Completeness and changes in registered data and reporting bias of randomized controlled trials in ICMJE journals after trial registration policy

Objective

We assessed the adequacy of randomized controlled trial (RCT) registration, changes to registration data and reporting completeness for articles in ICMJE journals during 2.5 years after registration requirement policy.

Methods

For a set of 149 reports of 152 RCTs with ClinicalTrials.gov registration number, published from September 2005 to April 2008, we evaluated the completeness of 9 items from WHO 20-item Minimum Data Set relevant for assessing trial quality. We also assessed changes to the registration elements at the Archive site of ClinicalTrials.gov and compared published and registry data.

Results

RCTs were mostly registered before 13 September 2005 deadline (n = 101, 66.4%); 118 (77.6%) started recruitment before and 31 (20.4%) after registration. At the time of registration, 152 RCTs had a total of 224 missing registry fields, most commonly ‘Key secondary outcomes’ (44.1% RCTs) and ‘Primary outcome’ (38.8%). More RCTs with post-registration recruitment had missing Minimum Data Set items than RCTs with pre-registration recruitment: 57/118 (48.3%) vs. 24/31 (77.4%) (χ² ₁ = 7.255, P = 0.007). Major changes in the data entries were found for 31 (25.2%) RCTs. The number of RCTs with differences between registered and published data ranged from 21 (13.8%) for Study type to 118 (77.6%) for Target sample size.

Conclusions

ICMJE journals published RCTs with proper registration but the registration data were often not adequate, underwent substantial changes in the registry over time and differed in registered and published data. Editors need to establish quality control procedures in the journals so that they continue to contribute to the increased transparency of clinical trials.     

Geographical representativeness of published and ongoing randomized controlled trials. The example of: Tobacco consumption and HIV infection

Background

The challenge for evidence-based healthcare is to reduce mortality and the burden of diseases. This study aimed to compare where research is conducted to where research is needed for 2 public health priorities: tobacco consumption and HIV infection.

Methods

We identified randomized controlled trials (RCTs) included in Cochrane systematic reviews published between 1997 and 2007 and registered ongoing RCTs identified in January 2009 through the World Health Organization''s International Clinical Trials Registry Platform (WHO-ICTRP) evaluating interventions aimed at reducing or stopping tobacco use and treating or preventing HIV infection. We used the WHO and World Bank reports to classify the countries by income level, as well as map the global burden of disease and mortality attributable to tobacco use and HIV infection to the countries where the trials performed.

Results

We evaluated 740 RCTs included in systematic reviews and 346 ongoing RCTs. For tobacco use, 4% of RCTs included in systematic reviews and 2% of ongoing trials were performed in low- and middle-income countries, even though these countries represented 70% of the mortality related to tobacco use. For HIV infection, 31% of RCTs included in systematic reviews and 33% of ongoing trials were performed in low- and middle-income countries, even though these countries represented 99% of the mortality related to HIV infection.

Conclusions

Our results highlight an important underrepresentation of low- and middle-income countries in currently available evidence (RCTs included in systematic reviews) and awaiting evidence (registered ongoing RCTs) for reducing or stopping tobacco use and treating or preventing HIV infection.     

Measurable prediction for the single patient and the results of large double blind controlled randomized trials

BACKGROUND: It has been shown that the clinical state of one patient can be represented by known measured variables of interest, each of which then form the element of a fuzzy set as point in the unit hypercube. We hypothesized that precise comparison of a single patient with the average patient of a large double blind controlled randomized study is possible using fuzzy theory. METHODS/PRINCIPLE FINDINGS: The sets as points unit hypercube geometry allows fuzzy subsethood to define in measures of fuzzy cardinality different conditions, similarity and comparison between fuzzy sets. A fuzzy measure of prediction is defined from fuzzy measures of similarity and comparison. It is a measure of the degree to which fuzzy set A is similar to fuzzy set B when different conditions are taken into account and removed from the comparison. When represented as a fuzzy set as point in the unit hypercube, a clinical patient can be compared to an average patient of a large group study in a precise manner. This comparison is expressed by the fuzzy prediction measure. This measure in itself is not a probability. Once thus precisely matched to the average patient of a large group study, risk reduction is calculated by multiplying the measured similarity of the clinical patient to the risk of the average trial patient. CONCLUSION/SIGNIFICANCE: Otherwise not precisely translatable to the single case, the result of group statistics can be applied to the single case through the use of fuzzy subsethood and measured in fuzzy cardinality. This measure is an alternative to a Bayesian or other probability based statistical approach.     

