Adaptive designs in clinical trials

The changing perspective of clinical trial designs

Maintaining health and well-being of the population is a universal priority. Governments around the globe are therefore seeking greater efficiency and better outcomes from researches being held. Although large randomized trials or systematic review of several large trials provides the highest level of evidence, the intricate cost, time, and difficulties of conventional trials have led to questions about their sustainability commanding search for alternative approaches. Demands for improved competences in medical research have led to mounting interest in newer clinical trial designs. This article provides an insight into newer clinical trial designs, including cluster trials, adaptive designs, the master protocols along with their strengths, weaknesses, and which trials design should be opted for in different clinical scenarios.

Early phase and adaptive design clinical trials in rheumatoid arthritis: a systematic review of early phase trials

Objective

Adaptive designs can enable highly sophisticated and efficient early phase trials, but the clinical inference from these trials is surrounded by complexity, and currently there is a paucity but steadily increasing amount of use of these designs in all fields of medicine. We aim to review early phase trials in RA to discover those that have used adaptive designs and benchmark trial characteristics.

Methods

From an OVID search for journal articles reporting the results of early phase trials in rheumatology, 35 studies were found, with 9 subsequently excluded; 11 were added from manual searches and 19 from searching the references. Study characteristics were extracted from the 56 papers (describing 62 trials), including the number of arms, number of patients, the primary outcome and when it was measured.

Result

One early phase trial using an adaptive design was found. The benchmark early phase trial in RA is a phase II double-blinded randomized trial, with four arms (one control and three intervention), each with 34 patients, and ACR20 measured at 16 weeks as the primary outcome.

Conclusion

The one adaptive design reviewed here, and a simulation study found in the search, both indicate that adaptive designs can be applied to early phase trials in RA. We have described the benchmark, which the efficiency of early phase trials using an adaptive design needs to exceed. These efficient designs could drive down numbers required, time for data collection and thus cost. Changes have been suggested, but more needs to be done.

Advanced Research and Data Methods in Women's Health: Big Data Analytics, Adaptive Studies, and the Road Ahead

Technical advances in science have had broad implications in reproductive and women's health care. Recent innovations in population-level data collection and storage have made available an unprecedented amount of data for analysis while computational technology has evolved to permit processing of data previously thought too dense to study. "Big data" is a term used to describe data that are a combination of dramatically greater volume, complexity, and scale. The number of variables in typical big data research can readily be in the thousands, challenging the limits of traditional research methodologies. Regardless of what it is called, advanced data methods, predictive analytics, or big data, this unprecedented revolution in scientific exploration has the potential to dramatically assist research in obstetrics and gynecology broadly across subject matter. Before implementation of big data research methodologies, however, potential researchers and reviewers should be aware of strengths, strategies, study design methods, and potential pitfalls. Examination of big data research examples contained in this article provides insight into the potential and the limitations of this data science revolution and practical pathways for its useful implementation.

A Double-Blind, Double-Dummy, Flexible-Design Randomized Multicenter Trial: Early Safety of Single- Versus Divided-Dose Rabbit Anti-Thymocyte Globulin Induction in Renal Transplantation

A previous nonblinded, randomized, single-center renal transplantation trial of single-dose rabbit anti-thymocyte globulin induction (SD-rATG) showed improved efficacy compared with conventional divided-dose (DD-rATG) administration. The present multicenter, double-blind/double-dummy STAT trial (Single dose vs. Traditional Administration of Thymoglobulin) evaluated SD-rATG versus DD-rATG induction for noninferiority in early (7-day) safety and tolerability. Ninety-five patients (randomized 1:1) received 6 mg/kg SD-rATG or 1.5 mg/kg/dose DD-rATG, with tacrolimus-mycophenolate maintenance immunosuppression. The primary end point was a composite of fever, hypoxia, hypotension, cardiac complications, and delayed graft function. Secondary end points included 12-month patient survival, graft survival, and rejection. Target enrollment was 165 patients with an interim analysis scheduled after 80 patients. Interim analysis showed primary end point noninferiority of SD-rATG induction (p = 0.6), and a conditional probability of <1.73% of continued enrollment producing a significant difference (futility analysis), leading to early trial termination. Final analysis (95 patients) showed no differences in occurrence of primary end point events (p = 0.58) or patients with no, one, or more than one event (p = 0.81), or rejection, graft, or patient survival (p = 0.78, 0.47, and 0.35, respectively). In this rigorously blinded trial in adult renal transplantation, we have shown SD-rATG induction to be noninferior to DD-rATG induction in early tolerability and equivalent in 12-month safety. (Clinical Trials.gov #NCT00906204.).

