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Biomedical subjects

W D Flanders

Publications and source records attributed to W D Flanders.

At least 91 records · Page 5Linked to original sources
PubMed1992

The associations of alcohol drinking and drinking cessation to measures of the immune system in middle-aged men.

To estimate the association between the immunologic responses of the cell-mediated and humoral systems and alcohol drinking, we used data from the Vietnam Experience Study conducted by the Centers for Disease Control. That study, conducted from 1985 to 1986, was based on a random sample of 4462 male, Vietnam-era, U.S. veterans. By using linear regression, we evaluated how (1) the number of alcoholic drinks the subjects consumed per month and (2) the drinking cessation of certain subjects were associated with their relative and absolute T, B, CD4, and CD8 lymphocyte counts and immunoglobulin A (IgA), IgM, and IgG levels. We used geometric means and percentage differences in geometric means of immune status to measure the associations and adjusted these values to account for the effect of covariates. The results indicated that measures of immune status differed among the drinking categories and that, generally, the differences changed after adjustment for covariates. These differences consisted, as alcohol consumption increased, of higher IgA and IgM levels, relative T and CD4 lymphocytes, and the ratio of CD4 to CD8 cells, and of lower IgG levels, relative B and CD8 lymphocytes, absolute lymphocyte, and lymphocyte subset counts after adjusting for other covariates. Among former drinkers, we found no clear-cut pattern in measures of immunity for a few years after cessation and then found that values of former drinkers tended to return toward values of nondrinkers as they continued to abstain.

Adult↗
PubMed1991

A meta-analysis of the effect of estrogen replacement therapy on the risk of breast cancer.

To quantify the effect of estrogen replacement therapy on breast cancer risk, we combined dose-response slopes of the relative risk of breast cancer against the duration of estrogen use across 16 studies. Using this summary dose-response slope, we calculated the proportional increase in risk of breast cancer for each year of estrogen use. For women who experienced any type of menopause, risk did not appear to increase until after at least 5 years of estrogen use. After 15 years of estrogen use, we found a 30% increase in the risk of breast cancer (relative risk, 1.3; 95% confidence interval [CI], 1.2 to 1.6). The increase in risk was largely due to results of studies that included premenopausal women or women using estradiol (with or without progestin), studies for which the estimated relative risk was 2.2 (CI, 1.4 to 3.4) after 15 years. Among women with a family history of breast cancer, those who had ever used estrogen replacement had a significantly higher risk (3.4; CI, 2.0 to 6.0) than those who had not (1.5; CI, 1.2 to 1.7).

Adult↗
PubMed1991

Commentary: the affected sib-pair method in the context of an epidemiologic study design.

The purpose of this commentary is to provide a framework for using the well-known sib-pair methodology in the context of epidemiologic study designs. Using examples from the Pittsburgh family studies of insulin-dependent diabetes mellitus, we illustrate that the sib-pair method can be used in family-based epidemiologic studies. In a cohort study, unaffected relatives of probands ascertained from well-defined populations are followed for disease development. Disease risks are then stratified according to the number of alleles at one or more loci (0, 1, 2) that are identical by descent (ibd) with the proband. In the absence of linkage between the marker locus and the disease locus, disease risks are expected to be identical in the three groups. Measures of relative risk can be computed (with share-0 as baseline group). In a case-control study, relatives of probands that become affected (cases) are compared to a sample of relatives of probands that stay unaffected (controls) with respect to the number of alleles ibd with the proband. Measures of odds ratio can be computed (with share-0 as baseline group). In both cohort and case-control approaches, covariates including other genetic markers and environmental exposures can be evaluated in relation to disease risk and also for evidence of interaction with the specific marker of interest using stratified and multivariate analyses. Family-based epidemiologic studies allow investigators to study, in a single design, the role of environmental factors and specific gene loci in the etiology of diseases.

Alleles↗
PubMed1991

Extensions to methods of sib-pair linkage analyses.