Diagnostic randomized controlled trials: the final frontier

ABSTRACT: Clinicians, patients, governments, third-party payers, and the public take for granted that diagnostic tests are accurate, safe and effective. However, we may be seriously misled if we are relying on robust study design to ensure accurate, safe, and effective diagnostic tests. Properly conducted, randomized controlled trials are the gold standard for assessing the effectiveness and safety of interventions, yet are rarely conducted in the assessment of diagnostic tests. Instead, diagnostic cohort studies are commonly performed to assess the characteristics of a diagnostic test including sensitivity and specificity. While diagnostic cohort studies can inform us about the relative accuracy of an experimental diagnostic intervention compared to a reference standard, they do not inform us about whether the differences in accuracy are clinically important, or the degree of clinical importance (in other words, the impact on patient outcomes). In this commentary we provide the advantages of the diagnostic randomized controlled trial and suggest a greater awareness and uptake in their conduct. Doing so will better ensure that patients are offered diagnostic procedures that will make a clinical difference.     

Reporting of informed consent, standard of care and post-trial obligations in global randomized intervention trials: a systematic survey of registered trials

Objective:  Ethical guidelines are designed to ensure benefits, protection and respect of participants in clinical research. Clinical trials must now be registered on open-access databases and provide details on ethical considerations. This systematic survey aimed to determine the extent to which recently registered clinical trials report the use of standard of care and post-trial obligations in trial registries, and whether trial characteristics vary according to setting.
Methods:  We selected global randomized trials registered on http://www.clinicaltrials.gov and http://www.controlled-trials.com . We searched for intervention trials of HIV/AIDS, malaria, and tuberculosis from 9 October 2004, the date of the most recent version of the Helsinki Declaration, to 10 April 2007.
Results:  We collected data from 312 trials. Fifty-eight percent (58%, 95% CI  =  53 to 64) of trial protocols report informed consent. Fifty-eight percent (58%, 95% CI  =  53 to 64) of trials report active controls. Almost no trials (1%, 95% CI  =  0.5 to 3) mention post-trial provisions. Most trials measure surrogate outcomes. Twenty percent (20%, 95% CI  =  16 to 25) of trials measure patient-important outcomes, such as death; and the odds that these outcomes are in a low income country are five times greater than for a developed country (odds ratio (OR) 5.03, 95% CI  =  2.70 to 9.35, p  = < 0.001). Pharmaceutical companies are involved in 28% (CI  =  23 to 33) of trials and measure surrogate outcomes more often than nonpharmaceutical companies (OR 2.45, 95% CI  =  1.18 to 5.09, p  =  0.31).
Conclusion:  We found a large discrepancy in the quality of reporting and approaches used in trials in developing settings compared to wealthier settings.     

Male inclusion in randomized controlled trials of lifestyle weight loss interventions

