Overhauling clinical trials

A Vector Theory of Assessing Clinical Trials: An Application to Bioequivalence

A novel idea is introduced regarding the statistical comparisons of endpoints in clinical trials. Currently, the (dis)similarity of measured endpoints is not assessed. Instead, statistical analysis is directly applied, which can lead to multiplicity issues, reduced statistical power, and the recruitment of more subjects. The Vector-Based Comparison (VBC) approach originates from vector algebra and considers clinical endpoints as "vectors". In the general case of N clinical endpoints, a Cartesian coordinate system is defined, and the most important primary endpoint (E1) is set. Following an explicitly defined procedure, the pairwise relationships of the remaining N-1 endpoints with E1 are estimated, and the N-1 endpoints are decomposed into axes perpendicular to E1. The angle between vectors provides insight into the level of dependency between variables. Vectors that are perpendicular to each other are considered independent, and only these are used in the statistical analysis. In this work, VBC is applied to bioequivalence studies of three anti-hypertensive drugs: amlodipine, irbesartan, and hydrochlorothiazide. The results suggest that VBC is a reproducible, easily applicable method allowing for the discrimination and utilization of the endpoint component expressing different attributes. All clinical characteristics are assessed with increased statistical power, without inflation of type I error.

Randomized Controlled Trials 1: Design

Today's clinical practice relies on the application of well-designed clinical research, the gold standard test of an intervention being the randomized controlled trial. Principles of the randomized control trial include emphasis on the principal research question, randomization, blinding; definitions of outcome measures, of inclusion and exclusion criteria, and of co-morbid and confounding factors; enrolling an adequate sample size; planning data management and analysis; preventing challenges to trial integrity such as drop-out, drop-in, and bias. The application of pre-trial planning is stressed to ensure the proper application of epidemiological principles resulting in clinical studies that are feasible and generalizable. In addition, funding strategies and trial team composition are discussed.

Empowering phase II clinical trials to reduce phase III failures

The large number of failures in phase III clinical trials, which occur at a rate of approximately 45%, is studied herein relative to possible countermeasures. First, the phenomenon of failures is numerically described. Second, the main reasons for failures are reported, together with some generic improvements suggested in the related literature. This study shows how statistics explain, but do not justify, the high failure rate observed. The rate of failures due to a lack of efficacy that are not expected, is considered to be at least 10%. Expanding phase II is the simplest and most intuitive way to reduce phase III failures since it can reduce phase III false negative findings and launches of phase III trials when the treatment is positive but suboptimal. Moreover, phase II enlargement is discussed using an economic profile. As resources for research are often limited, enlarging phase II should be evaluated on a case-by-case basis. Alternative strategies, such as biomarker-based enrichments and adaptive designs, may aid in reducing failures. However, these strategies also have very low application rates with little likelihood of rapid growth.

Modern clinical research: How rapid learning health care and cohort multiple randomised clinical trials complement traditional evidence based medicine

BACKGROUND

Trials are vital in informing routine clinical care; however, current designs have major deficiencies. An overview of the various challenges that face modern clinical research and the methods that can be exploited to solve these challenges, in the context of personalised cancer treatment in the 21st century is provided.

AIM

The purpose of this manuscript, without intending to be comprehensive, is to spark thought whilst presenting and discussing two important and complementary alternatives to traditional evidence-based medicine, specifically rapid learning health care and cohort multiple randomised controlled trial design. Rapid learning health care is an approach that proposes to extract and apply knowledge from routine clinical care data rather than exclusively depending on clinical trial evidence, (please watch the animation: http://youtu.be/ZDJFOxpwqEA). The cohort multiple randomised controlled trial design is a pragmatic method which has been proposed to help overcome the weaknesses of conventional randomised trials, taking advantage of the standardised follow-up approaches more and more used in routine patient care. This approach is particularly useful when the new intervention is a priori attractive for the patient (i.e. proton therapy, patient decision aids or expensive medications), when the outcomes are easily collected, and when there is no need of a placebo arm.

DISCUSSION

Truly personalised cancer treatment is the goal in modern radiotherapy. However, personalised cancer treatment is also an immense challenge. The vast variety of both cancer patients and treatment options makes it extremely difficult to determine which decisions are optimal for the individual patient. Nevertheless, rapid learning health care and cohort multiple randomised controlled trial design are two approaches (among others) that can help meet this challenge.

