Statistical properties of randomization in clinical trials

If in a clinical trial prognostic factors are known in advance to be associated with the outcome of a patient it is often recommended that the randomization for a clinical trial should be stratified on these factors, particularly in a multicenter trial. Unfortunately, stratified or covariate-adaptive randomization does not always promote greater balance between the numbers of treatment assignments to A and B within each stratum and thus overall. Because such designs have numerous parameters that must be specified, simulation is a good tool to investigate the impact of these parameters on balance. We investigate and discuss in more detail the difference in balancing performance of three stratified randomization procedures. The permuted-block randomization within strata, the "minimization" method and "self-adjusting" design are assessed overall, within levels of prognostic factors, and within strata. We show the superior performance of "self-adjusting" design and the extent of balancing losses occurring with permuted-block randomization within levels of factors and with "minimization" within strata. A summary of principal conclusions regarding the balancing properties of stratified randomization procedures is presented and general recommendations are offered. The relative merits of each procedure should be weighted carefully in relation to the characteristics of the trial. Considering the likelihood of imbalances, the sample size and values of parameters of stratified randomization procedures (number of prognostic factors, number of factor levels, block size) are important when choosing a randomization procedure.

Can selenium supplementation prevent colorectal cancer?

Randomization ensures that treatment groups do not differ systematically in their characteristics, thereby reducing threats to validity that may otherwise explain differences in outcomes. Large observed imbalances in patient characteristics may indicate that selection bias is being introduced into the treatment allocation process. We introduce classification tree analysis (CTA) as a novel algorithmic approach for identifying potential imbalances in characteristics and their interactions when provisionally assigning each new participant to one or the other treatment group. The participant is then permanently assigned to the treatment group that elicits either no or less imbalance than if assigned to the alternate group. Using data on participant characteristics from a clinical trial, we compare 3 different treatment allocation approaches: permuted block randomization (the original allocation method), minimization, and CTA. Treatment allocation performance is assessed by examining balance of all 17 patient characteristics between study groups for each of the allocation techniques. While all 3 treatment allocation techniques achieved excellent balance on main effect variables, Classification tree analysis further identified imbalances on interactions and in the distributions of some of the continuous variables. Classification tree analysis offers an algorithmic procedure that may be used with any randomization methodology to identify and then minimize linear, nonlinear, and interactive effects that induce covariate imbalance between groups. Investigators should consider using the CTA approach as a real-time complement to randomization for any clinical trial to safeguard the treatment allocation process against bias.

Cancer medicine continues to evolve into a more molecularly based discipline with many new treatments being developed aimed at specific cancer-related pathways and genetic alterations. In order to meet the challenges of the evolving science, new clinical trial designs and approaches for treatment trials are needed to evaluate the promise of these potential therapies. The National Cancer Institute (NCI) with the national NCI Clinical Trials Network (NCTN) Groups will launch two clinical research initiatives in lung cancer in 2014 that demonstrate innovative approaches to the design and conduct of clinical trials. The first initiative is the ALCHEMIST trial (Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial) which is aimed at patients with lung adenocarcinoma that has been entirely removed by surgery. In this study, samples of tumor tissue from thousands of patients will be tested for two specific genetic alterations, one in the EGFR gene, and the other in the ALK gene. These alterations are not common; about 10% of the lung cancer patient population in the US will have tumors with alterations in the EGFR gene and 5% will have alterations in the ALK gene. Rather than conduct a single trial for each alteration, the screening component of the ALCHEMIST trial will screen patients for both alterations at the same time. The ALCHEMIST is connected to 2 specific NCI-supported NCTN Group clinical treatment trials that are each testing a targeted agent specific for one of the alterations in conjunction with adjuvant therapy. Patients found to have tumors containing one of the alterations will be offered enrollment onto the appropriate clinical treatment trial. Every patient in the ALCHEMIST trial, including those without an EGFR or ALK alteration, will also be studied for cancer risk characteristics and their tumor tissue will be analyzed in a research genomics initiative conducted by the NCI Center for Cancer Genomics (CCG). This effort will employ next-generation sequencing technology to capitalize on the foundation of the CCG's earlier effort, the Cancer Genome Atlas. The second initiative, the Advanced Squamous Cell Carcinoma Lung Master Protocol, is a public-private effort made possible through collaboration with stakeholders including the NCI, NCTN Groups, FDA, NIH Foundation, the Friends of Cancer patient advocacy group, and the pharmaceutical industry. By pooling resources to screen tumor samples from about a thousand patients per year with advanced squamous cell carcinoma for multiple genetic alterations, this master protocol will enable several, randomized, phase II clinical trials with promising new agents to take place in parallel within a single study management framework. Agents will be evaluated rapidly and either be further evaluated in a phase III clinical trial or replaced by other new agents for phase II evaluation, without having to develop individual trials de novo each time. Compared with the usual process of developing clinical trials, these two new design approaches will hopefully allow more patients to be enrolled in trials with agents targeted for important molecular characteristics specific for their tumors and the trials will yield clinically useful results more rapidly. Citation Format: Margaret M. Mooney, Jack Welch, Jeffrey S. Abrams. Clinical trial design and master protocols in NCI clinical treatment trials. [abstract]. In: Proceedings of the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; 2014 Jan 6-9; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2014;20(2Suppl):Abstract nr IA08.

