Evaluating temporal trends from occupational lead exposure data reported in the published literature using meta-regression.

OBJECTIVES: The published literature provides useful exposure measurements that can aid retrospective exposure assessment efforts, but the analysis of this data is challenging as it is usually reported as means, ranges, and measures of variability. We used mixed-effects meta-analysis regression models, which are commonly used to summarize health risks from multiple studies, to predict temporal trends of blood and air lead concentrations in multiple US industries from the published data while accounting for within- and between-study variability in exposure. METHODS: We extracted the geometric mean (GM), geometric standard deviation (GSD), and number of measurements from journal articles reporting blood and personal air measurements from US worksites. When not reported, we derived the GM and GSD from other summary measures. Only industries with measurements in ≥2 time points and spanning ≥10 years were included in our analyses. Meta-regression models were developed separately for each industry and sample type. Each model used the log-transformed GM as the dependent variable and calendar year as the independent variable. It also incorporated a random intercept that weighted each study by a combination of the between- and within-study variances. The within-study variances were calculated as the squared log-transformed GSD divided by the number of measurements. Maximum likelihood estimation was used to obtain the regression parameters and between-study variances. RESULTS: The blood measurement models predicted statistically significant declining trends of 2-11% per year in 8 of the 13 industries. The air measurement models predicted a statistically significant declining trend (3% per year) in only one of the seven industries; an increasing trend (7% per year) was also observed for one industry. Of the five industries that met our inclusion criteria for both air and blood, the exposure declines per year tended to be slightly greater based on blood measurements than on air measurements. CONCLUSIONS: Meta-analysis provides a useful tool for synthesizing occupational exposure data to examine exposure trends that can aid future retrospective exposure assessment. Data remained too sparse to account for other exposure predictors, such as job category or sampling strategy, but this limitation may be overcome by using additional data sources.

Power and sample size requirements for non-inferiority in studies comparing two matched proportions where the events are correlated.

Consider clustered matched-pair studies for non-inferiority where clusters are independent but units in a cluster are correlated. An inexpensive new procedure and the expensive standard one are applied to each unit and outcomes are binary responses. Appropriate statistics testing non-inferiority of a new procedure have been developed recently by several investigators. In this note, we investigate power and sample size requirement of the clustered matched pair study for non-inferiority. Power of a test is related primarily to the number of clusters. The effect of a cluster size on power is secondary. The efficiency of a clustered matched-pair design is inversely related to the intra-class correlation coefficient within a cluster. We present an explicit formula for obtaining the number of clusters for given a cluster size and the cluster size for a given number of clusters for a specific power. We also provide alternative sample size calculations when available information regarding parameters are limited. The formulae can be useful in designing a clustered matched-pair study for non-inferiority. An example for determining sample size to establish non-inferiority for a clustered matched-pair study is illustrated.

Efficient interval estimation of a ratio of marginal probabilities in matched-pair data: non-iterative method.

Matched-pair designs have been commonly employed in diagnostic, epidemiologic and laboratory studies. For estimation of a ratio of two marginal probabilities in matched-pair data, a Wald-type logarithmic method is computationally simple, but an actual coverage rate is known to be smaller than a nominal one and a length of the confidence interval is shorter than it should be. The Fieller-type method based on constrained maximum likelihood (CML) estimators possesses asymptotically optimum statistical properties and a coverage rate is close to a nominal one. However, hitherto the limits have been obtained by numerical iterations. In this paper, we derive the efficient confidence limits based on CML as analytical solutions of a quartic equation and present the confidence limits in a closed form.

Non-inferiority tests for clustered matched-pair data.