Randomized controlled trials 1: Design

Today's clinical practice relies on the application of well-designed clinical research, the gold standard test of an intervention being the randomized controlled trial. Principles of the randomized control trial include emphasis on the principal research question, randomization, blinding; definitions of outcome measures, of inclusion and exclusion criteria, and of comorbid and confounding factors; enrolling an adequate sample size; planning data management and analysis; preventing challenges to trial integrity such as drop-out, drop-in, and bias. The application of pretrial planning is stressed to ensure the proper application of epidemiological principles resulting in clinical studies that are feasible and generalizable. In addition, funding strategies and trial team composition are discussed.

Response-adaptive decision-theoretic trial design: operating characteristics and ethics

Adaptive randomization is used in clinical trials to increase statistical efficiency. In addition, some clinicians and researchers believe that using adaptive randomization leads necessarily to more ethical treatment of subjects in a trial. We develop Bayesian, decision-theoretic, clinical trial designs with response-adaptive randomization and a primary goal of estimating treatment effect and then contrast these designs with designs that also include in their loss function a cost for poor subject outcome. When the loss function did not incorporate a cost for poor subject outcome, the gains in efficiency from response-adaptive randomization were accompanied by ethically concerning subject allocations. Conversely, including a cost for poor subject outcome demonstrated a more acceptable balance between the competing needs in the trial. A subsequent, parallel set of trials designed to control explicitly types I and II error rates showed that much of the improvement achieved through modification of the loss function was essentially negated. Therefore, gains in efficiency from the use of a decision-theoretic, response-adaptive design using adaptive randomization may only be assumed to apply to those goals that are explicitly included in the loss function. Trial goals, including ethical ones, which do not appear in the loss function, are ignored and may even be compromised; it is thus inappropriate to assume that all adaptive trials are necessarily more ethical. Controlling types I and II error rates largely negates the benefit of including competing needs in favor of the goal of parameter estimation.

Effectiveness of adaptive designs for phase II cancer trials

BACKGROUND

Evaluation of new therapies for cancer has suffered a paradigm shift in the last years. The use of innovative and more efficient designs is a priority for the scientific community; nevertheless, the use of this kind of design is not yet wide spread.

PURPOSE

In this paper will examine the effectiveness of adaptive designs compared with traditional designs in phase II clinical trials.

METHODS

We reviewed a group of abstracts records between 1980 and 2008 and extracted data regarding statistical design, year of publication, kind of evaluated product, localization, sample size and results of the trials.

RESULTS

Nine hundred and eighty-nine clinical trials were identified and from them 333 traditional designs and 19 adaptive designs were included in the review. Two hundred statistical papers were located and 16 were included in the review. The most frequent designs were Standard up and down designs, continual reassessment methods and its variation and designs with Bayesian approaches. More than 80% of the studies evaluated different schemes of chemotherapy. Adaptive designs evaluated only drugs and not any kind of treatment combination and the most often localizations evaluated in both designs were lung, haematology malignancies, and colon cancers.

CONCLUSIONS

Adaptive designs are more efficient from the statistical point of view but they are not yet widely used because of complex and computationally intensive methods needed, substantial effort for planning the trials and lack of regulatory guidance.

Adaptive trial design: its growing role in clinical research and implications for pharmacists

PURPOSE

Current trends and recent developments in use of adaptive trial design methodology for pharmaceutical research, as well as barriers to wider acceptance and implications for pharmacists, are discussed.

SUMMARY

Traditional clinical drug trials typically take many months or years to complete. In contrast, trials incorporating adaptive design elements allow researchers to make midstudy adjustments so that trial objectives are addressed more efficiently. Properly designed adaptive trials can enable researchers to conclude trials of unsuccessful treatments earlier or bring effective drugs to market sooner, improving patient safety and yielding substantial time and cost savings. Challenges and concerns with adaptive trial methodology include inadequate knowledge of adaptive design techniques among health care professionals and increased potential for bias or misinterpretation of trial results stemming from earlier access to data. Over the past decade, U.S. and European regulatory bodies have issued a number of documents to better define acceptable practices for designing, conducting, and reporting the results of adaptive trials, including updated Food and Drug Administration guidance released in 2010. Pharmacists need to stay current with developments in the field to properly assess and interpret trial results.

CONCLUSION

Adaptive trial design is an emerging study methodology that allows for design modifications during a study, with the objective of implementing trial data as early as possible for the benefit of patients and the drug development process.