The prevalence of obesity is similar for men (32.2%) and women (35.5%). It has been assumed that lifestyle weight loss interventions have been developed and tested in predominately female samples, but this has not been systematically investigated. The aim of this review was to investigate total and ethnic male inclusion in randomized controlled trials of lifestyle interventions. PUBMED, MEDLINE, and PSYCHINFO were searched for randomized controlled trials of lifestyle weight loss interventions (N = 244 studies with a total of 95,207 participants) published in the last 10 years (1999-2009). A trial must be in English, included weight loss as an outcome, and tested a dietary, exercise, and/or other behavioral intervention for weight loss. Results revealed samples were on average 27% male vs. 73% female (P < 0.001). Trials recruiting a diseased sample included a larger proportion of males than those not targeting a disease (35% vs. 21%; P < 0.001). About 32% of trials used exclusively female samples, whereas only 5% used exclusively male samples (P < 0.001). No studies in the past 10 years specifically targeted minority males. Ethnic males identified composed 1.8% of total participants in US studies. Only 24% of studies that underrepresented males provided a reason. Males, especially ethnic males, are underrepresented in lifestyle weight loss trials.     

Cardiac resynchronization therapy: a meta-analysis of randomized controlled trials

Background

Studies of cardiac resynchronization therapy in addition to an implantable cardioverter defibrillator in patients with mild to moderate congestive heart failure had not been shown to reduce mortality until the recent RAFT trial (Resynchronization/Defibrillation for Ambulatory Heart Failure Trial). We performed a meta-analysis including the RAFT trial to determine the effect of cardiac resynchronization therapy with or without an implantable defibrillator on mortality.

Methods

We searched electronic databases and other sources for reports of randomized trials using a parallel or crossover design. We included studies involving patients with heart failure receiving optimal medical therapy that compared cardiac resynchronization therapy with optimal medical therapy alone, or cardiac resynchronization therapy plus an implantable defibrillator with a standard implantable defibrillator. The primary outcome was mortality. The optimum information size was considered to assess the minimum amount of information required in the literature to reach reliable conclusions about cardiac resynchronization therapy.

Results

Of 3071 reports identified, 12 studies (n = 7538) were included in our meta-analysis. Compared with optimal medical therapy alone, cardiac resynchronization therapy plus optimal medical therapy significantly reduced mortality (relative risk [RR] 0.73, 95% confidence interval [CI] 0.62–0.85). Compared with an implantable defibrillator alone, cardiac resynchronization therapy plus an implantable defibrillator significantly reduced mortality (RR 0.83, 95% CI 0.72–0.96). This last finding remained significant among patients with New York Heart Association (NYHA) class I or II disease (RR 0.80, 95% CI 0.67–0.96) but not among those with class III or IV disease (RR 0.84, 95% CI 0.69–1.07). Analysis of the optimum information size showed that the sequential monitoring boundary was crossed, which suggests no need for further clinical trials.

Interpretation

The cumulative evidence is now conclusive that the addition of cardiac resynchronization to optimal medical therapy or defibrillator therapy significantly reduces mortality among patients with heart failure.Congestive heart failure is currently reaching epidemic proportions in Canada, with 500 000 Canadians affected and 50 000 new patients identified each year.¹ It accounts for more than 100 000 hospital admissions per year and has a one-year mortality ranging from 15% to 50%, depending on the severity of heart failure.² By 2050, the number of patients with heart failure is projected to increase threefold.²Advances in medical therapies have resulted in substantial reductions in mortality associated with congestive heart failure.^3–7 The use of devices has recently become an important adjuvant therapy.⁸ Cardiac resynchronization therapy involves pacing from both the right and left ventricles simultaneously to improve myocardial efficiency (see radiographs in Appendix 1, at www.cmaj.ca/cgi/content/full/cmaj.101685/DC1). Cardiac resynchronization therapy has been shown to reduce morbidity and, when compared with medical therapy alone, to reduce mortality.^9–13 Until recently, it was not shown to reduce mortality among patients who also received an implantable cardioverter defibrillator. Among patients receiving optimal medical therapy, the Resynchronization/Defibrillation for Ambulatory Heart Failure Trial (RAFT) showed the superiority of cardiac resynchronization therapy in addition to an implantable defibrillator over a standard implantable defibrillator in reducing mortality and the combined outcome of death from any cause or hospital admission related to heart failure.¹⁴We performed a meta-analysis to further assess the effect on mortality of cardiac resynchronization therapy with and without an implantable defibrillator among patients with mildly symptomatic and advanced heart failure.     

