Biomedical subjects

Shein-Chung Chow

Publications and source records attributed to Shein-Chung Chow.

At least 19 recordsLinked to original sources

PubMed2007

Stability analysis for drugs with multiple active ingredients.

For every drug product on the market, the United States Food and Drug Administration (FDA) requires that an expiration dating period (shelf-life) must be indicated on the immediate container label. For determination of the expiration dating period of a drug product, regulatory requirements and statistical methodology are provided in the FDA and ICH Guidelines. However, this guideline is developed for drug products with a single active ingredient. There are many drug products consisting of multiple active ingredients, especially for most traditional Chinese medicine. In this article, we propose a statistical method for determining the shelf-life of a drug product with multiple active ingredients following similar idea as suggested by the FDA and assuming that these active ingredients are linear combinations of some factors. Stability data observed from a traditional Chinese medicine were analysed to illustrate the proposed method.

Arthritis, Rheumatoid↗

PubMed2007

A note on sample size calculation based on propensity analysis in nonrandomized trials.

In nonrandomized trials, patients are not randomly assigned to treatment groups with equal probability. Instead, the probability of assignment varies from patient to patient depending on patients baseline covariates. This often results in a non-comparable treatment groups due to treatment imbalance. As a result, the United States Food and Drug Administration (FDA) recommended that the method of propensity score analysis be employed to overcome this problem. In this note, a formula for sample size calculation is developed based on a proposed weighted Mantel-Haenszel test on the strata defined by the propensity score analysis. It was shown that the sample size formula derived by Nam (1998) based on the test statistic proposed by Gart (1985) is a special case of the sample size formula derived in this note.

Algorithms↗

PubMed2006

On non-inferiority margin and statistical tests in active control trials.

The problem of selecting a non-inferiority margin and the corresponding statistical test for non-inferiority in active control trials is considered. For selection of non-inferiority margin, the guideline by the International Conference on Harmonization (ICH) recommends that the non-inferiority margin should be chosen in such a way that if the non-inferiority of the test therapy to the active control agent is claimed, the test therapy is not only non-inferior to the active control agent, but also superior to the placebo. Furthermore, variability should be taken into account. Along this line, a method for selecting non-inferiority margins with some statistical justification is proposed. Statistical tests for non-inferiority designed in the situation where the non-inferiority margin is an unknown parameter are derived. An example concerning a cancer trail for testing non-inferiority with the primary study endpoint of the time to disease progression is presented to illustrate the proposed method.

Antineoplastic Agents↗

PubMed2006

Adaptive design in clinical research: issues, opportunities, and recommendations.

The issues and opportunities of adaptive designs are discussed. Starting with the definitions of an adaptive design, its validity and integrity are discussed. The three key components of an adaptive design, i.e., Type I error control, p-value adjustment, and unbiased estimation and confidence interval are addressed. Various seamless designs are investigated. Recommendations are made in the following aspects: study planning, trial monitoring, analysis and reporting, trial simulation, and regulatory perspectives.

Bayes Theorem↗

PubMed2006

On the assessment of dose proportionality: a comparison of two slope approaches.

The problem for assessment of dose proportionality (or linearity) is studied. Various methods for assessment of dose proportionality (or linearity) such as ANOVA type F-test have been proposed. Cheng et al. (2006) proposed an alternative approach based on the slopes of adjacent dose levels under a crossover design. They showed that when dose proportionality (or linearity) cannot be established, their proposed slope approach is useful for evaluation of the degree of departure from dose proportionality (or linearity). In this article, we propose the use of slopes between the dose level and the initial dose (baseline), which we refer to as the baseline slope approach. The two slope approaches are compared under a parallel group design by means of an ANOVA type F-test and other tests. Simulation studies show that the proposed method has a satisfactory small sample performance.

Analysis of Variance↗

PubMed2006

Statistical quality control process for traditional Chinese medicine.

The statistical quality control process on raw materials and/or the final product of traditional Chinese medicine (TCM) is examined. We develop a statistical quality control (QC) method to assess a proposed consistency index of raw materials from different sources and/or final products manufactured at different sites. The idea is to construct a 95% confidence interval for a proposed consistency index under a sampling plan. If the constructed 95% confidence lower limit is greater than a prespecified QC lower limit, then we claim that the raw material or final products have passed the QC and hence can be released for further processing or use; otherwise, the raw materials and/or final product should be rejected. For a given component (the most active component if possible), a sampling plan is derived to ensure that there is a desired probability for establishing consistency between sites when there is truly no difference in raw materials or final products between sites. An example concerning the development of a TCM is presented to illustrate the proposed statistical QC method for assessing consistency in raw materials from two sites.