Sib-pair methods provide simple, robust, easily implemented ways to screen for linkage between a marker locus and a suspected disease susceptibility locus. The basic analysis reflects the idea that, in the presence of linkage, siblings who share more alleles at the marker locus should also tend to be concordant for disease. Available sib-pair methods do not lead directly to estimates of risk associated with nongenetic factors, may not account for a variable age-at-onset, or may require that the age-at-onset distribution be known. In this paper, we propose a method for sib-pair linkage analyses that allows for a variable age-at-onset using a logistic model, easily allows modelling of nongenetic factors, reflects the correlation of sibs within a sibship, and allows for nonzero risk in those without the susceptibility genotype. Based on a limited number of simulations, the method has as good or better power than another recently described method that also allows for a variable age-at-onset.

Epidemiologic Methods↗
PubMed1991

Analytic methods for two-stage case-control studies and other stratified designs.

Nested case-control studies, or case-control studies within a cohort, combine the advantages of cohort studies with the efficiency of case-control studies. Case-control studies can often be viewed as having two stages; the first stage consists of vital status, disease, and basic covariate ascertainment, and the second stage consists of detailed covariate and exposure ascertainment. Breslow and Cain (1988) and Breslow and Zhao (1988) recently showed that conventional analyses of such two-stage studies may ignore some of the available information. In this paper, we show how one can adapt the pseudo-likelihood analyses developed by Kalbfleisch and Lawless (1988) to the analysis of data from two-stage case-control studies.

Case-Control Studies↗
PubMed1991

The associations of race, cigarette smoking, and smoking cessation to measures of the immune system in middle-aged men.

To estimate the association between the immunologic responses of the cell-mediated and humoral systems and race or tobacco smoking, we used data from the Vietnam Experience Study conducted by the Centers for Disease Control. That study, done from 1985 to 1986, was based on a random sample of 4462 male, Vietnam-era, U.S. veterans. Racial groups were white, black, Hispanic, Asian, and American Indian. We used linear regression to evaluate how (i) the race of the subjects, (ii) the number of pack-years of cigarettes the subjects smoked, and (iii) the smoking cessation of certain subjects were associated with their relative and absolute T, B, CD4, and CD8 lymphocyte counts and immunoglobulin A (IgA), IgM, and IgG levels. The results indicated that immune status was associated with race and smoking history and that, generally, the associations remained after adjustment for covariates. For example, the average IgA level and absolute CD8 lymphocyte count for blacks were, respectively, 19 and 16% higher than those for whites. On the other hand, smokers had lower immunoglobulin levels and relative CD8 cell counts and higher counts for other lymphocytes of the cell-mediated system than nonsmokers. For example, the average absolute B count of heavy smokers was 37% higher than that of nonsmokers. The pattern after cigarette smoking cessation was consistent with a reversible effect of smoking and a return toward immune levels of nonsmokers.

Adult↗
PubMed1991

Does increased detection account for the rising incidence of breast cancer?

BACKGROUND: The incidence of breast cancer has been increasing over time in the United States. METHODS: To determine the role of screening in this increase, trends in the incidence of in situ and invasive carcinoma of the breast were evaluated using records of the metropolitan Atlanta SEER program between 1979 and 1986. From a sample of records, evidence of symptoms and mammographic screening prior to diagnosis was recorded. RESULTS: The average annual age-adjusted incidence of invasive disease rose 29 percent among Whites and 41 percent among Blacks. Incidence increased in all age groups. A trend towards earlier detection of invasive disease was found. Asymptomatic tumors accounted for only 40 percent of the increased incidence among whites and 25 percent of the increased incidence among blacks, with mammography as the principal contributing procedure. CONCLUSIONS: These data suggest that increased detection accounts for some but not all of the rising incidence of breast cancer in the United States.

Adult↗
PubMed1991

Use of the Mantel-Haenszel chi 2 overestimates precision in studies with sparse data.

Probability values or "test-based" confidence limits computed on the basis of the Mantel-Haenszel chi 2 statistic may be invalid if minimum cell-size requirements are not met. In 30 studies of occupational proportionate mortality published from 1985 through 1987, the Mantel-Haenszel chi 2 was used in potential violation of cell-size requirements in 21 studies. Sixteen (76%) studies included at least one value that, when compared with testing with the Poisson distribution, was erroneously reported as statistically significant at the 0.05 level. We conclude that by using the Mantel-Haenszel chi 2 with sparse data, some epidemiologists overestimate precision.