Confounding due to changing background risk in adaptively randomized trials

BACKGROUND

While adaptive trials tend to improve efficiency, they are also subject to some unique biases.

PURPOSE

We address a bias that arises from adaptive randomization in the setting of a time trend in disease incidence.

METHODS

We use a potential-outcome model and directed acyclic graphs to illustrate the bias that arises from a changing subject allocation ratio with a concurrent change in background risk.

RESULTS

In a trial that uses adaptive randomization, time trends in risk can bias the crude effect estimate obtained by naively combining the data from the different stages of the trial. We illustrate how the bias arises from an interplay of departures from exchangeability among groups and the changing randomization proportions.

LIMITATIONS

We focus on risk-ratio and risk-difference analysis.

CONCLUSIONS

Analysis of trials using adaptive randomization should involve attention to or adjustment for possible trends in background risk. Numerous modeling strategies are available for that purpose, including stratification, trend modeling, inverse-probability-of-treatment weighting, and hierarchical regression.

Stable and nondisruptive in vitro/in vivo labeling of mesenchymal stem cells by internalizing quantum dots

Progress in stem cell research has prioritized the refinement of cell-labeling techniques for in vitro and in vivo basic and therapeutic studies. Although quantum dots, because of their optical properties, are emerging as favorable nanoparticles for bioimaging, substantial refinements or modifications that would improve their biocompatibility are still required. We report here that internalizing quantum dots (i-QDs) generated by their conjugation with an internalizing antibody against a heat shock protein-70 family stress chaperone, mortalin, offered an efficient, genetically noninvasive, nontoxic, and functionally inert way to label mesenchymal stem cells (MSCs). The i-QD-labeled MSCs underwent normal adipocyte, osteocyte, and chondrocyte differentiation in vitro and in vivo, suggesting the potential application of i-QDs in in vivo diagnostics, regenerative and therapeutic medicine.

The design of randomized controlled trials

Today's clinical practice relies on the application of well-designed clinical research, the gold standard test of an intervention being the randomized controlled trial. Principles of the randomized controlled trial include emphasis on the principal research question, randomization, and blinding; definitions of outcome measures, inclusion and exclusion criteria, and comorbid and confounding factors; enrolling an adequate sample size; planning data management and analysis; preventing challenges to trial integrity, such as dropout, drop-in, and bias. The application of pretrial planning is stressed to ensure the proper application of epidemiological principles, resulting in clinical studies that are feasible and generalizable. In addition, funding strategies and trial team composition are discussed.

Neuroprotection for ischemic stroke: past, present and future

Neuroprotection for ischemic stroke refers to strategies, applied singly or in combination, that antagonize the injurious biochemical and molecular events that eventuate in irreversible ischemic injury. There has been a recent explosion of interest in this field, with over 1000 experimental papers and over 400 clinical articles appearing within the past 6 years. These studies, in turn, are the outgrowth of three decades of investigative work to define the multiple mechanisms and mediators of ischemic brain injury, which constitute potential targets of neuroprotection. Rigorously conducted experimental studies in animal models of brain ischemia provide incontrovertible proof-of-principle that high-grade protection of the ischemic brain is an achievable goal. Nonetheless, many agents have been brought to clinical trial without a sufficiently compelling evidence-based pre-clinical foundation. At this writing, around 160 clinical trials of neuroprotection for ischemic stroke have been initiated. Of the approximately 120 completed trials, two-thirds were smaller early-phase safety-feasibility studies. The remaining one-third were typically larger (>200 subjects) phase II or III trials, but, disappointingly, only fewer than one-half of these administered neuroprotective therapy within the 4-6h therapeutic window within which efficacious neuroprotection is considered to be achievable. This fact alone helps to account for the abundance of "failed" trials. This review presents a close survey of the most extensively evaluated neuroprotective agents and classes and considers both the strengths and weakness of the pre-clinical evidence as well as the results and shortcomings of the clinical trials themselves. Among the agent-classes considered are calcium channel blockers; glutamate antagonists; GABA agonists; antioxidants/radical scavengers; phospholipid precursor; nitric oxide signal-transduction down-regulator; leukocyte inhibitors; hemodilution; and a miscellany of other agents. Among promising ongoing efforts, therapeutic hypothermia, high-dose human albumin therapy, and hyperacute magnesium therapy are considered in detail. The potential of combination therapies is highlighted. Issues of clinical-trial funding, the need for improved translational strategies and clinical-trial design, and "thinking outside the box" are emphasized.