Adjudication-related processes are underreported and lack standardization in clinical trials of venous thromboembolism: a systematic review

OBJECTIVES Although the use of an adjudication committee (AC) for outcomes is recommended in randomized controlled trials, there are limited data on the process of adjudication. We therefore aimed to assess whether the reporting of the adjudication process in venous thromboembolism (VTE) trials meets existing quality standards and which characteristics of trials influence the use of an AC. STUDY DESIGN AND SETTING We systematically searched MEDLINE and the Cochrane Library from January 1, 2003, to June 1, 2012, for randomized controlled trials on VTE. We abstracted information about characteristics and quality of trials and reporting of adjudication processes. We used stepwise backward logistic regression model to identify trial characteristics independently associated with the use of an AC. RESULTS We included 161 trials. Of these, 68.9% (111 of 161) reported the use of an AC. Overall, 99.1% (110 of 111) of trials with an AC used independent or blinded ACs, 14.4% (16 of 111) reported how the adjudication decision was reached within the AC, and 4.5% (5 of 111) reported on whether the reliability of adjudication was assessed. In multivariate analyses, multicenter trials [odds ratio (OR), 8.6; 95% confidence interval (CI): 2.7, 27.8], use of a data safety-monitoring board (OR, 3.7; 95% CI: 1.2, 11.6), and VTE as the primary outcome (OR, 5.7; 95% CI: 1.7, 19.4) were associated with the use of an AC. Trials without random allocation concealment (OR, 0.3; 95% CI: 0.1, 0.8) and open-label trials (OR, 0.3; 95% CI: 0.1, 1.0) were less likely to report an AC. CONCLUSION Recommended processes of adjudication are underreported and lack standardization in VTE-related clinical trials. The use of an AC varies substantially by trial characteristics.

Staging of osteoarthritis for clinical trials on femoroacetabular impingement

Future clinical trials investigating the natural history and treatment of femoroacetabular impingement (FAI) will require multimodal staging systems for hip osteoarthritis because the optimal system will differ based on the size of the study population, the specific objective in question, and the time frame in which the investigator expects to see the specified end point. Plain radiographs are readily available, low in cost, and of unquestioned validity, but they are relatively insensitive to early joint damage. MRI allows assessment of both bony and soft-tissue pathology within the joint, and it is much more sensitive for early joint damage because cartilage is visualized directly. Biochemical imaging techniques such as delayed gadolinium-enhanced MRI of cartilage, T2 mapping, and T1rho offer the potential to identify biochemical damage to cartilage before the onset of irreversible tissue loss. In the future, biomarkers may allow earlier detection of osteoarthritis before the development of radiographic evidence of disease.

BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

Phase I clinical trials in 56 patients with thyroid cancer: the M. D. Anderson Cancer Center experience.

INTRODUCTION: Thyroid cancer is the most common endocrine malignancy. The outcomes of patients with relapsed thyroid cancer treated on early-phase clinical trials have not been systematically analyzed. PATIENTS AND METHODS: We reviewed the records of consecutive patients with metastatic thyroid cancer referred to the Phase I Clinical Trials Program from March 2006 to April 2008. Best response was assessed by Response Evaluation Criteria in Solid Tumors. RESULTS: Fifty-six patients were identified. The median age was 55 yr (range 35-79 yr). Of 49 patients evaluable for response, nine (18.4%) had a partial response, and 16 (32.7%) had stable disease for 6 months or longer. The median progression-free survival was 1.12 yr. With a median follow-up of 15.6 months, the 1-yr survival rate was 81%. In univariate analysis, factors predicting shorter survival were anaplastic histology (P = 0.0002) and albumin levels less than 3.5 g/dl (P = 0.05). Among 26 patients with tumor decreases, none died (median follow-up 1.3 yr), whereas 52% of patients with any tumor increase died by 1 yr (P = 0.0001). The median time to failure in our phase I clinical trials was 11.5 months vs. 4.1 months for the previous treatment (P = 0.04). CONCLUSION: Patients with advanced thyroid cancer treated on phase I clinical trials had high rates of partial response and prolonged stable disease. Time to failure was significantly longer on the first phase I trial compared with the prior conventional treatment. Patients with any tumor decrease had significantly longer survival than those with any tumor increase.