Non-inferiority tests for matched-pair data where pairs are mutually independent may not be appropriate when pairs are clustered. The tests may require an adjustment to account for the correlation within a cluster. We consider the adjusted score and Wald-type tests, and a modification of Obuchowski's method for non-inferiority and compare them with the non-inferiority test based on a method of moments estimate in terms of Type 1 error rate and power by simulations for a small cluster size under various correlation structures. In general, the score test adjusted by an inflation factor and the modified Obuchowski's method perform as good as the test based on moments estimate in the accuracy of Type 1 error rates. The latter does not provide reasonably close Type 1 error rates to the nominal level when the number of clusters is 25 or smaller and a positive response rate for the standard procedure is 20 per cent or lower. The adjusted score test, the method based on moments estimate and the modified test are comparable in power. The adjusted Wald-type test is too anti-conservative and we should caution use of the test. Since number of clusters is strongly related to the accuracy of empirical Type 1 error rate and power, it is very important to have a sufficiently large number of clusters in designing a clustered matched-pair study for non-inferiority.

Comparison of validity of assessment methods using indices of adjusted agreement.

For comparing the validity of rating methods, the adjusted kappa (S coefficient) and Yule's Y index are better than Cohen's kappa which is affected by marginal probabilities. We consider a validity study in which a subject is assessed as exposed or not-exposed by two competing rating methods and the gold standard. We are interested in one of the methods, which is closer in agreement with the gold standard. We present statistical methods taking correlations into account for comparing the validity of the rating methods using S coefficient and Y index. We show how the S coefficient and Yule's Y index are related to sensitivity and specificity. In comparing the two rating methods, the preference is clear when the inference is the same for both S and Y. If the inference using S differs from that using Y, then it is not obvious how to decide a preference. This may occur when one rating method is better than the other in sensitivity but not in specificity. Numerical examples for comparing asbestos-exposure assessment methods are illustrated.

Assessment on homogeneity tests for kappa statistics under equal prevalence across studies in reliability.

In this paper, we assess the performance of homogeneity tests for two or more kappa statistics when prevalence rates across reliability studies are assumed to be equal. The likelihood score method and the chi-square goodness-of-fit (GOF) test provide type 1 error rates that are satisfactorily close to the nominal level, but a Fleiss-like test is not satisfactory for small or moderate sample sizes. Simulations show that the score test is more powerful than the chi-square GOF test and the approximate sample size required for a specific power of the former is substantially smaller than the latter. In addition, the score test is robust to deviations from the equal prevalence assumption, while the GOF test is highly sensitive and it may give a grossly misleading type 1 error rate when the assumption of equal prevalence is violated. We conclude that the homogeneity score test is the preferred method.

Non-inferiority of new procedure to standard procedure in stratified matched-pair design.

We consider the statistical testing for non-inferiority of a new treatment compared with the standard one under matched-pair setting in a stratified study or in several trials. A non-inferiority test based on the efficient scores and a Mantel-Haenszel (M-H) like procedure with restricted maximum likelihood estimators (RMLEs) of nuisance parameters and their corresponding sample size formulae are presented. We evaluate the above tests and the M-H type Wald test in level and power. The stratified score test is conservative and provides the best power. The M-H like procedure with RMLEs gives an accurate level. However, the Wald test is anti-conservative and we suggest caution when it is used. The unstratified score test is not biased but it is less powerful than the stratified score test when base-line probabilities related to strata are not the same. This investigation shows that the stratified score test possesses optimum statistical properties in testing non-inferiority. A common difference between two proportions across strata is the basic assumption of the stratified tests, we present appropriate tests to validate the assumption and related remarks.

Maternal hormone levels and risk of cryptorchism among populations at high and low risk of testicular germ cell tumors.

Cryptorchism is one of the few well-described risk factors for testicular cancer. It has been suggested that both conditions are related to increased in utero estrogen exposure. The evidence supporting the "estrogen hypothesis" has been inconsistent, however. An alternative hypothesis suggests that higher in utero androgen exposure may protect against the development of cryptorchism and testicular cancer. In order to examine both hypotheses, we studied maternal hormone levels in two populations at diverse risks of testicular cancer; Black Americans (low-risk) and White Americans (high-risk). The study population of 200 mothers of cryptorchid sons and 200 mothers of noncryptorchid sons was nested within the Collaborative Perinatal Project, a cohort study of pregnant women and their children. Third trimester serum levels of estradiol (total, free, bioavailable), estriol, testosterone (total, free, bioavailable), sex hormone-binding globulin, alpha-fetoprotein, and the ratios of estradiols to testosterones were compared between the case and control mothers. The results found no significant differences in the levels of testosterone (total, free, bioavailable), alpha-fetoprotein, sex hormone-binding globulin, or in the ratios of estrogens to androgens. Total estradiol, however, was significantly lower in the cases versus the controls (P = 0.03) among all mothers and, separately, among White mothers (P = 0.05). Similarly, estriol was significantly lower among all cases (P = 0.05) and among White cases (P = 0.05). These results do not support either the estrogen or the androgen hypothesis. Rather, lower estrogens in case mothers may indicate that a placental defect increases the risk of cryptorchism and, possibly, testicular cancer.

