Statistical Issues and Recommendations for Clinical Trials Conducted During the COVID-19 Pandemic.

Abstract-The COVID-19 pandemic has had and continues to have major impacts on planned and ongoing clinical trials. Its effects on trial data create multiple potential statistical issues. The scale of impact is unprecedented, but when viewed individually, many of the issues are well defined and feasible to address. A number of strategies and recommendations are put forward to assess and address issues related to estimands, missing data, validity and modifications of statistical analysis methods, need for additional analyses, ability to meet objectives and overall trial interpretability.

Considerations for pediatric trial designs and analyses.

There are challenges in designing pediatric trials arising from special ethical issues and the relatively small accessible patient population. The application of conventional phase 3 trial designs to pediatrics is not realistic in some therapeutic areas. To address this issue, we propose various approaches for designing pediatric trials that incorporate data available from adult studies using James-Stein shrinkage estimation, empirical shrinkage estimation, and Bayesian methods. We also apply the concept of consistency used in multi-regional trials to pediatric trials. The performance of these methods is assessed through representative scenarios and an example using actual Type 2 diabetes mellitus (T2DM) trials.

Example-based illustrations of design, conduct, analysis and result interpretation of multi-regional clinical trials.

Extensive research has been conducted in the Multi-Regional Clinical Trial (MRCT) area. To effectively apply an appropriate approach to a MRCT, we need to synthesize and understand the features of different approaches. In this paper, examples are used to illustrate considerations regarding design, conduct, analysis and interpretation of result of MRCTs. We start with a brief discussion of region definitions and the scenarios where different regions have differing requirements for a MRCT. We then compare different designs and models as well as the corresponding interpretation of the results. We highlight the importance of paying special attention to trial monitoring and conduct to prevent potential issues associated with the final trial results. Besides evaluating the overall treatment effect for the entire MRCT, we also consider other key analyses including quantification of regional treatment effects within a MRCT, and assessment of consistency of these regional treatment effects.

Daunomycin-loaded superparamagnetic iron oxide nanoparticles: Preparation, magnetic targeting, cell cytotoxicity, and protein delivery research.

The clinical use of daunomycin is restricted by dose-dependent toxicity and low specificity against cancer cells. In the present study, modified superparamagnetic iron oxide nanoparticles were employed to load daunomycin and the drug-loaded nanospheres exhibited satisfactory size and smart pH-responsive release. The cellular uptake efficiency, targeted cell accumulation, and cell cytotoxicity experimental results proved that the superparamagnetic iron oxide nanoparticle-loading process brings high drug targeting without decreasing the cytotoxicity of daunomycin. Moreover, a new concern for the evaluation of nanophase drug delivery's effects was considered, with monitoring the interactions between human serum albumin and the drug-loaded nanospheres. Results from the multispectroscopic techniques and molecular modeling calculation elucidate that the drug delivery has detectable deleterious effects on the frame conformation of protein, which may affect its physiological function.

Synthesis, G-quadruplexes DNA binding, and photocytotoxicity of novel cationic expanded porphyrins.

Intensive reports allowed the conclusion that molecules with extended aromatic surfaces always do good jobs in the DNA interactions. Inspired by the previous successful researches, herein, we designed a series of cationic porphyrins with expanded planar substituents, and evaluated their binding behaviors to G-quadruplex DNA using the combination of surface-enhanced raman, circular dichroism, absorption spectroscopy and fluorescence resonance energy transfer melting assays. Asymmetrical tetracationic porphyrin with one phenyl-4-N-methyl-4-pyridyl group and three N-methyl-4-pyridyl groups exhibit the best G4-DNA binding affinities among all the designed compounds, suggesting that the bulk of the substituents should be matched to the width of the grooves they putatively lie in. Theoretical calculations applying the density functional theory have been carried out and explain the binding properties of these porphyrins reasonably. Meanwhile, these porphyrins were proved to be potential photochemotherapeutic agents since they have photocytotoxic activities against both myeloma cell (Ag8.653) and gliomas cell (U251) lines.