Robust meta-analytic-predictive priors in clinical trials with historical control information.

Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials.

Factorial designs: an overview with applications to orthodontic clinical trials.

Factorial designs for clinical trials are often encountered in medical, dental, and orthodontic research. Factorial designs assess two or more interventions simultaneously and the main advantage of this design is its efficiency in terms of sample size as more than one intervention may be assessed on the same participants. However, the factorial design is efficient only under the assumption of no interaction (no effect modification) between the treatments under investigation and, therefore, this should be considered at the design stage. Conversely, the factorial study design may also be used for the purpose of detecting an interaction between two interventions if the study is powered accordingly. However, a factorial design powered to detect an interaction has no advantage in terms of the required sample size compared to a multi-arm parallel trial for assessing more than one intervention. It is the purpose of this article to highlight the methodological issues that should be considered when planning, analysing, and reporting the simplest form of this design, which is the 2 × 2 factorial design. An example from the field of orthodontics using two parameters (bracket type and wire type) on maxillary incisor torque loss will be utilized in order to explain the design requirements, the advantages and disadvantages of this design, and its application in orthodontic research.

Feasibility platform for stroke studies: an online tool to improve eligibility criteria for clinical trials

BACKGROUND AND PURPOSE Eligibility criteria are a key factor for the feasibility and validity of clinical trials. We aimed to develop an online tool to assess the potential effect of inclusion and exclusion criteria on the proportion of patients eligible for an acute stroke trial. METHODS We identified relevant inclusion and exclusion criteria of acute stroke trials. Based on these criteria and using a cohort of 1537 consecutive patients with acute ischemic stroke from 3 stroke centers, we developed a web portal feasibility platform for stroke studies (FePASS) to estimate proportions of eligible patients for acute stroke trials. We applied the FePASS resource to calculate the proportion of patients eligible for 4 recent stroke studies. RESULTS Sixty-one eligibility criteria were derived from 30 trials on acute ischemic stroke. FePASS, publicly available at http://fepass.uni-muenster.de, displays the proportion of patients in percent to assess the effect of varying values of relevant eligibility criteria, for example, age, symptom onset time, National Institutes of Health Stroke Scale, and prestroke modified Rankin Scale, on this proportion. The proportion of eligible patients for 4 recent stroke studies ranged from 2.1% to 11.3%. Slight variations of the inclusion criteria could substantially increase the proportion of eligible patients. CONCLUSIONS FePASS is an open access online resource to assess the effect of inclusion and exclusion criteria on the proportion of eligible patients for a stroke trial. FePASS can help to design stroke studies, optimize eligibility criteria, and to estimate the potential recruitment rate.

A pilot test of the new Swiss regulatory procedure for categorizing clinical trials by risk: A randomized controlled trial

BACKGROUND/AIMS Several countries are working to adapt clinical trial regulations to align the approval process to the level of risk for trial participants. The optimal framework to categorize clinical trials according to risk remains unclear, however. Switzerland is the first European country to adopt a risk-based categorization procedure in January 2014. We assessed how accurately and consistently clinical trials are categorized using two different approaches: an approach using criteria set forth in the new law (concept) or an intuitive approach (ad hoc). METHODS This was a randomized controlled trial with a method-comparison study nested in each arm. We used clinical trial protocols from eight Swiss ethics committees approved between 2010 and 2011. Protocols were randomly assigned to be categorized in one of three risk categories using the concept or the ad hoc approach. Each protocol was independently categorized by the trial's sponsor, a group of experts and the approving ethics committee. The primary outcome was the difference in categorization agreement between the expert group and sponsors across arms. Linear weighted kappa was used to quantify agreements, with the difference between kappas being the primary effect measure. RESULTS We included 142 of 231 protocols in the final analysis (concept = 78; ad hoc = 64). Raw agreement between the expert group and sponsors was 0.74 in the concept and 0.78 in the ad hoc arm. Chance-corrected agreement was higher in the ad hoc (kappa: 0.34 (95% confidence interval = 0.10-0.58)) than in the concept arm (0.27 (0.06-0.50)), but the difference was not significant (p = 0.67). LIMITATIONS The main limitation was the large number of protocols excluded from the analysis mostly because they did not fit with the clinical trial definition of the new law. CONCLUSION A structured risk categorization approach was not better than an ad hoc approach. Laws introducing risk-based approaches should provide guidelines, examples and templates to ensure correct application.