Comparison of asbestos exposure assessments by next-of-kin respondents, by an occupational hygienist, and by a job-exposure matrix from the National Occupational Hazard Survey.

BACKGROUND: Assessments of occupational exposures in case-control studies of rapidly fatal illnesses often rely on data from next-of-kin respondents, which may be inaccurate. METHODS: Three methods for assessing exposure to asbestos from case-control data on mesothelioma, including next-of-kin assessment, expert assessment, and use of a generic job-exposure matrix (JEM). Interview data [Spirtas et al. (1994): Occup Environ Med 51:804-811] were reviewed to determine exposure status by an occupational hygienist (C.R.) who was unaware of disease status. Exposure odds ratios were calculated using standard methods, and measures of agreement included the kappa statistic and conditional and marginal odds ratios. RESULTS: Expert assessment detected higher proportions of exposed subjects than the next-of-kin respondents or JEM methods. The disease-exposure odds ratios were highest for respondents, perhaps because of recall bias, and lowest for the JEM method. The agreement was highest between the respondent and expert assessments. A combination of respondent's assessment and JEM assessment led to the best prediction of the expert's assessment. Results for spouse respondents were similar to those for other "next-of-kin" respondents. CONCLUSIONS: Expert assessments were the most plausible, but the data indicate that disease associations could also be detected with the other exposure assessment methods. Using some combination of the proxy respondent's assessment and the JEM assessment, one can predict the expert's assessment. A strategy that relied on the respondent's assessment when it was positive and otherwise obtained an expert assessment could reduce costs with little error, compared to expert assessment on all subjects.

Homogeneity score test for the intraclass version of the kappa statistics and sample-size determination in multiple or stratified studies.

When the intraclass correlation coefficient or the equivalent version of the kappa agreement coefficient have been estimated from several independent studies or from a stratified study, we have the problem of comparing the kappa statistics and combining the information regarding the kappa statistics in a common kappa when the assumption of homogeneity of kappa coefficients holds. In this article, using the likelihood score theory extended to nuisance parameters (Tarone, 1988, Communications in Statistics-Theory and Methods 17(5), 1549-1556) we present an efficient homogeneity test for comparing several independent kappa statistics and, also, give a modified homogeneity score method using a noniterative and consistent estimator as an alternative. We provide the sample size using the modified homogeneity score method and compare it with that using the goodness-of-fit method (GOF) (Donner, Eliasziw, and Klar, 1996, Biometrics 52, 176-183). A simulation study for small and moderate sample sizes showed that the actual level of the homogeneity score test using the maximum likelihood estimators (MLEs) of parameters is satisfactorily close to the nominal and it is smaller than those of the modified homogeneity score and the goodness-of-fit tests. We investigated statistical properties of several noniterative estimators of a common kappa. The estimator (Donner et al., 1996) is essentially efficient and can be used as an alternative to the iterative MLE. An efficient interval estimation of a common kappa using the likelihood score method is presented.

HLA-DR15 (DR2) is overrepresented in myelodysplastic syndrome and aplastic anemia and predicts a response to immunosuppression in myelodysplastic syndrome.

