The randomized controlled trial in studies using biomarkers

The randomized controlled trial (RCT) is a scientific experiment during which observations on the effects of therapy or a preventive action are conducted by the researcher under rigorous control. The purpose of the experiment is to clear the uncertainties surrounding a clinical/research issue and involves isolating the 'treatment' and 'end result' variables from external influences. RCTs therefore make use of scientific method standards: measuring, which includes the possibility of reproducing observations; controlling factors unconnected to the cause-effect relationship of interest; and the external verification or 'falsification' of the cause-effect relationship. Many RCTs are now including biomarkers to answer scientific questions in a more accurate way. In the present methodological paper, the main aspects involved in the design and conduction of a trial are discussed, with special emphasis on the use of biomarkers. Aspects that are often overlooked by scientists involved in the design of trials include multiple comparisons, subgroup analysis, the duration of the observations, the use of surrogate endpoints, and ethical issues. This review summarizes the main issues that should be addressed in a protocol, and illustrates these with an example.     

Intervention description is not enough: evidence from an in-depth multiple case study on the untold role and impact of context in randomised controlled trials of seven complex interventions

ABSTRACT: BACKGROUND: A number of single case reports have suggested that the context within which intervention studies take place may challenge the assumptions that underpin RCTs. However, the diverse ways in which context may challenge the central tenets of the RCT, and the degree to which this information is known to researchers and/or subsequently reported, has received much less attention. In this paper we explore these issues by focussing on 7 RCTs of interventions ranging in type and degree of complexity, and across diverse contexts. METHODS: This in-depth multiple case study using interviews, focus groups and documentary analysis was conducted in two phases. In phase one, a RCT of a nurse-led intervention provided a single exploratory case and informed the design, sampling and data collection within the main study. Phase two consisted of a multiple explanatory case study covering a range of trials of different types of complex intervention. A total of 84 data sources across the 7 trials were accessed. RESULTS: We present consistent empirical evidence across all trials to indicate that four key elements of context (personal, organisational, trial and problem context) are crucial to understanding how a complex intervention works and to enable both assessments of internal validity and likely generalizability to other settings. The ways in which context challenged trial operation was often complex, idiosyncratic, and subtle; often falling outside of current trial reporting formats. However, information on such issues appeared to be available via first hand "insider accounts" of each trial suggesting that improved reporting on the role of context is possible. CONCLUSIONS: Sufficient detail about context needs to be understood and reported in RCTs of complex interventions, in order for the transferability of complex interventions to be assessed. Improved reporting formats that require and encourage the clarification of both general and project-specific threats to the likely internal and external validity need to be developed. In addition a cultural change is required in which the open and honest reporting of such issues is seen as an indicator of study strength and researcher integrity, rather than a symbol of a poor quality study or investigator ability.     

Effect of Vitamin D3 Supplementation on Inflammatory Markers and Glycemic Measures among Overweight or Obese Adults: A Systematic Review of Randomized Controlled Trials

BackgroundObesity induced low-grade chronic inflammation disrupts proper immune and metabolic function. Vitamin D deficiency increases inflammation, which is associated with cardiometabolic risk. This systematic review examines the association between oral vitamin D (VD) supplementation and circulating inflammatory biomarkers and glycemic outcomes from randomized controlled trials (RCTs) of overweight and/or obese adults.MethodsMEDLINE OVID, EMBASE and the Cochrane Central Register of Controlled Trials were searched according to a predefined protocol. Eligible RCTs included adults randomized to receive either oral VD or placebo. Two reviewers independently assessed RCTs for inclusion. Bias was assessed using the Cochrane Collaboration risk of bias tool. Mean differences were calculated comparing end-of-study sample means between the independent VD and placebo groups.ResultsEleven unique RCTs met inclusion criteria from a total of 3,383 identified citations, including 79 screened articles and 14 full text data extractions. Inflammatory and glycemic measures were reported in 7 and 10 RCTs, respectively. Most trial findings were non-significant with considerable heterogeneity in design, participants and outcomes. All but one trial was rated as either high or unclear risk of bias. Two RCTs reported significant changes in inflammatory biomarkers; however, the mean difference between groups was not statistically significant: C-reactive protein 0.19 mg/L (p = 0.88); Tumor Necrosis Factor -0.54 pg/ml (p = 0.20). Two other trials found significant mean differences in fasting plasma glucose -0.32 mmol/L (p = 0.03), Hemoglobin A1c -0.13% (p = 0.04), and Homeostatic Model Assessment -0.86 (p = 0.02) following VD supplementation.ConclusionsOverall, there is no clear established benefit of VD supplementation on inflammatory biomarkers among overweight/obese adults. Baseline serum VD possibly influences the effect of VD repletion on inflammatory markers. Risk of bias was present in most studies, thus supporting the need for higher quality studies in this area to more conclusively understand the role VD supplementation has on inflammatory pathways.     