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.     

Dexamethasone and bacterial meningitis. A meta-analysis of randomized controlled trials.

A meta-analysis of 5 randomized, controlled trials using dexamethasone as adjunctive therapy in the treatment of bacterial meningitis in children was done to assess the efficacy in reducing sequelae. A 6th study including both children and adults was analyzed separately. Results of the 5 pediatric studies indicated no significant difference in case-fatality rate between the placebo and dexamethasone groups. Significantly more neurologic sequelae were found in the placebo group during the period from discharge from hospital to 6 weeks after discharge (relative risk [RR] = 1.99, 95% confidence interval [CI] 1.13 to 3.53) and during the period beginning 6 months after discharge (RR = 3.90, 95% CI 1.72 to 8.85). The incidence of neurologic sequelae from 6 weeks to 6 months after discharge, though less with dexamethasone administration, did not reach statistical significance. The frequency of bilateral hearing loss was significantly greater in the placebo group (RR = 4.12, 95% CI 1.74 to 9.79), but unilateral loss was not statistically different in the two groups. Dexamethasone administration in addition to antimicrobial therapy appears to be effective in reducing neurologic sequelae and bilateral hearing loss associated with bacterial meningitis in children.     

Targeted maximum likelihood estimation for dynamic treatment regimes in sequentially randomized controlled trials

Sequential Randomized Controlled Trials (SRCTs) are rapidly becoming essential tools in the search for optimized treatment regimes in ongoing treatment settings. Analyzing data for multiple time-point treatments with a view toward optimal treatment regimes is of interest in many types of afflictions: HIV infection, Attention Deficit Hyperactivity Disorder in children, leukemia, prostate cancer, renal failure, and many others. Methods for analyzing data from SRCTs exist but they are either inefficient or suffer from the drawbacks of estimating equation methodology. We describe an estimation procedure, targeted maximum likelihood estimation (TMLE), which has been fully developed and implemented in point treatment settings, including time to event outcomes, binary outcomes and continuous outcomes. Here we develop and implement TMLE in the SRCT setting. As in the former settings, the TMLE procedure is targeted toward a pre-specified parameter of the distribution of the observed data, and thereby achieves important bias reduction in estimation of that parameter. As with the so-called Augmented Inverse Probability of Censoring Weight (A-IPCW) estimator, TMLE is double-robust and locally efficient. We report simulation results corresponding to two data-generating distributions from a longitudinal data structure.     

Sample size recalculation in multicenter randomized controlled clinical trials based on noncomparative data

Many late-phase clinical trials recruit subjects at multiple study sites. This introduces a hierarchical structure into the data that can result in a power-loss compared to a more homogeneous single-center trial. Building on a recently proposed approach to sample size determination, we suggest a sample size recalculation procedure for multicenter trials with continuous endpoints. The procedure estimates nuisance parameters at interim from noncomparative data and recalculates the sample size required based on these estimates. In contrast to other sample size calculation methods for multicenter trials, our approach assumes a mixed effects model and does not rely on balanced data within centers. It is therefore advantageous, especially for sample size recalculation at interim. We illustrate the proposed methodology by a study evaluating a diabetes management system. Monte Carlo simulations are carried out to evaluate operation characteristics of the sample size recalculation procedure using comparative as well as noncomparative data, assessing their dependence on parameters such as between-center heterogeneity, residual variance of observations, treatment effect size and number of centers. We compare two different estimators for between-center heterogeneity, an unadjusted and a bias-adjusted estimator, both based on quadratic forms. The type 1 error probability as well as statistical power are close to their nominal levels for all parameter combinations considered in our simulation study for the proposed unadjusted estimator, whereas the adjusted estimator exhibits some type 1 error rate inflation. Overall, the sample size recalculation procedure can be recommended to mitigate risks arising from misspecified nuisance parameters at the planning stage.