Bias↗
PubMed1990

Estimation of risk ratios in case-base studies with competing risks.

The case-base study is a recently developed modification of the case-control design that leads to risk ratio estimates. Currently available methods for the analysis of case-base studies lead to estimates of the unconditional risk ratio which may be misleading of censoring occurs. In this manuscript, we describe an approach for the analysis of case-base studies that yields conditional risk ratio estimates which remain valid in the presence of censoring. The approach we propose for estimating risk ratios and their standard errors involves a non-iterative procedure.

Case-Control Studies↗
PubMed1990

Estimating benefits of screening from observational cohort studies.

Analysis and interpretation of observational studies of screening effectiveness is difficult because several biases threaten validity, including the structural healthy screenee bias, length bias, and effects of lead time. Although methods for the analysis of observational studies of screening effectiveness have been proposed, most have limitations such as incomplete control of length bias, or a heavy reliance on distributional assumptions. In this report we present a method for the analysis of observational cohort studies of screening effectiveness. Although developed independently and formulated specifically for estimating benefits of screening, our approach is implied by a more general approach developed previously by Robins. Our approach, in contrast to other available methods, avoids the healthy screenee bias, and length and lead time bias, and allows an empirical approach to analysis that need not depend highly on distributional assumptions. We illustrate application of the approach with analysis of published data from a study of breast cancer screening.

Bias↗
PubMed1990

Limitations of the case-exposure study.

The case-exposure study, described in 1983, is a modification of the case-control study that allows estimation of risk ratios without need for a rare-disease assumption. For a fixed population the approach is the same as the case-base or case-cohort study. Two sampling strategies have been described for extending application of the case-exposure approach to stationary populations, although the validity of the extension was not proven. As shown here, the two sampling strategies for stationary populations can provide valid estimates of the risk ratio, but restrictive assumptions related to stationarity may limit application of the strategy. We also show that the case-exposure study depends on the stationarity assumptions in a different, possibly more restrictive way than some other case-control approaches. We emphasize limitations of the case-exposure study that may preclude its use, particularly if the period of risk is long.

Case-Control Studies↗
PubMed1990

Illustration of the effects of genotype misclassification on the measurement of familial aggregation in epidemiologic studies.

Exposure misclassification is a well-known problem in epidemiologic studies and can considerably dilute relative risk (RR) measures toward unity. A vivid illustration of such misclassification occurs in familial aggregation studies, where "exposure" is defined as a specified genetic relationship to an affected individual (case) or to an unaffected individual (control). Even in the simplest single-gene model, only a fraction of relatives of cases have the disease genotype. Also, if the trait is not fully penetrant, a proportion of relatives of controls can have the genotype. Thus the familial RR measures are subject to misclassification bias if they are interpreted as the relative effect of a susceptible genotype. The effects of this form of "exposure" (or more properly genotype) misclassification on familial RR measures were quantified and applied empirically to known disease-genetic trait associations. Expected RRs in first-, second-, and third-degree relatives were generated and plotted for different genotype RRs, disease, and allele frequencies. In general, familial RRs are substantially lower than genotypic RRs. Even in the case of strong associations such as HLA-B27 and ankylosing spondylitis (RR = 100), RR measures in first-, second-, and third-degree relatives are only 6.0, 3.5, and 2.2, respectively. Such strong misclassification effects may result in considerable reduction of statistical power in family studies. It is suggested that etiologic studies of disease explore directly the role of measurable genetic traits in epidemiologic studies in populations as well as in families.

Classification↗
PubMed1990

Indirect assessment of confounding: graphic description and limits on effect of adjusting for covariates.