Pseudo cluster randomization dealt with selection bias and contamination in clinical trials

Crossover designs have some advantages over standard clinical trial designs and they are often used in trials evaluating the efficacy of treatments for infertility. However, clinical trials of infertility treatments violate a fundamental condition of crossover designs, because women who become pregnant in the first treatment period are not treated in the second period. In previous research, to deal with this problem, some new designs, such as re-randomization designs, and analysis methods including the logistic mixture model and the beta-binomial mixture model were proposed. Although the performance of these designs and methods has previously been evaluated in large-scale clinical trials with sample sizes of more than 1000 per group, the actual sample sizes of infertility treatment trials are usually around 100 per group. The most appropriate design and analysis for these moderate-scale clinical trials are currently unclear. In this study, we conducted simulation studies to determine the appropriate design and analysis method of moderate-scale clinical trials for irreversible endpoints by evaluating the statistical power and bias in the treatment effect estimates. The Mantel-Haenszel method had similar power and bias to the logistic mixture model. The crossover designs had the highest power and the smallest bias. We recommend using a combination of the crossover design and the Mantel-Haenszel method for two-period, two-treatment clinical trials with irreversible endpoints.

Randomization is a key step in reducing selection bias during the treatment allocation phase in randomized clinical trials. The process of randomization follows specific steps, which include generation of the randomization list, allocation concealment, and implementation of randomization. The phenomenon in the dental and orthodontic literature of characterizing treatment allocation as random is frequent; however, often the randomization procedures followed are not appropriate. Randomization methods assign, at random, treatment to the trial arms without foreknowledge of allocation by either the participants or the investigators thus reducing selection bias. Randomization entails generation of random allocation, allocation concealment, and the actual methodology of implementing treatment allocation randomly and unpredictably. Most popular randomization methods include some form of restricted and/or stratified randomization. This article introduces the reasons, which make randomization an integral part of solid clinical trial methodology, and presents the main randomization schemes applicable to clinical trials in orthodontics.

Prospective Clinical Trial Registration: A Prerequisite for Publishing Your Results.

Treating the Black Hypertensive in 2010: Achieve Lower Targets While Awaiting More Definitive Evidence

Now viewed as its own scientific discipline, clinical trial methodology encompasses the methods required for the protection of participants in a clinical trial and the methods necessary to provide a valid inference about the objective of the trial. Drawing from the authors' courses on the subject as well as the first author's more than 30 years wor

Perioperative Cardiac Research Considerations During the Coronavirus Disease 2019 (COVID-19) Pandemic