Transforming Clinical Trial Eligibility Criteria to Reflect Practical Clinical Application

Historically, oncology clinical trials have focused on comparing a new drug's efficacy to the standard of care. However, as our understanding of molecular pathways in oncology has evolved, so has our ability to predict how patients will respond to a particular drug, and thus comparison with a standard therapy has become less important. Biomarkers and corresponding diagnostic testing are becoming more and more important to drug development but also limit the type of patient who may benefit from the therapy. Newer clinical trial designs have been developed to assess clinically meaningful endpoints in biomarker-enriched populations, and the number of modern, molecularly driven clinical trials are steadily increasing. At the same time, barriers to clinical trial enrollment have also grown. Many barriers contribute to nonenrollment in clinical trials, including patient, physician, institution, protocol, and regulatory barriers. At the protocol level, eligibility criteria have become a large roadblock to clinical trial accrual. Over time, eligibility criteria have become more and more restrictive. To accrue an adequate number of patients to molecularly driven trials, we should consider eligibility criteria carefully and attempt to reduce restrictive criteria. Reducing restrictive eligibility criteria will allow more patients to be eligible for clinical trial participation, will likely increase the speed of drug approvals, and will result in clinical trial results that more accurately reflect treatment of the population in the clinical setting.

Best (but oft-forgotten) practices: the multiple problems of multiplicity-whether and how to correct for many statistical tests

Testing many null hypotheses in a single study results in an increased probability of detecting a significant finding just by chance (the problem of multiplicity). Debates have raged over many years with regard to whether to correct for multiplicity and, if so, how it should be done. This article first discusses how multiple tests lead to an inflation of the α level, then explores the following different contexts in which multiplicity arises: testing for baseline differences in various types of studies, having >1 outcome variable, conducting statistical tests that produce >1 P value, taking multiple "peeks" at the data, and unplanned, post hoc analyses (i.e., "data dredging," "fishing expeditions," or "P-hacking"). It then discusses some of the methods that have been proposed for correcting for multiplicity, including single-step procedures (e.g., Bonferroni); multistep procedures, such as those of Holm, Hochberg, and Šidák; false discovery rate control; and resampling approaches. Note that these various approaches describe different aspects and are not necessarily mutually exclusive. For example, resampling methods could be used to control the false discovery rate or the family-wise error rate (as defined later in this article). However, the use of one of these approaches presupposes that we should correct for multiplicity, which is not universally accepted, and the article presents the arguments for and against such "correction." The final section brings together these threads and presents suggestions with regard to when it makes sense to apply the corrections and how to do so.

Clinical evidence for orphan medicinal products-a cause for concern?

Background

The difficulties associated with organising clinical studies for orphan medicinal products (OMPs) are plentiful. Recent debate on the long-term effectiveness of some OMPs, led us to question whether the initial standards for clinical evidence for OMPs, set by the European Medicines Agency (EMA) at the time of marketing authorization, are too low. Therefore, the aim of this study was to quantitatively evaluate the characteristics and quality of clinical evidence that is presented for OMPs to obtain marketing authorization in Europe, using the new and validated COMPASS tool.

Methods

We quantitatively assessed the characteristics and quality of clinical evidence of the pivotal studies of 64 OMPs as described in the European Public Assessment Report and/or the Scientific Discussion document prepared by the Committee for Human Medicinal Products of the EMA.

Results

The 64 OMPs were altogether authorized for 78 orphan indications, for which 117 studies were identified as 'pivotal’ or 'main’ studies. In approximately two thirds of the studies, the allocation was randomized (64.8%) and a control arm was used (68.5%). Half of the studies applied some type of blinding. Only a minority (26.9%) of the studies included a Quality-of-Life (QoL) related endpoint, of which a third claim an improvement in QoL. Upon analyzing the quality of reporting, we found that some aspects (i.e. the endpoints, the sampling criteria, and the interventions) are well described, whereas other items (i.e. a description of the patients and of potential biases) are not reported for all studies.

Conclusions

In conclusion, the pivotal studies that are the basis for marketing authorization of OMPs are a cause for concern, as they exhibit methodological flaws i.e. the lack of QoL-related endpoints as outcome, lack of blinding in the study design and the use of surrogate endpoints. Additionally, there are shortcomings in the reporting of those studies that complicate the interpretation. A more demanding regulatory process for OMPs is needed to guide evidence-based clinical decision-making.

Advances and challenges towards a vaccine against Chagas disease

Chagas disease is major public health problem, affecting nearly 10 million people, characterized by cardiac alterations leading to congestive heart failure and death of 20-40% of the patients infected with Trypanosoma cruzi, the protozoan parasite responsible for the disease. A vaccine would be key to improve disease control and we review here the recent advances and challenges of a T. cruzi vaccine. There is a growing consensus that a protective immune response requires the activation of a Th1 immune profile, with the stimulation of CD8 (+) T cells. Several vacines types, including recombinant proteins, DNA and viral vectors, as well as heterologous prime-boost combinations, have been found immunogenic and protective in mouse models, providing proof-of-concept data on the feasibility of a preventive or therapeutic vaccine to control a T. cruzi infection. However, several challenges such as better end-points, safety issues and trial design need to be addressed for further vaccine development to proceed.