Algorithms↗

PubMed2005

Statistical inference for cancer trials with treatment switching.

In cancer clinical trials, it is not uncommon that some patients switched their treatments due to lack of efficacy and/or disease progression under ethical consideration. This treatment switch makes it difficult for the evaluation of the efficacy of the treatment under investigation. The current existing methods consider random treatment switch and do not take into consideration of prognosis and/or investigator's assessment that leads to patients' treatment switch. In this paper, we model patients' treatment switching effect in a latent event times model under parametric setting or a latent hazard rate model under the semi-parametric proportional hazard model. Statistical inference procedures under both models are provided. A simulation study is performed to investigate the performance of the proposed methods.

Antineoplastic Agents↗

PubMed2005

Statistical consideration of adaptive methods in clinical development.

In recent years, the use of adaptive methods in clinical development based on accrued data has become very popular due to its flexibility in modifying trial procedures and/or statistical procedures of on-going clinical trials. However, it is a concern that the actual patient population after the modifications could deviate from the originally targeted patient population. Major modifications of trial procedures and/or statistical procedures of on-going trials may result in a totally different trial, which is unable to address the scientific/medical questions that the trial intends to answer.

Algorithms↗

PubMed2005

Inference for clinical trials with some protocol amendments.

The use of adaptive methods in clinical development has become very popular in recent years due to its flexibility in modifying trial procedures and/or statistical procedures of on-going clinical trials. Modifications to trial procedures are usually documented by protocol amendments. However, the actual patient population after protocol amendments could deviate from the originally targeted patient population. In addition, protocol amendments made based on accrued data of the on-going trial may distort the sampling distribution of the statistic designed for the case of no protocol change. In this article, we model the population deviations due to protocol amendments using some covariates and study how to develop a valid statistical inference procedure. An example concerning an asthma trial is presented for illustration.

Algorithms↗

PubMed2005

A hybrid Bayesian adaptive design for dose response trials.

In recent years, the use of adaptive design methods based on accrued data of on-going trials have become very popular for dose response trials in early clinical development due to their flexibility (EMEA, 2002). In this paper, we developed a hybrid frequentist-Bayesian continual reassessment method (CRM) in conjunction with utility-adaptive randomization for clinical trial designs with multiple endpoints. The proposed hyperlogistic function family with multiple parameters gives users flexibility for probability modeling. CRM reassesses a dose-response relationship based on accrued data of the on-going trial, which allows investigators to make decisions based on a constantly updated dose-response model. The proposed utility-adaptive randomization for multiple-endpoint trials allows more patients to be assigned to superior treatment groups. The performance of the proposed method was examined in terms of its operating characteristics through computer simulations.

Algorithms↗

PubMed2005

A Bayesian approach on sample size calculation for comparing means.

In clinical research, parameters required for sample size calculation are usually unknown. A typical approach is to use estimates from some pilot studies as the true parameters in the calculation. This approach, however, does not take into consideration sampling error. Thus, the resulting sample size could be misleading if the sampling error is substantial. As an alternative, we suggest a Bayesian approach with noninformative prior to reflect the uncertainty of the parameters induced by the sampling error. Based on the informative prior and data from pilot samples, the Bayesian estimators based on appropriate loss functions can be obtained. Then, the traditional sample size calculation procedure can be carried out using the Bayesian estimates instead of the frequentist estimates. The results indicate that the sample size obtained using the Bayesian approach differs from the traditional sample size obtained by a constant inflation factor, which is purely determined by the size of the pilot study. An example is given for illustration purposes.

Aged↗

PubMed2004

Analysis of clinical data with breached blindness.

In clinical trials, blinding is usually employed to prevent bias that may be introduced due to the knowledge of the identity of the treatment codes. This bias could alter the conclusion of statistical inference on the treatment effect. The purpose of this article is to propose a method for analysing clinical data with breached blindness. The example regarding the study of the effectiveness of an appetite suppressant in weight loss in obese woman as described in Brownell and Stunkard (Am. J. Psychiatry 1982; 139:1487-1489) is used to illustrate the application of the proposed methods.

Analysis of Variance↗

PubMed2004

Cross-validation for linear model with unequal variances in genomic analysis.