Confounding is recognized as a mixing of effects that can lead to spurious conclusions about the association between disease and a putative risk factor. Confounding occurs if an extraneous factor causes disease and is associated with the exposure of interest. Since information on potential confounders may be missing, the investigator may assess confounding indirectly by specifying values for three types of parameters: the prevalence of the covariate in the population, the association between exposure and the covariate, and the effect of the covariate on disease. Qualitative and quantitative arguments suggest that adjustment for a potential confounder may have small effects on the risk ratio, even if the confounder is a strong risk factor. In this report we illustrate graphically the effect that adjustment for a confounder will have on the risk ratio and derive limits for the magnitude of that effect. Our approach allows the investigator to calculate limits for the maximum effect of covariate adjustment, even if only one or two of the relevant parameters can be specified.

Confounding Factors, Epidemiologic↗
PubMed1989

Are racial differences in the prevalence of diabetes in adults explained by differences in obesity?

To determine whether the higher prevalence of diabetes found among blacks in the United States is explained by racial differences in obesity, we examined the prevalence of diabetes adjusted for adiposity, education, and income in a cohort of US Army veterans from the Vietnam era. Among 12,558 white men and 1677 black men, aged 30 to 47 years, blacks were more likely than whites to have diagnosed diabetes (adjusted prevalence ratio, 1.9; 95% confidence interval, 1.3 to 2.7). Within every age, adiposity, and socioeconomic stratum, blacks had a higher prevalence of diagnosed diabetes than whites. In a subgroup of veterans for whom fasting serum glucose values were measured, blacks were more likely than whites to have fasting hyperglycemia (fasting serum glucose value greater than or equal to 7.8 mmol/L) (adjusted prevalence ratio, 5.7; 95% confidence interval, 2.7 to 12.0). These data provide evidence that the higher prevalence of diabetes found among blacks is not explained by differences in obesity.

Adult↗
PubMed1989

On the measurement of susceptibility to genetic factors.

Geneticists usually measure the phenotypic effects of a single gene trait in terms of penetrance and recurrence risks in relatives of affected individuals, while epidemiologists usually compute measures of relative and attributable risks. These concepts can be merged to measure the proportion of individuals "susceptible" to a genetic factor. In the context of a sufficient cause model, susceptibility can be defined as the underlying factor(s) sufficient to make a person develop disease because of the genetic factor in the absence of other causes. The proportion of susceptibles to the genetic factor in the population differs conceptually and often arithmetically from the penetrance of the genotype especially for common diseases with etiologic heterogeneity. For a wide range of disease and allele frequencies, it can be shown that the proportion of susceptibles can be approximated by the risk difference measure (i.e., difference between penetrance with the genotype and penetrance without the genotype). We also apply the concept of susceptibility to estimate familial recurrence of disease due to a genetic factor. This measure of familial recurrence differs conceptually from simple recurrence risk and can be approximated by the familial risk difference measure (i.e., difference between recurrence risks in relatives of cases and relatives of controls) for a wide range of disease and allele frequencies.

Environmental Exposure↗
PubMed1989

Bias associated with differential hospitalization rates in incident case-control studies.

Berkson's bias reflects a statistical phenomenon in which differential hospitalization rates create an exposure distribution among hospitalized cases that differs from that among other cases. Importantly, previous work on Berkson's bias has not explicitly addressed the possibility of excluding prevalent or previously diagnosed cases--exclusions that are key features of many study designs. We indicate that the classically described bias differs from the corresponding bias in studies, such as incidence density studies, in which cases are restricted to those with recent diagnoses. We present methods that may be used to assess the magnitude of Berkson's bias in incidence-density studies. In many, though not all, situations the bias should be small and of little practical concern.

Epidemiologic Methods↗
PubMed1989

Bias arising in case-control studies from selection of controls from overlapping groups.

Three examples are used to demonstrate that the selection of controls from categories that overlap can lead to bias. Case-control studies that use friend controls and the practice of age-matching controls to cases within a specified number of years (caliper matching) are examples of the selection bias described in the paper. The bias resulting from the use of friend controls can be large and, since the use of friend controls is common, this source of bias is of considerable practical consequence. The use of friend controls or the selection of controls according to other variables with categories that overlap should be avoided.

Age Factors↗