Ethical problems in cytology

Great advances in medical science have raised a number of ethical issues, many of which affect cytopathology. Some of the main issues addressed in this paper relate to the organization of a cytology laboratory: internal and external quality control, adequate staffing levels and staff education, cytopathology reporting format and contents, confidentiality issues, relationship with the clinicians and involvement of cytopathologists in clinical management teams. Quality control has to be provided within cytology departments but external quality assurance is also essential, with national monitoring. New technologies should be used according to the best scientific methods, following cytological analysis. Scientific work in cytology has to respect the general principles of scientific ethics. The patient's interest has to be the main reason for such work.     

Assessment of Field Reentry Exposure to Pesticides: Limitations,Uncertainties, and Alternatives

There are many complex scientific as well as regulatory issues associated with the assessment of field reentry exposure to pesticides. These issues largely come from the limitations and uncertainties inherent in the simplified algorithm that many regulatory agencies use to estimate the reentry exposure. The main objective of this Perspective Article is to bring out these issues systematically in an open forum for further consideration by the exposure assessment community. Accordingly, in this Perspective Article, the simplified algorithm is elaborated first to provide a basic understanding for the complex issues involved. Both the limitations and the uncertainties revolving around this algorithm's real-time application are then discussed extensively, including those specific to monitoring dermal residues in a study trial, measuring dislodgeable foliar residues, and dealing with dislodgeability as well as transferability of foliar residues. The discussion ends by proposing a more practical alternative to the current assessment approach.     

Equipoise,design bias,and randomized controlled trials: the elusive ethics of new drug development

The concept of 'equipoise', or the 'uncertainty principle', has been represented as a central ethical principle, and holds that a subject may be enrolled in a randomized controlled trial (RCT) only if there is true uncertainty about which of the trial arms is most likely to benefit the patient. We sought to estimate the frequency with which equipoise conditions were met in industry-sponsored RCTs in rheumatology, to explore the reasons for any deviations from equipoise, to examine the concept of 'design bias', and to consider alternative ethical formulations that might improve subject safety and autonomy. We studied abstracts accepted for the 2001 American College of Rheumatology meetings that reported RCTs, acknowledged industry sponsorship, and had clinical end-points (n = 45), and examined the proportion of studies that favored the registration or marketing of the sponsor's drug. In every trial (45/45) results were favorable to the sponsor, indicating that results could have been predicted in advance solely by knowledge of sponsorship (P < 0.0001). Equipoise clearly was being systematically violated. Publication bias appeared to be an incomplete explanation for this dramatic result; this bias occurs after a study is completed. Rather, we hypothesize that 'design bias', in which extensive preliminary data are used to design studies with a high likelihood of being positive, is the major cause of the asymmetric results. Design 'bias' occurs before the trial is begun and is inconsistent with the equipoise principle. However, design bias increases scientific efficiency, decreases drug development costs, and limits the number of subjects required, probably reducing aggregate risks to participants. Conceptual and ethical issues were found with the equipoise principle, which encourages performance of negative studies; ignores patient values, patient autonomy, and social benefits; is applied at a conceptually inappropriate decision point (after randomization rather than before); and is in conflict with the Belmont, Nuremberg, and other sets of ethical principles, as well as with US Food and Drug Administration procedures. We propose a principle of 'positive expected outcomes', which informs the assessment that a trial is ethical, together with a restatement of the priority of personal autonomy.     

