Tumor Study who underwent primary nephrectomy. Four hundred and ninety-five surgical complications occurred in 379 children (19.8 percent).

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