Nonparametric comparison of two survival-time distributions in the presence of dependent censoring

When testing the null hypothesis that treatment arm-specific survival-time distributions are equal, the log-rank test is asymptotically valid when the distribution of time to censoring is conditionally independent of randomized treatment group given survival time. We introduce a test of the null hypothesis for use when the distribution of time to censoring depends on treatment group and survival time. This test does not make any assumptions regarding independence of censoring time and survival time. Asymptotic validity of this test only requires a consistent estimate of the conditional probability that the survival event is observed given both treatment group and that the survival event occurred before the time of analysis. However, by not making unverifiable assumptions about the data-generating mechanism, there exists a set of possible values of corresponding sample-mean estimates of these probabilities that are consistent with the observed data. Over this subset of the unit square, the proposed test can be calculated and a rejection region identified. A decision on the null that considers uncertainty because of censoring that may depend on treatment group and survival time can then be directly made. We also present a generalized log-rank test that enables us to provide conditions under which the ordinary log-rank test is asymptotically valid. This generalized test can also be used for testing the null hypothesis when the distribution of censoring depends on treatment group and survival time. However, use of this test requires semiparametric modeling assumptions. A simulation study and an example using a recent AIDS clinical trial are provided.     

The compliance score as a regressor in randomized trials

The compliance score in randomized trials is a measure of the effect of randomization on treatment received. It is in principle a group-level pretreatment variable and so can be used where individual-level measures of treatment received can produce misleading inferences. The interpretation of models with the compliance score as a regressor of interest depends on the link function. Using the identity link can lead to valid inference about the effects of treatment received even in the presence of nonrandom noncompliance; such inference is more problematic for nonlinear links. We illustrate these points with data from two randomized trials.     

Efficient nonparametric estimation of causal effects in randomized trials with noncompliance

Causal approaches based on the potential outcome framework providea useful tool for addressing noncompliance problems in randomizedtrials. We propose a new estimator of causal treatment effectsin randomized clinical trials with noncompliance. We use theempirical likelihood approach to construct a profile randomsieve likelihood and take into account the mixture structurein outcome distributions, so that our estimator is robust toparametric distribution assumptions and provides substantialfinite-sample efficiency gains over the standard instrumentalvariable estimator. Our estimator is asymptotically equivalentto the standard instrumental variable estimator, and it canbe applied to outcome variables with a continuous, ordinal orbinary scale. We apply our method to data from a randomizedtrial of an intervention to improve the treatment of depressionamong depressed elderly patients in primary care practices.     

No effect of a traditional Chinese medicine, Hochu-ekki-to, on antibody titer after influenza vaccination in man: A randomized, placebo-controlled, double-blind trial

BACKGROUND: It was shown that a traditional Chinese medicine, Hochu-ekki-to (HET), had adjuvant effects in influenza vaccination in an animal experiment. This, however, could not be assessed in a clinical study. METHODS: Thirty-two healthy subjects were randomly assigned to two groups (control and HET groups) in a double-blind manner. HET subjects (n=17) took 7.5 g of HET/day for two weeks; control subjects took the same amount of indistinguishable placebo. Then subjects were vaccinated against influenza (H1N1, H3N2 and B/Shandong). Hemagglutinin titers and natural killer (NK) activity were measured at weeks 0, 1, 2, 4, and 12. RESULTS: Antiinfluenza titers against the three viruses were increased continuously for the first two weeks and leveled off. However, there were no significant differences in any titers between the two groups. NK activity peaked at week 2 without any inter-group differences. CONCLUSION: We could not find any adjuvant effects of HET in this experimental condition.     

ED-71, a new active vitamin D3, increases bone mineral density regardless of serum 25(OH)D levels in osteoporotic subjects

A previous randomized placebo-controlled double-blinded clinical trial revealed that treatment of osteoporotic subjects supplemented with 200 or 400 IU/day vitamin D3 with 0.75 μg/day ED-71 for 12 months increased lumbar and hip bone mineral density (BMD) by 3.4 and 1.5%, respectively, compared to placebo group (JCE&M 90:5031,2005). These effects on BMD were stronger than any previous results using 1(OH)D3 or 1,25(OH)2D3. However, there still was a concern that the effect of ED-71 could be observed because serum 25(OH)D in many of these subjects were below its optimal level. In order to address this issue, we performed post hoc analysis to compare the effect of ED-71 on lumbar and hip BMD between subjects with upper (>29 ng/mL) and lower tertiles (<25 ng/mL) of serum 25(OH)D. Lumbar BMD after 12-month treatment with 0.5, 0.75 and 1.0 μg/day ED-71 increased similarly in both lower and upper tertile groups of serum 25(OH)D. In addition, hip BMD also showed a tendency to increase when 0.75 and 1.0 μg/day ED-71 groups were combined together in both upper and lower serum 25(OH)D tertile groups, although the increase was not statistically significant. These results demonstrate that the effect of ED-71 on bone is independent of supplementary effect for nutritional vitamin D insufficiency, and suggest that ED-71 may exert its effect as a unique VDR ligand with stronger effect on bone compared to the natural ligand, 1,25(OH)2D3.     

Precision Estimation in Zelen's Single-Consent Design

The precision of a treatment contrast, as conventionally estimated in Zelen's Single-Consent Design, is shown under randomization theory to be positively biased. The magnitude of this bias is demonstrated and a new statistic is derived which is a consistent estimator of the precision. Confidence interval estimation for the treatment contrast is also presented.