In recent years, genomic studies are usually conducted to identify genes that may have an impact on clinical outcomes. The identified genes are then used to establish a predictive model for identifying subjects who are most likely to respond to the test treatment in clinical trials. This information is useful in early and later phases of clinical development. The United States Food and Drug Administration (FDA) requires that such a predictive model be validated before it can be used in clinical development. Shao [Shao, J. (1993). Linear model selection by cross-validation. J. Amer. Statist. Assoc. 88(422):486-494] proposed a cross-validation method for linear model with equal variances, which is found useful in genomic studies. In practice, however, genomic data may be obtained from different sources with unequal variances. As a result, Shao's method may not be applied directly. In this paper, we extend Shao's method for cross-validation of a linear model with unequal variances. Along this line, two re-sampling methods were proposed to account for the heterogeneity in variance. Several simulations were performed to evaluate the finite samples performances of the proposed methods. An example concerning a breast cancer research is present to illustrate the use of the proposed methods.

Algorithms↗

PubMed2004

Assessing bioequivalence using genomic data.

For approval of a generic drug product, the assessment of bioequivalence in drug absorption is usually considered as a surrogate for evaluation of drug efficacy and safety in clinical studies. For some drug products, the United States Food and Drug Administration indicates that the assessment of similarity between dissolution profiles may be used as a surrogate for assessment of bioequivalence. Along this line, we propose assessing bioequivalence using genomic data collected from the same individuals, assuming that there is an established relationship between pharmacokinetic and genomic data. Because there may be a bias in the prediction of pharmacokinetic data using genomic data and the variations in these two types of data are different, we propose to assess bioequivalence based on sensitivity analysis of prediction bias and variation difference within some predetermined limits. Our methods are derived for average, population, and individual bioequivalence.

Acyclovir↗

PubMed2003

In vitro bioequivalence testing.

A statistical test is proposed for in vitro bioequivalence testing between drug products such as nasal aerosols and nasal sprays. The proposed test generalizes the one recommended in the FDA 1999 guidance to the situation where replicated observations obtained from each sampled canister or bottle of the drug product are available. The technique developed by Hyslop, Hsuan and Holder is used so that the proposed test is asymptotically accurate. The type I error probability and power of the proposed test are investigated through a simulation study. A method for determining the required sample size to achieve a desired power is also proposed. A numerical example is given for illustration.

Administration, Intranasal↗

PubMed2003

Examining outlying subjects and outlying records in bioequivalence trials.

The problem of detecting outliers in bioequivalence trials is considered. We formulate the problem as a hypothesis-testing problem under a mean-shift model and propose a test procedure based on the likelihood function. The test statistic has two components: one is to detect whether a specific pharmacokinetic measurement of a subject for certain formulation/drug product is an outlying value; the other is to test whether a subject as a whole is an outlying subject (with unusual high or low bioavailability for all formulations/drug products). Under normality assumption, the proposed procedure is most powerful. The small sample distribution of the proposed test statistic is derived. A numerical example illustrates the use of the procedure. The proposed test is then compared in a simulation study against the Hotelling T2 test, recommended by Liu and Weng (1991) for the use of outlier detection in bioequivalence studies. The results from the simulation study show that the proposed test is more powerful than the Hotelling T2 test.

Biological Availability↗

PubMed2003

Stability analysis with discrete responses.

We consider the estimation of shelf life of a drug product when the stability data are discrete. When there is no batch-to-batch variation, the proposed shelf life estimator is an approximate 95% lower confidence bound of the true shelf life. In the presence of batch-to-batch variation, the proposed shelf life estimator is an approximate 95% lower prediction bound of the shelf life of future batches. As a result, the proposed shelf life is applicable to all future batches of the same drug product. Testing for batch-to-batch variation based on discrete responses is also discussed.

Confidence Intervals↗

PubMed2003

Sample size determination based on rank tests in clinical trials.

The problem of sample size determination based on three commonly used non-parametric rank based tests, namely, one-sample Wilcoxon's rank sum test, two-sample's Wilcoxon's rank sum test, and the rank-based test for independence is studied. Explicit formulas for variabilities of the test statistics under the alternative hypotheses are derived. Consequently, close forms of power functions of these test statistics are obtained for sample size determination utilizing the concept of higher order polynominal equations. Simulation studies were performed to evaluate the finite samples performance of the derived sample size formulas. The results indicates that the derived methods work well with moderate sample size.

Clinical Trials as Topic↗