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The interpretation of between-group comparisons is facilitated by the creation of treatment groups that are similar to each other in baseline composition. To prevent treatment effects from being confounded with time effects, most trials use restricted randomization to force balance. An unintended consequence of these restrictions is that they create patterns that allow for the prediction of future treatment allocations, and hence selection bias, especially in unmasked trials. In fact, the more restrictive the allocation procedure, the greater the potential for selection bias. It was decided, in the context of a recent clinical trial comparing two dosing schedules of paclitaxel and carboplatin for advanced stage IIIB/IV non-small-cell lung cancer, that the randomized block procedure could not simultaneously protect sufficiently against both selection and chronological bias. In this paper we detail our development of the maximal procedure. The maximal procedure takes as input the extent of chronological bias allowed by the randomized block procedure, then matches it, but does so with fewer restrictions. This feature makes the maximal procedure more resistant to selection bias than the randomized block procedure is., (Published in 2003 by John Wiley & Sons, Ltd.)

Objective: Increasing rates of type 2 diabetes worldwide suggest that diabetes may be caused by environmental toxins. Cadmium is a widespread environmental pollutant that accumulates in the pancreas and exerts diabetogenic effects in animals. To test the hypothesis that exposure to cadmium is associated with impaired fasting glucose and type 2 diabetes, we examined the associations between urinary cadmium and the prevalence of impaired fasting glucose (prediabetes) and diabetes in the Third National Health and Nutrition Examination Survey (NHANES III)., Research Design and Methods: We analyzed data on 8,722 adults > or =40 years of age from the NHANES III (1988-1994), a cross-sectional health survey of a nationally representative sample of the noninstitutionalized civilian U.S. population. We studied urinary levels of cadmium (adjusted for urine creatinine) in relation to the prevalence of impaired fasting glucose and diabetes, using the criteria of the American Diabetes Association., Results: After adjustment for age, ethnicity, sex, and BMI, the odds of impaired fasting glucose and diabetes increased dose-dependently with elevations in urinary cadmium from 0-0.99 to 1.00-1.99 and > or =2 micro g/g creatinine (impaired fasting glucose, odds ratio [OR] 1.48, 95% CI 1.21-1.82 and OR 2.05, 95% CI 1.42-2.95; diabetes, OR 1.24, 95% CI 1.06-1.45 and OR 1.45, 95% CI 1.07-1.97)., Conclusions: In this large cross-sectional study, urinary cadmium levels are significantly and dose-dependently associated with both impaired fasting glucose and diabetes. These findings, which require confirmation in prospective studies, suggest that cadmium may cause prediabetes and diabetes in humans.

We consider several designs from the family of up-and-down rules for the sequential allocation of dose levels to subjects in a dose-response study. We show that an up-and-down design can be improved by using more information than the most recent response. For example, the k-in-a-row rule uses up to the k most recent responses. We introduce a new design, the Narayana rule, which uses a local estimate of the probability of toxicity calculated from all previous responses. For the Narayana rule, as the sample size gets large, the probability of assignment goes to zero for dose levels not among the two (or three) closest to the target. Different estimators of the target dose are compared. We find that the isotonic regression estimator is superior to other estimators for small to moderate sample sizes., (Copyright 2003 John Wiley & Sons, Ltd.)