In recent years, there has been a growing interest in incorporating patients’ perspectives when measuring and interpreting the clinical benefit of cancer therapies. Patient-reported outcomes (PROs) are used in a variety of cancer clinical trials. These studies range from using PROs to better understand the burden of cancer and the adverse effects of cancer therapy (such as pain), to studies that use PROs as the primary end point of the clinical trial, such as reducing symptoms like nausea or fatigue that can be caused by certain cancer therapies. The evolution of PROs in cancer trials has been recently documented by the National Cancer Institute (NCI)–supported Cancer Outcomes Measurement Working Group and by the US Food and Drug Administration’s recent guidance for the use of PROs in product labeling. PRO research also has been recognized as an important element in the NCI strategic planning process. A major NCI goal is to support research that enhances our understanding of the burden of disease among patients with cancer and cancer survivors, and reduces the sequellae of cancer throughout the continuum of care. NCI has taken an important role in developing new ways to measure patient-reported symptoms such as pain and fatigue, and aspects of health-related quality of life across a wide range of cancers and other diseases, through the Patient Reported Outcomes Measurement Information System (PROMIS). As a National Institutes of Health Roadmap initiative, PROMIS will provide clinical research communities with a reliable, valid, and standardized approach to capture these clinically relevant, but subjective and difficult-to-measure outcomes in clinical trials. Standardization of these data will provide additional benefits to the cancer clinical trial enterprise because it will eventually facilitate their incorporation into the cancer bioinformatics grid (ca-BIG), thereby making PROs available to all researchers who participate in and use the grid to support correlative research studies in connection with clinical trials. Through the NCI Clinical Trials Working Group (CTWG), NCI also has undertaken a major reassessment of the design, review, funding, and implementation of cancer clinical treatment trials and symptom management trials. Among the many recommendations contained in the CTWG report are ones to establish a new funding mechanism and prioritization process for supporting correlative science and quality-of-life studies using PROs, that can be initiated in association with clinical trials. As part of the CTWG process, NCI recently created a Symptom Management and Health-Related Quality of Life (SxQOL) Steering Committee to prioritize and review studies that include PROs as primary end points in symptom management clinical trials, and PROs as secondary end points in phase III Cooperative Group cancer treatment trials sponsored by the NCI. In addition, the SxQOL committee will provide guidance on how to improve the utility of PROs in cancer treatment trials and in symptom management trials. Although PRO data have potential utility for a variety of analyses in cancer clinical trials, the issues surrounding their appropriate and effective application are complex. In September 2006, the NCI convened a 2-day conference entitled “PatientReported Outcomes Assessment in Cancer Trials (PROACT): Evaluating and Enhancing the Payoff to Decision-Making.” This conference was cosponsored by the American Cancer Society and represented a collaborative effort among the leadership from all major NCI extramural divisions involved with clinical trials—the Division of Cancer Treatment and Diagnosis, the Division of Cancer Prevention, and the Division of Cancer Control and Population Sciences. The goal of the PROACT conference was to bring together scientists working in this area to inform NCI and the broader cancer research and policy community on how the NCI clinical trial infrastructure is currently organized to support PRO research in clinical trials, and to identify the issues and lessons learned from the experiences of NCI-sponsored cooperative groups and Community Cancer Oncology Programs; other national and international researchers; and US pharmaceutical industry experts in using PROs in phase II and III cancer treatment trials, as well as in symptom management trials. Before the conference, NCI charged a multidisciplinary Scientific Program Committee of internationally recognized experts to identify key determinants of the successful application of PROs in JOURNAL OF CLINICAL ONCOLOGY O V E R V I E W VOLUME 25 NUMBER 32 NOVEMBER 1

BackgroundThere are currently no approved pharmacotherapies for managing methamphetamine dependence. N-acetylcysteine (NAC) has been found to reduce the craving for methamphetamine and other drugs, but its effect on methamphetamine use and other clinically related endpoints are uncertain. The N-ICE trial is evaluating the safety and efficacy of NAC as a take-home pharmacotherapy for methamphetamine dependence.Methods/designThis is a two-arm parallel double-blind placebo-controlled three-site randomised trial (ratio 1:1) using permuted block randomisation, with variable block sizes. It is stratified by site, sex and whether the methamphetamine is injected or not. Participants (N = 180; 60 per site) need to be dependent on methamphetamine, interested in reducing their methamphetamine use and not currently receiving treatment for substance use disorders. The trial is being conducted in outpatient settings in Melbourne, Geelong and Wollongong, Australia. Participants will receive either 2400 mg oral NAC or a matched placebo, delivered as a take-home medication for 12 weeks. Two 600 mg capsules are self-administered in the morning and two more in the evening. Adherence is being monitored using eCAP™ medication bottle lids, which record the date and time of each occasion the bottle is opened. The primary outcome is methamphetamine use during the 12-week trial medication period, measured as (a) days of use, assessed using the timeline followback, and (b) methamphetamine-positive saliva tests, taken weekly. Secondary measures include weekly assessment of methamphetamine craving, severity of methamphetamine dependence, methamphetamine withdrawal symptoms and psychiatric symptoms (depression, suicidality, psychotic symptoms and hostility). Adverse events are monitored at each weekly assessment. Tolerability is assessed using the Treatment Satisfaction Questionnaire for Medication.DiscussionThe N-ICE trial is the first clinical trial to assess whether NAC can reduce methamphetamine use. This trial will improve our understanding of the potential utility of NAC in managing methamphetamine dependence and clinically related outcomes. If found to be effective, take-home NAC could be a potentially scalable and affordable pharmacotherapy option for treating methamphetamine dependence.Trial registrationAustralian and New Zealand Clinical Trials Registry, ACTRN12618000366257. Registered on 29 May 2018.