Mendelian randomization studies on atherosclerotic cardiovascular disease: evidence and limitations

Epidemiological research has revealed a galaxy of biomarkers, such as genes, molecules or traits, which are associated with increased risk of atherosclerotic cardiovascular diseases(ASCVD). However, the etiological basis remains poorly characterized.Mendelian randomization(MR) involves the use of observational genetic data to ascertain the roles of disease-associated risk factors and, in particular, differentiate those reflecting the presence or severity of a disease from those contributing causally to a disease. Over the past decade, MR has evolved into a fruitful approach to clarifying the causal relation of a biomarker with ASCVD and to verifying potential therapeutic targets for ASCVD. In this review, we selected high-quality MR studies on ASCVD, examined the causal relationship of a series of biomarkers with ASCVD, and elucidated the role of MR in validating biomarkers as a therapeutic target by comparing the results from MR studies and randomized clinical trials(RCTs) for the treatment of ASCVD. The good agreement between the results derived by MR and RCTs suggests that MR could be performed as a screening process before novel drug development. However, when designing and interpreting a MR study, the assumptions and limitations inherent in this approach should be taken into account. Novel methodological developments, such as sensitivity analysis, will help to strengthen the validity of MR studies.     

Emission of microvesicles and erythrocytic spherocytation

We have examined mathematically the "cause-effect" relationship between the phenomenon of emission of microvesicles and that of erythrocytic sphericitation, especially when the age of the cell is the main factor involved.     

Using real-world data to predict health outcomes—The prediction design: Application and sample size planning

The gold standard for investigating the efficacy of a new therapy is a (pragmatic) randomized controlled trial (RCT). This approach is costly, time-consuming, and not always practicable. At the same time, huge quantities of available patient-level control condition data in analyzable format of (former) RCTs or real-world data (RWD) are neglected. Therefore, alternative study designs are desirable. The design presented here consists of setting up a prediction model for determining treatment effects under the control condition for future patients. When a new treatment is intended to be tested against a control treatment, a single-arm trial for the new therapy is conducted. The treatment effect is then evaluated by comparing the outcomes of the single-arm trial against the predicted outcomes under the control condition. While there are obvious advantages of this design compared to classical RCTs (increased efficiency, lower cost, alleviating participants’ fear of being on control treatment), there are several sources of bias. Our aim is to investigate whether and how such a design—the prediction design—may be used to provide information on treatment effects by leveraging external data sources. For this purpose, we investigated under what assumptions linear prediction models could be used to predict the counterfactual of patients precisely enough to construct a test and an appropriate sample size formula for evaluating the average treatment effect in the population of a new study. A user-friendly R Shiny application (available at: https://web.imbi.uni-heidelberg.de/PredictionDesignR/ ) facilitates the application of the proposed methods, while a real-world application example illustrates them.     

Microcosm experiments can inform global ecological problems

Global-scale environmental problems are rarely regarded as amenable to traditional scientific experiment. We argue here that small-scale experiments using 'model organisms' in microcosms or mesocosms can be a useful approach for apparently intractable global problems, such as ecosystem responses to climate change or managing biodiversity through the design of nature reserves. An experimental, small-scale research programme can easily be coupled with the development of theory and act as a stimulus to further research, thereby hastening both understanding of the issues and development of practical solutions. This process--from microcosm experiment to the development of practical application--has previously been influential but also has a long time lag. We suggest short-cuts in an attempt to stimulate the use of small-scale experiments to address globally urgent issues with meaningful policy implications.     