Multi-regional clinical trial design and consistency assessment of treatment effects.

We can apply both fixed and random effects models to multi-regional clinical trial (MRCT) design and data analysis. Thoroughly, understanding the features of these models in an MRCT setting will help assessing their applicability to an MRCT. In this paper, we discuss the interpretations of trial results from these models. We also evaluate the impact of the number of regions and the sample size configuration across the regions on the required total sample size for the overall treatment effect assessment. For quantifying treatment effects of individual regions, the empirical shrinkage estimator and the James-Stein type shrinkage estimator associate with smaller variability compared with the regular sample estimator. We conduct computation and simulation to compare the performance of these estimators when they are applied to assess consistency of treatment effects across regions. We use a multinational trial example to illustrate the application of these methods.

New paradigm for drug developments--from emerging market statistical perspective.

Paradigm for new drug development has changed dramatically over the last decade. Even though new technology increases efficiency in many aspects, partially due to much more stringent regulatory requirements, it actually now takes longer and costs more to develop a new drug. To deal with challenge, some initiatives are taken by the pharmaceutical industry. These initiatives include exploring emerging markets, conducting global trials and building research and development centers in emerging markets to curb spending. It is particularly the current trend that major pharmaceutical companies offshore a part of their biostatistical support to China. In this paper, we first discuss the skill set for trial statisticians in the new era. We then elaborate on some of the approaches for acquiring statistical talent and capacity in general, particularly in emerging markets. We also make some recommendations on the use of the PDUFA strategy and collaborations among industry, health authority and academia from emerging market statistical perspective.

Considerations for design and data analysis of noninferiority/superiority cardiovascular trials.

The Food and Drug Administration (FDA) guidance for evaluating cardiovascular (CV) risk in new antidiabetic therapies to treat type 2 diabetes released in December 2008 recommends that sponsors conduct appropriate data analysis to rule out CV safety concerns for drugs treating type 2 diabetes. CV trials of antidiabetic drugs and drugs of other indications for chronic conditions are usually large-scale/long-term trials and can be designed as adaptive noninferiority/superiority trials. In these trials, treatment effect may not manifest immediately after patients take study medication and there will be a dilution in treatment effect after treatment discontinuation. These factors should be taken into account for more precise planning of study sample size and timeline. In this paper, we first derive closed-form formulas for the number of events and total exposure as functions of many other trial parameters. We then outline some considerations for the design of an adaptive noninferiority/superiority CV trial based on ideas of other authors. We also use an example to illustrate the application of the methods.

Empirical shrinkage estimator for consistency assessment of treatment effects in multi-regional clinical trials.

Multi-regional clinical trials have been widely used for efficient global new drug developments. Both a fixed-effect model and a random-effect model can be used for trial design and data analysis of a multi-regional clinical trial. In this paper, we first compare these two models in terms of the required sample size, type I error rate control, and the interpretability of trial results. We then apply the empirical shrinkage estimation approach based on the random-effect model to two criteria of consistency assessment of treatment effects across regions. As demonstrated in our computations, compared with the sample estimator, the shrinkage estimator of the treatment effect of an individual region borrowing information from the other regions is much closer to the estimator of the overall treatment effect, has smaller variability, and therefore provides much higher probability for demonstrating consistency. We use a multinational trial example with time to event endpoint to illustrate the application of the method.

Interim treatment selection with a flexible selection margin in clinical trials.

When several treatment arms are administered along with a control arm in a trial, dropping the non-promising treatments at an early stage helps to save the resources and expedite the trial. In such adaptive designs with treatment selection, a common selection rule is to pick the most promising treatment, for example, the treatment with the numerically highest mean response, at the interim stage. However, with only a single treatment selected for final evaluation, this selection rule is often too inflexible. We modified this interim selection rule by introducing a flexible selection margin to judge the acceptable treatment difference. Another treatment could be selected at the interim stage in addition to the empirically best one if the differences of the observed treatment effect between them do not exceed this margin. We considered the study starting with two treatment arms and a control arm. We developed hypothesis testing procedures to assess the selected treatment(s) by taking into account the interim selection process. Compared with the one-winner selection designs, the modified selection rule makes the design more flexible and practical.