Radiotherapy and paclitaxel plus pazopanib or placebo in anaplastic thyroid cancer (NRG/RTOG 0912): a randomised, double-blind, placebo-controlled, multicentre, phase 2 trial.

<p indent="0mm">A clinical trial is a key step in the process of pharmaceutical research and development (R &amp; D). It is a key indicator of the innovative potential of the pharmaceutical industry. ClinicalTrials.gov shows that the average annual growth rate of the total number of clinical trials globally in the past decade (2012–2021) was 20.7%, mainly distributed in Europe and the United States, and the total number of clinical trials registered in China accounted for 6% of the world. According to the statistics of IQVIA Institute for Human Data Science, the global proportion of early-stage R &amp; D pipelines from China-headquartered companies increased from 1% in 2005 to 12% in 2020, which was still far behind that of European and American companies. Among 871 new active substances approved for marketing globally in the past two decades, 522 were for marketing in China, with the high number driven by regulatory acceleration mechanisms from National Medical Products Administration, such as breakthrough and orphan designations and priority reviews. Considering the gap in clinical research strength between China and developed countries such as Europe and the United States, the clinical trial research capacity and level should be improved to assist China in the R &amp; D of innovative drugs. According to the Registration and Information Disclosure Platform for Drug Clinical Studies and the clinical trial institution filing management information platform in China, in the last five years (2017–2021), the average annual growth rates of the total number of new drug clinical trial registration and clinical trial units in China reached 26.9% and 12.6%, respectively. However, clinical trial resources are mainly concentrated in major institutions, municipalities, or provincial capital cities in the eastern and central regions of China, with distributions becoming increasingly polarised. Under the background of China’s new medical reforms, the strategic direction of national political support is to motivate equitable access to high-quality clinical trial resources and cross-regional collaborative development of medical institutions by means of medical unions, national clinical medical research centres, Chinese national major projects for new drug innovation and so on. In the context of this background, clinical trial research unions (CTRUs) have been built in China. A CTRU is defined as a consortium formed by medical institutions, sponsors and third-party service institutions of various levels and functions, led by a national clinical medical research centre or clinical trial medical institutions undertaking major national science and technology projects or supporting projects of national key R &amp; D plans, radiating and driving the improvement of clinical trial research capacity in multiple regions. CTRUs develop a multi-level clinical research centre system and collaborative network by vertically and horizontally combining multi-level medical institutions, sponsors and third-party service institutions. All participants of CTRUs are crucial. The leading clinical trial research medical institution, as the core, is responsible for establishing institutional system standards in CTRUs, designing and leading high-quality multi-centre clinical trials, central ethics and personality training. The major clinical trial research medical institutions are responsible for implementing high-quality, multi-centre, complex and high-risk clinical trials. The other member institutions are responsible for implementing basic clinical trials. The sponsors, contract research organizations (CROs), site management organizations (SMOs) and other enterprises are responsible for funding, supporting and promoting the construction of a clinical trial centre system and collaborative network. The specific construction contents of CTRUs include building a clinical trial research resource sharing platform, homogenising clinical trial quality management, constructing a rapid clinical trial process platform, diversified multi-level and multi-form talent training, information interconnection, deepening strategic cooperation and designing and leading high-level trials. CTRUs have established the selection criteria and assessment exit mechanism and conducted work performance assessments from the dimensions of organisation and implementation, division of labour and cooperation, the connection of clinical trial resources from top to bottom, efficiency and benefit and sustainable development to ensure their good and sustainable development. Through CTRUs, we can achieve high-quality clinical trial resource sharing, improve the clinical trial research capability of member institutions, cultivate high-level skills, such as principal investigators (PIs), sub-investigators, institutional managers and clinical research coordinators (CRCs), and promote the development of clinical trials, economically and with high-quality. Through the trial operation with one member of CTRUs, it was found that the key points should be strengthened in deepening resource sharing, implementing central ethics review, interconnecting information platforms and leading high-quality clinical trials. The construction of CTRUs is an effective means for China’s clinical trial research to solve the current problems and change from a ‘follow-on pattern’ to leading high-level and high-quality international multi-centre trials. However, the construction of CTRUs is a complex systematic project. In addition to performing an excellent job in the top-level design and overall planning, CTRUs’ specific implementation process and measures need to be continuously explored in the practice process.