Centronuclear (myotubular) myopathy

In recent years, the use of adaptive design methods in clinical research and development based on accrued data has become very popular due to its flexibility and efficiency. Based on adaptations applied, adaptive designs can be classified into three categories: prospective, concurrent (ad hoc), and retrospective adaptive designs. An adaptive design allows modifications made to trial and/or statistical procedures of ongoing clinical trials. However, it is a concern that the actual patient population after the adaptations could deviate from the originally target patient population and consequently the overall type I error (to erroneously claim efficacy for an infective drug) rate may not be controlled. In addition, major adaptations of trial and/or statistical procedures of on-going trials may result in a totally different trial that is unable to address the scientific/medical questions the trial intends to answer. In this article, several commonly considered adaptive designs in clinical trials are reviewed. Impacts of ad hoc adaptations (protocol amendments), challenges in by design (prospective) adaptations, and obstacles of retrospective adaptations are described. Strategies for the use of adaptive design in clinical development of rare diseases are discussed. Some examples concerning the development of Velcade intended for multiple myeloma and non-Hodgkin's lymphoma are given. Practical issues that are commonly encountered when implementing adaptive design methods in clinical trials are also discussed.     

Are Flexible Designs Sound?

Flexible designs allow large modifications of a design during an experiment. In particular, the sample size can be modified in response to interim data or external information. A standard flexible methodology combines such design modifications with a weighted test, which guarantees the type I error level. However, this inference violates basic inference principles. In an example with independent N(mu, 1) observations, the test rejects the null hypothesis of mu < or = 0 while the average of the observations is negative. We conclude that flexible design in its most general form with the corresponding weighted test is not valid. Several possible modifications of the flexible design methodology are discussed with a focus on alternative hypothesis tests.     

Bayesian Two-Stage Biomarker-Based Adaptive Design for Targeted Therapy Development

We propose a Bayesian two-stage biomarker-based adaptive randomization (AR) design for the development of targeted agents. The design has three main goals: (1) to test the treatment efficacy, (2) to identify prognostic and predictive markers for the targeted agents, and (3) to provide better treatment for patients enrolled in the trial. To treat patients better, both stages are guided by the Bayesian AR based on the individual patient’s biomarker profiles. The AR in the first stage is based on a known marker. A Go/No-Go decision can be made in the first stage by testing the overall treatment effects. If a Go decision is made at the end of the first stage, a two-step Bayesian lasso strategy will be implemented to select additional prognostic or predictive biomarkers to refine the AR in the second stage. We use simulations to demonstrate the good operating characteristics of the design, including the control of per-comparison type I and type II errors, high probability in selecting important markers, and treating more patients with more effective treatments. Bayesian adaptive designs allow for continuous learning. The designs are particularly suitable for the development of multiple targeted agents in the quest of personalized medicine. By estimating treatment effects and identifying relevant biomarkers, the information acquired from the interim data can be used to guide the choice of treatment for each individual patient enrolled in the trial in real time to achieve a better outcome. The design is being implemented in the BATTLE-2 trial in lung cancer at the MD Anderson Cancer Center.     

A clinician's guide for conducting randomized trials in individual patients.

In determining optimal treatment for a patient conventional trials of therapy are susceptible to bias. Large-scale randomized trials can provide only a partial guide and have not been or cannot be carried out for most clinical disorders. However, randomized controlled trials (RCTs) in individual patients (N of 1 RCTs) may in some circumstances provide a solution to this dilemma. In an N of 1 RCT a patient undergoes pairs of treatment periods (one period of each pair with the active drug and one with matched placebo, assigned at random); both the patient and the clinician are blind to allocation, and treatment targets are monitored. N of 1 RCTs are useful for chronic, stable conditions for which the proposed treatment, which has a rapid onset of action and ceases to act soon after it is discontinued, has shown promise in an open trial of therapy. The monitoring of treatment targets usually includes quantitative measurement of the patient''s symptoms with the use of simple patient diaries or questionnaires. Pairs of treatment periods are continued until effectiveness is proved or refuted. The cooperation of a pharmacy is required for the preparation of matching placebos and conduct of the trial. Formal statistical analysis may be helpful for interpreting the results. The practical approach presented in this paper allows clinicians to conduct their own N of 1 RCTs.     