PEDro or Cochrane to Assess the Quality of Clinical Trials? A Meta-Epidemiological Study.

OBJECTIVE There is debate on how the methodological quality of clinical trials should be assessed. We compared trials of physical therapy (PT) judged to be of adequate quality based on summary scores from the Physiotherapy Evidence Database (PEDro) scale with trials judged to be of adequate quality by Cochrane Risk of Bias criteria. DESIGN Meta-epidemiological study within Cochrane Database of Systematic Reviews. METHODS Meta-analyses of PT trials were identified in the Cochrane Database of Systematic Reviews. For each trial PeDro and Cochrane assessments were extracted from the PeDro and Cochrane databases. Adequate quality was defined as adequate generation of random sequence, concealment of allocation, and blinding of outcome assessors (Cochrane criteria) or as trials with a PEDro summary score ≥5 or ≥6 points. We combined trials of adequate quality using random-effects meta-analysis. RESULTS Forty-one Cochrane reviews and 353 PT trials were included. All meta-analyses included trials with PEDro scores ≥5, 37 (90.2%) included trials with PEDro scores ≥6 and only 22 (53.7%) meta-analyses included trials of adequate quality according to the Cochrane criteria. Agreement between PeDro and Cochrane was poor for PeDro scores of ≥5 points (kappa = 0.12; 95% CI 0.07 to 0.16) and slight for ≥6 points (kappa 0.24; 95% CI 0.16-0.32). When combining effect sizes of trials deemed to be of adequate quality according to PEDro or Cochrane criteria, we found that a substantial difference in the combined effect size (≥0.15) was evident in 9 (22%) out of the 41 meta-analyses for PEDro cutoff ≥5 and 10 (24%) for cutoff ≥6. CONCLUSIONS The PeDro and Cochrane approaches lead to different sets of trials of adequate quality, and different combined treatment estimates from meta-analyses of these trials. A consistent approach to assessing RoB in trials of physical therapy should be adopted.

Hyperthermia-related clinical trials on cancer treatment within the ClinicalTrials.gov registry

PURPOSE Hyperthermia has been shown to improve the effectiveness of chemotherapy and radiotherapy in the treatment of cancer. This paper summarises all recent clinical trials registered in the ClinicalTrials.gov registry. MATERIALS AND METHODS The records of 175,538 clinical trials registered at ClinicalTrials.gov were downloaded on 29 September 2014 and a database was established. We searched this database for hyperthermia or equivalent words. RESULTS A total of 109 trials were identified in which hyperthermia was part of the treatment regimen. Of these, 49 trials (45%) had hyperthermic intraperitoneal chemotherapy after cytoreductive surgery (HIPEC) as the primary intervention, and 14 other trials (13%) were also testing some form of intraperitoneal hyperthermic chemoperfusion. Seven trials (6%) were testing perfusion attempts to other locations (thoracic/pleural n = 4, limb n = 2, hepatic n = 1). Sixteen trials (15%) were testing regional hyperthermia, 13 trials (12%) whole body hyperthermia, seven trials (6%) superficial hyperthermia and two trials (2%) interstitial hyperthermia. One remaining trial tested laser hyperthermia. CONCLUSIONS In contrast to the general opinion, this analysis shows continuous interest and ongoing clinical research in the field of hyperthermia. Interestingly, the majority of trials focused on some form of intraperitoneal hyperthermic chemoperfusion. Despite the high number of active clinical studies, HIPEC is a topic with limited attention at the annual meetings of the European Society for Hyperthermic Oncology and the Society of Thermal Medicine. The registration of on-going clinical trials is of paramount importance for the achievement of a comprehensive overview of available clinical research activities involving hyperthermia.

