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Xiaohui Luo

Publications and source records attributed to Xiaohui Luo.

5 recordsLinked to original sources

Multiplicity adjustment for multiple endpoints in clinical trials with multiple doses of an active treatment.

Frequently, multiple doses of an active treatment and multiple endpoints are simultaneously considered in the designs of clinical trials. For these trials, traditional multiplicity adjustment procedures such as Bonferroni, Hochberg and Hommel procedures can be applied when treating the comparisons of different doses to the control on all endpoints at the same level. However, these approaches will not take into account the possible dose-response relationship on each endpoint, and therefore are less specific and may have lower power. To gain power, in this paper, we consider the problem as a two-dimensional multiplicity problem: one dimension concerns the multiple doses and the other dimension concerns the multiple endpoints. We propose procedures which consider the dose order to form the closure of the procedures and control the family-wise type I error rate in a strong sense. For this two-dimensional problem, numerical examples show that procedures proposed in this paper in general have higher power than the commonly used procedures (e.g. the regular Hochberg procedure) especially for comparing the higher dose to the control.

Analgesics↗

The application of enhanced parallel gatekeeping strategies.

The parallel gatekeeping strategy proposed by Dmitrienko et al. (Statist. Med. 2003; 22:2387-2400) provides a flexible framework for the pursuit of strong control on study wise type I error rate. This paper further explores the application of the weighted Simes parallel gatekeeping procedure recommended by Dmitrienko et al. and proposes some modifications to it to better incorporate the interrelationships of different hypotheses in actual clinical trials and to achieve better power performance. We first propose a simple method to quantitatively control the impact of secondary tests on the testing of primary hypotheses. We then introduce a matched gatekeeping procedure to exemplify how to address special relationships between individual primary and secondary tests following the parallel gatekeeping framework. Our simulation study demonstrates that the enhanced gatekeeping procedures generally result in more powerful tests than the parallel gatekeeping procedure in Dmitrienko et al. whenever applicable.

Analgesics↗

Decision rule based multiplicity adjustment strategy.

To minimize potential controversies in determining the need for multiplicity adjustment for multiple hypotheses, we propose a decision rule based multiplicity adjustment strategy in this paper. Resorting to a predefined decision rule of a clinical trial, one may link the different hypotheses by their logical relationships and divide them into different families. A proper multiplicity adjustment procedure can then be developed by maintaining strong control of Type I error rate within each family. The paper applies the proposed multiplicity adjustment strategy to a published raloxifene clinical trial.

Bone Density Conservation Agents↗

Score tests for dose effect in the presence of non-responders.

When only a certain proportion of subjects respond to treatment ('responders') or may never experience an event of interest (thus 'cured'), mixture models often lead to increased understanding of the treatment or disease process. This paper focuses on hypothesis testing in a dose-response framework and shows that increased power is possible by using a mixture model where both the logit of the response rate and the response mean are linear functions of the dose level. Three score tests are developed for testing an overall effect and permutation methods are used to control the type I error. Extensive simulations establish the power properties of the tests and show that our proposed score test has the best performance. The approach is illustrated by a multi-country clinical trial of rapid acting Intramuscular Olanzapine.

Algorithms↗

[A multi-team case-control study on the effects of psychosocial stress to overall health].

OBJECTIVE: To explore the quantitative relationship between the intensity of psychosocial stress and the degree of overall health damages. METHODS: A multi-group case-control study was designed and implemented. The cases included two groups of out-patients (177) and in-patients (214) in a hospital in Jianyang city, and controls (587) were from the follow-up cohort in the same city. Three groups were studied on the following contents: general demographic characteristics, psychosocial factors and the degree of health damages including mental, physical, and social status. Major statistical analyses were as follows: ranks test, ANOVA, cluster analysis, multinomial logistic regression and ordered-logit regression. RESULTS: Ordered-logit regression model showed that the odds ratio of negative life-events on degree of health damages was 1.335 (P < 0.01). This result showed that there was a positive dose-effect relationship between the negative life-events score and overall health damages. The utility of social support to overall health had protective effect (OR = 0.513). CONCLUSION: Negative life-events were the major risk factors to overall health, and there was a dose-effect relationship between negative events and health damages. Function of social support played a protective factor for health.

Analysis of Variance↗