Unbiased research and the human spirit: the challenges of randomized controlled trials.

Research by Klein and associates provides useful information on the relation between episiotomy and outcomes such as perineal trauma, but the methodologic implications of their work are especially fascinating. Physicians who participated in their randomized controlled trial (RCT) were supposed to adhere to a policy of either liberal or restrictive use of episiotomy according to the study arm to which each patient was assigned. However, some used the procedure for approximately 90% of patients regardless of allocation. Klein and associates'' post-hoc study (see pages 769 to 779 of this issue) sheds light on the relation between physician attitudes and the practice of episiotomy. The author contends that the noncompliance encountered by Klein and associates reflects the fact that randomized trials are anathema to the human spirit. He offers suggestions for making RCTs more meaningful and stresses that, although RCTs are indispensible to the advancement of medical knowledge, they necessitate assiduous attention to matters of design and implementation.     

The randomized controlled trial: gold standard, or merely standard?

The randomized controlled trial (RCT) is not a gold standard: it is a good experimental design in some circumstances, but that's all. Potential shortcomings in the design and implementation of RCTs are often mentioned in passing, yet most researchers consider that RCTs are always superior to all other types of evidence. This paper examines the limitations of RCTs and shows that some types of evidence commonly supposed to be inferior to all RCTs are actually superior to many. This has important consequences for research methodology, for quality of care in clinical medicine, and--especially--for research funding policy. Because every study design may have problems in particular applications, studies should be evaluated by appropriate criteria, and not primarily according to the simplistic RCT/non-RCT dichotomy promoted by some prominent advocates of the evidence-based medicine movement and by the research evaluation guidelines based on its principles.     

Living with observational data in biological anthropology

The establishment of cause and effect relationships is a fundamental objective of scientific research. Many lines of evidence can be used to make cause–effect inferences. When statistical data are involved, alternative explanations for the statistical relationship need to be ruled out. These include chance (apparent patterns due to random factors), confounding effects (a relationship between two variables because they are each associated with an unmeasured third variable), and sampling bias (effects due to preexisting properties of compared groups). The gold standard for managing these issues is a controlled randomized experiment. In disciplines such as biological anthropology, where controlled experiments are not possible for many research questions, causal inferences are made from observational data. Methods that statisticians recommend for this difficult objective have not been widely adopted in the biological anthropology literature. Issues involved in using statistics to make valid causal inferences from observational data are discussed.     

Treatment Trials for Neonatal Seizures: The Effect of Design on Sample Size

Neonatal seizures are common in the neonatal intensive care unit. Clinicians treat these seizures with several anti-epileptic drugs (AEDs) to reduce seizures in a neonate. Current AEDs exhibit sub-optimal efficacy and several randomized control trials (RCT) of novel AEDs are planned. The aim of this study was to measure the influence of trial design on the required sample size of a RCT. We used seizure time courses from 41 term neonates with hypoxic ischaemic encephalopathy to build seizure treatment trial simulations. We used five outcome measures, three AED protocols, eight treatment delays from seizure onset (T_d) and four levels of trial AED efficacy to simulate different RCTs. We performed power calculations for each RCT design and analysed the resultant sample size. We also assessed the rate of false positives, or placebo effect, in typical uncontrolled studies. We found that the false positive rate ranged from 5 to 85% of patients depending on RCT design. For controlled trials, the choice of outcome measure had the largest effect on sample size with median differences of 30.7 fold (IQR: 13.7–40.0) across a range of AED protocols, T_d and trial AED efficacy (p<0.001). RCTs that compared the trial AED with positive controls required sample sizes with a median fold increase of 3.2 (IQR: 1.9–11.9; p<0.001). Delays in AED administration from seizure onset also increased the required sample size 2.1 fold (IQR: 1.7–2.9; p<0.001). Subgroup analysis showed that RCTs in neonates treated with hypothermia required a median fold increase in sample size of 2.6 (IQR: 2.4–3.0) compared to trials in normothermic neonates (p<0.001). These results show that RCT design has a profound influence on the required sample size. Trials that use a control group, appropriate outcome measure, and control for differences in T_d between groups in analysis will be valid and minimise sample size.     

