Semiparametric copula-based analysis for treatment effects in the presence of treatment switching.

In controlled trials, "treatment switching" occurs when patients in one treatment group switch to alternative treatments during the trial, and poses challenges to treatment effect evaluation owing to crossover of the treatments groups. In this work, we assume that treatment switching can occur after some disease progression event and view the progression and death events as two semicompeting risks. The proposed model consists of a copula model for the joint distribution of time-to-progression (TTP) and overall survival (OS) up to the earlier of the two events, as well as a conditional hazard model for OS subsequent to progression.

Human papillomavirus infections as a marker to predict overall survival in lung adenocarcinoma.

Human papillomavirus (HPV) has been implicated in multiple cancers, but its significance in lung cancer has remained controversial. As the prevalence of HPV 16/18 infection was higher in lung adenocarcinoma among Taiwanese females, the aim of our study was to evaluate the clinical impact of HPV infections in lung adenocarcinoma. Two hundred and ten patients were enrolled to investigate the associations of HPV status in tumors with clinical characteristics as well as its impact on overall survival.

Assessing dose-region profile of drug efficacy: a multiregional trial strategy.

In this article, we try to address the optimal dosing issue using a multiregional trial. In this trial, in addition to the treatment group using a globally promising dose of study drug, we have another treatment group using a lower dose treatment with which the drug also shows substantial treatment effect in some of the regions, and both treatment groups share the same placebo (control) group. The incorporation of an additional low-dose treatment group in the multiregional trial can provide the following advantages: (i) The multiregional trial can establish the whole treatment effect profile over different regions as well as drug doses; (ii) the multiregional trial allows for sharing drug efficacy information across different regions; and (iii) the use of a common placebo (control) group for the high- and low-dose treatment groups in the multiregional trial results in logistical convenience.

Proposals of statistical consideration to evaluation of results for a specific region in multi-regional trials--Asian perspective.

In recent years, global collaboration has become a conventional strategy for new drug development. To accelerate the development process and to shorten approval time, the design of multi-regional trials incorporates subjects from many countries around the world under the same protocol. After showing the overall efficacy of a drug in all global regions, one can also simultaneously evaluate the possibility of applying the overall trial results to all regions and subsequently support drug registration in each of them.

A Bayesian approach to evaluating regional treatment effect in a multiregional trial.

A multiregional trial, conducted in more than one region under a common protocol, is a promising strategy making valuable medicines available to patients globally without time lag. When evaluating the treatment effect for each local region, one may wish to utilize information from other regions to enhance the statistical power. This work proposes a Bayesian approach to bridging data across different regions in a multiregional trial to get an improved analysis of treatment effect for a local region.

A regulatory view of adaptive trial design.

Developing a new medicine is an expensive and time-consuming process. Researchers are interested in applying better designs to expedite the approval of potential medicinal products. Adaptive designs, which allow for some types of prospectively planned mid-study change, can improve the efficiency of a trial and maximize the chance of success.

The use of weighted Z-tests in medical research.

Traditionally the un-weighted Z-tests, which follow the one-patient-one-vote principle, are standard for comparisons of treatment effects. We discuss two types of weighted Z-tests in this manuscript to incorporate data collected in two (or more) stages or in two (or more) regions. We use the type A weighted Z-test to exemplify the variance spending approach in the first part of this manuscript.

Sample size and optimal designs in stratified comparative trials to establish the equivalence of treatment effects among two ethnic groups.

When a new investigational medicine is intended to be applied to populations with different ethnic backgrounds, a stratified comparative phase III trial using ethnic groups as strata may be conducted to assess the influence of ethnic factors on clinical outcomes of this new medicine. In this paper, based on a binomial model with odds ratio as the measure of the treatment effect, we derive the score test and the associated sample size formula for establishing the equivalence/noninferiority of the treatment effects of a medicine among two ethnic groups. A simplified test together with its sample size formula are also given.