Sample size calculation for thorough QT/QTc study considering various factors related to multiple time points.

The sample size requirement in a thorough QT/QTc study is discussed under a balanced parallel or crossover study design. First, we explore the impacts of various factors on the study power, including the mean effect profile across time and correlation among time points. Then we estimate the variability parameters needed based on multiple historical studies. Different baseline usage is illustrated to have a significant impact on the analysis variability in the parallel studies. Finally, the sample size calculations and recommendations are given for demonstrating a "negative" drug effect and the study assay sensitivity, respectively.

Sample size considerations for Japanese patients in a multi-regional trial based on MHLW guidance.

Since the publication of the International Conference on Harmonization E5 guideline, new drug approvals in Japan based on the bridging strategy have been increasing. To further streamline and expedite new drug development in Japan, the Ministry of Health, Labour and Welfare, the Japanese regulatory authority, recently issued the 'Basic Principles on Global Clinical Trials' guidance to promote Japan's participation in multi-regional trials. The guidance, in a Q&A format, provides two methods as examples for recommending the number of Japanese patients in a multi-regional trial. Method 1 in the guidance is the focus of this paper. We derive formulas for the sample size calculations for normal, binary and survival endpoints. Computations and simulation results are provided to compare different approaches. Trial examples are used to illustrate the applications of the approaches.

A note on ANOVA assumptions and robust analysis for a cross-over study.

Analysis of variance (ANOVA) methods are usually applied to analyse continuous data from cross-over studies. The analysis, however, may not have appropriate type I error when certain assumptions are violated. In this paper, we first clarify a conventionally minimum set of assumptions that validate the F-tests of ANOVA models for cross-over studies. We then provide a practical verification/remedy procedure based upon the theoretical developments. By applying the verification/remedy procedure, more robust analysis results can be expected from the ANOVA models.

A randomized, controlled, clinical trial of etoricoxib in the treatment of rheumatoid arthritis.

OBJECTIVE: To evaluate the efficacy and tolerability of the highly selective cyclooxygenase-2 (COX-2) inhibitor etoricoxib for the treatment of rheumatoid arthritis (RA). METHODS: A double blind, randomized, placebo and active comparator controlled, 12 week study conducted at 88 US sites. Eligible patients were chronic nonsteroidal antiinflammatory drug (NSAID) users with clinical worsening of RA upon withdrawal of prestudy NSAID. Patients received either placebo, etoricoxib 90 mg once daily, or naproxen 500 mg twice daily (2:2:1 allocation ratio). Primary efficacy measures: patient and investigator global assessments of disease activity and direct assessment of arthritis by counts of tender and swollen joints. Key secondary measures: patient global assessment of pain, the Stanford Health Assessment Questionnaire, and the percentage of patients both completing the study and meeting the ACR20 criteria. Tolerability was assessed by tabulation of adverse events and routine laboratory evaluations. RESULTS: In all, 816 patients were randomized (placebo = 323, etoricoxib = 323, naproxen = 170), and 448 completed 12 weeks of treatment (placebo = 122, etoricoxib = 230, naproxen = 96). Compared with patients receiving placebo, patients receiving etoricoxib and naproxen showed significant improvements in all efficacy endpoints (p < 0.01). Compared with patients receiving naproxen, patients receiving etoricoxib demonstrated significant improvements (p < 0.05) on all primary endpoints and most other endpoints including ACR20 criteria. The percentage of patients who achieved an ACR20 response and who completed the study was 21%, 53%, and 39% in the placebo, etoricoxib and naproxen groups, respectively. Etoricoxib and naproxen were both generally well tolerated. CONCLUSION: In this study, etoricoxib 90 mg once daily was more effective than either placebo or naproxen 500 mg twice daily for treating patients with RA over 12 weeks. Etoricoxib 90 mg was generally well tolerated in patients with RA.