The extent and importance of autoimmune mechanisms in myelodysplastic syndrome (MDS) and the role of immunosuppression in the treatment of this disease are not well defined. We report overrepresentation of HLA-DR2 and its serologic split HLA-DR15 in both MDS and aplastic anemia (AA). Four clinically and ethnically defined patient groups were analyzed. The HLA-DR15 antigen frequencies among North American white MDS patients (n = 72) and AA patients (n = 59), who received immunosuppressive treatment at the National Institutes of Health (NIH), were 36% and 42%, respectively. These antigen frequencies were significantly higher than that of the control population of 240 North American white NIH blood donors typed for HLA antigens by the same molecular technique (HLA-DR15, 21.3%, P =.01 for MDS, P <.001 for AA). Among North American white patients reported in the International Bone Marrow Transplant Registry (IBMTR), 30% of 341 MDS patients and 33% of 364 AA patients were positive for HLA-DR2. These antigen frequencies were higher than those reported for the general North American white population (HLA-DR2, 25.3%, P =.089 for MDS, P =.01 for AA). The DR15 and DR2 frequencies were significantly increased in MDS refractory anemia (RA) (P =.036 and P =.01, respectively) but not MDS refractory anemia with excess blasts. In the NIH MDS patients, HLA-DR15 was significantly associated with a clinically relevant response to antithymocyte globulin (ATG) or cyclosporine immunosuppression (multivariate analysis, P =.008). In MDS with RA, DR15 may be useful as a guide to pathophysiology, prognosis, and treatment.

Analysis of the ratio of marginal probabilities in a matched-pair setting.

Statistical methods for testing and interval estimation of the ratio of marginal probabilities in the matched-pair setting are considered in this paper. We are especially interested in the situation where the null value is not one, as in one-sided equivalence trials. We propose a Fieller-type statistic based on constrained maximum likelihood (CML) estimation of nuisance parameters. For a series of examples, the significance level of the CML test is satisfactorily close to the nominal level, while a Wald-type test is anticonservative for reasonable sample sizes. We present formulae for approximate power and sample size for the CML and Wald tests. The matched design is seen to have a clear advantage over the unmatched design in terms of asymptotic efficiency when the two responses of the pair are highly positively correlated. We recommend the CML method over the Wald method, especially for small or moderate sample sizes.

Human leukocyte antigen class II alleles associated with human T cell lymphotropic virus type I infection and adult T-vell leukemia/lymphoma in a black population

BACKGROUND: Human T-cell lymphotropic virus type I (HTLV-I) is linked to adult T-cell luekemia/lymphoma (ATL) and HTLV-I associated myelopathy (HAM; also known as tropical spastic paraparesis [TSP]), a chronic neurodegenerative disorder. Worldwide, several million HTLV-I carriers are at risk for disease, with an estimated lifetime cumulative risk of 1 percent-5 percent. However, the determinants of disease progression are relatively unknown. We studied human leukocyte antigens (HLA class II) that have been implicated in the pathogenesis of HTLV-I related diseases. METHODS: We analyzed HLA class II alleles among asymptomatic HTLV-I carriers (n = 45), patients with ATL (n = 49) or HAM/TSP (n = 54), and HTLV-I seronegative control subjects (n = 51). All participants were of African descent and were enrolled in epidemiologic studies conducted at the University of the West Indies, Kingston, Jamaica. We used standard microlymphocytotoxicity assays for HLA antigen serotyping and polymerase chain reaction-based methods to examine HLA class II DRB1 and DQB1 alleles. RESULTS: Two antigens determined by serotyping DR15 and DQ1, occurred at significantly increased frequency among HTLV-I carriers compared with seronegative control subjects (42 percent versus 22 percent for DR15 [odds ratio [OR] = 2.7; 95 percent confidence interval [CI] - 1.0-7.2] and 78 percent versus 53 percent for DQ1 [OR = 3.1; 95 percent CI= 1.2-8.5]). Asymptomatic carriers were shown to have and HLA class II allele distribution similar to that of patients with ATL, and the frequencies of the alleles DRB1*1501, DRB1*1101, and DQB1*0602 were significantly increased among patients with ATL compared with patients with HAM/TSP. CONCLUSIONS: These data suggest that host genetic background is an important factor in determining weather HTLV-I carriers develop either ATL or HAM/TSP.(AU)