An analysis of protocols and publications suggested that most discontinuations of clinical trials were not based on preplanned interim analyses or stopping rules.

OBJECTIVES To investigate the frequency of interim analyses, stopping rules, and data safety and monitoring boards (DSMBs) in protocols of randomized controlled trials (RCTs); to examine these features across different reasons for trial discontinuation; and to identify discrepancies in reporting between protocols and publications. STUDY DESIGN AND SETTING We used data from a cohort of RCT protocols approved between 2000 and 2003 by six research ethics committees in Switzerland, Germany, and Canada. RESULTS Of 894 RCT protocols, 289 prespecified interim analyses (32.3%), 153 stopping rules (17.1%), and 257 DSMBs (28.7%). Overall, 249 of 894 RCTs (27.9%) were prematurely discontinued; mostly due to reasons such as poor recruitment, administrative reasons, or unexpected harm. Forty-six of 249 RCTs (18.4%) were discontinued due to early benefit or futility; of those, 37 (80.4%) were stopped outside a formal interim analysis or stopping rule. Of 515 published RCTs, there were discrepancies between protocols and publications for interim analyses (21.1%), stopping rules (14.4%), and DSMBs (19.6%). CONCLUSION Two-thirds of RCT protocols did not consider interim analyses, stopping rules, or DSMBs. Most RCTs discontinued for early benefit or futility were stopped without a prespecified mechanism. When assessing trial manuscripts, journals should require access to the protocol.

Addressing missing participant outcome data in dental clinical trials

Missing outcome data are common in clinical trials and despite a well-designed study protocol, some of the randomized participants may leave the trial early without providing any or all of the data, or may be excluded after randomization. Premature discontinuation causes loss of information, potentially resulting in attrition bias leading to problems during interpretation of trial findings. The causes of information loss in a trial, known as mechanisms of missingness, may influence the credibility of the trial results. Analysis of trials with missing outcome data should ideally be handled with intention to treat (ITT) rather than per protocol (PP) analysis. However, true ITT analysis requires appropriate assumptions and imputation of missing data. Using a worked example from a published dental study, we highlight the key issues associated with missing outcome data in clinical trials, describe the most recognized approaches to handling missing outcome data, and explain the principles of ITT and PP analysis.

Bayesian doubly optimal group sequential designs for randomized clinical trials

When conducting a randomized comparative clinical trial, ethical, scientific or economic considerations often motivate the use of interim decision rules after successive groups of patients have been treated. These decisions may pertain to the comparative efficacy or safety of the treatments under study, cost considerations, the desire to accelerate the drug evaluation process, or the likelihood of therapeutic benefit for future patients. At the time of each interim decision, an important question is whether patient enrollment should continue or be terminated; either due to a high probability that one treatment is superior to the other, or a low probability that the experimental treatment will ultimately prove to be superior. The use of frequentist group sequential decision rules has become routine in the conduct of phase III clinical trials. In this dissertation, we will present a new Bayesian decision-theoretic approach to the problem of designing a randomized group sequential clinical trial, focusing on two-arm trials with time-to-failure outcomes. Forward simulation is used to obtain optimal decision boundaries for each of a set of possible models. At each interim analysis, we use Bayesian model selection to adaptively choose the model having the largest posterior probability of being correct, and we then make the interim decision based on the boundaries that are optimal under the chosen model. We provide a simulation study to compare this method, which we call Bayesian Doubly Optimal Group Sequential (BDOGS), to corresponding frequentist designs using either O'Brien-Fleming (OF) or Pocock boundaries, as obtained from EaSt 2000. Our simulation results show that, over a wide variety of different cases, BDOGS either performs at least as well as both OF and Pocock, or on average provides a much smaller trial. ^