Biomarkers of oxidative stress and damage in human populations exposed to arsenic

Arsenic (As) is an ubiquitous element in the environment for which the main route of human exposure is through consumption of drinking water. Reactive oxygen species generation (ROS) associated with As exposure is known to play a fundamental role in the induction of adverse health effects and disease (cancer, diabetes, hypertension, and cardiovascular and neurological diseases). However, the precise mechanisms of oxidative stress and damage from As exposure are not fully understood and moreover the use of non-invasive methods of measuring ROS generation and oxidative damage footprints in humans is no easy task. Although As induces adverse health effects not all exposed individuals develop degenerative chronic diseases or even manifest adverse effects or symptoms, suggesting that genetic susceptibility is an important factor involved in the human response to As exposure. This mini-review summarizes the literature describing the molecular mechanisms affected by As, as well as the most used biomarkers of oxidative stress and damage in human populations. The most reported biomarkers of oxidative DNA damage are the urinary excretion of 8-OHdG and the comet assay in lymphocytes, and more recently DNA repair mechanism markers from the base and nuclear excision repair pathways (BER and NER). Genetic heterogeneity in the oxidative stress pathways involved in As metabolism are important causative factors of disease. Thus further refinement of human exposure assessment is needed to reinforce study design to evaluate exposure-response relationships and study gene-environment interactions. The use of microarray-based gene expression analysis can provide better insights of the underlying mechanisms involved in As-induced diseases and could help to identify target genes that can be modulated to prevent disease.     

A pivotal registration phase III, multicenter, randomized tuberculosis controlled trial: design issues and lessons learnt from the Gatifloxacin for TB (OFLOTUB) project

ABSTRACT: BACKGROUND: There have been no major advances in tuberculosis (TB) drug development since the first East African/British Medical Research Council short course chemotherapy trial 35 years ago. Since then, the landscape for conducting TB clinical trials has profoundly changed with the emergence of HIV infection, the spread of resistant TB bacilli strains, recent advances in mycobacteriological capacity, and drug discovery. As a consequence questions have arisen on the most appropriate approach to design and conduct current TB trials. To highlight key issues discussed: Is a superiority, equivalence, or non-inferiority design most appropriate? What should be the primary efficacy outcome? How to consider re-infections in the definition of the outcome? What is the optimal length of patient follow-up? Is blinding appropriate when treatment duration in test arm is shorter? What are the appropriate assumptions for sample size calculation? METHODS: Various drugs are currently in the development pipeline. We are presenting in this paper the design of the most recently completed phase III TB trial, the OFLOTUB project, which is the pivotal trial of a registration portfolio for a gatifloxacin-containing TB regimen. It is a randomized, open-label, multicenter, controlled trial aiming to evaluate the efficacy and safety of a gatifloxacin-containing 4-month regimen (trial registration: ClinicalTrial.gov database: NCT00216385). RESULTS: In the light of the recent scientific and regulatory discussions, we discuss some of the design issues in TB clinical trials and more specifically the reasons that guided our choices, in order to best answer the trial objectives, while at the same time satisfying regulatory authority requirements. CONCLUSION: When shortening TB treatment, we are advocating for a non-inferiority, non-blinded design, with a composite unfavorable endpoint assessed 12 months post treatment completion, and added trial procedures specifically aiming to: (1) minimize endpoint unavailability; and (2) distinguish between relapse and re-infection.