scholarly journals Pitfalls in reporting sample size calculation in randomized controlled trials published in leading anaesthesia journals: a systematic review

2015 ◽  
Vol 115 (5) ◽  
pp. 699-707 ◽  
Author(s):  
M. Abdulatif ◽  
A. Mukhtar ◽  
G. Obayah
2016 ◽  
Vol 124 (2) ◽  
pp. 558-568 ◽  
Author(s):  
Alireza Mansouri ◽  
Benjamin Cooper ◽  
Samuel M. Shin ◽  
Douglas Kondziolka

OBJECT Randomized-controlled trials (RCTs) are advocated to provide high-level medical evidence. However, in neurosurgery, there are barriers to conducting RCTs. The authors of this study sought to analyze the quality of neurosurgical RCTs since 2000 to determine the adequacy of their design and reporting. METHODS A search of the MEDLINE and EMBASE databases (2000–2014) was conducted. The medical subject heading (MeSH) terms used in the search included: “neurosurgery” OR “neurosurgical procedure,” “brain neoplasms,” “infarction” and “decompression,” “carotid stenosis,” “cerebral hemorrhage,” and “spinal fusion.” These studies were limited to RCTs, in humans, and in the English language. The Consolidated Standards for Reporting of Trials (CONSORT) and Jadad scales were used to assess the quality of RCT design and reporting. The standardized median times cited (median citations divided by years since publication) were used to assess impact. A pragmatic-explanatory continuum indicator summary-based scale was used to assess the design of the studies as primarily pragmatic or explanatory. RESULTS Sixty-one articles were identified, and the following subspecialties were the most common: vascular (23, 37%), followed by functional neurosurgery and neurooncology (both 13, 21%). The following nations were the primary leaders in RCTs: US (25 studies, 41%), Germany (8 studies, 13%), and the United Kingdom (7 studies, 11%). Median sample size was 100 (interquartile range [IQR] 41.5–279). The majority of the studies (40, 66%) had pragmatic objectives. The median number of times cited overall was 69 (IQR 20.5–193). The combined median CONSORT score was 36 (IQR 27.5–39). Blinding was most deficiently reported. Other areas with a relatively low quality of reporting were sample size calculation (34.2% of surgical, 38.5% of drug, and 20% of device studies), allocation concealment (28.9% of surgical, 23.1% of drug, and 50% of device studies), and protocol implementation (18.4% of surgical, 23% of drug, and 20% of device studies). The quality of reporting did not correlate with the study impact. All studies had a median Jadad score ≤ 3. Thirty-three pragmatic studies (83%) and 5 explanatory studies (25%) met the design objectives. All pragmatic studies based on drug and device trials met their objectives, while 74% of pragmatic surgical trials met their objectives. CONCLUSIONS The prevalence of neurosurgical RCTs is low. The quality of RCT design and reporting in neurosurgery is also low. Many study designs are not compatible with stated objectives. Pragmatic studies were more likely to meet design objectives. Given the role of RCTs as one of the highest levels of evidence, it is critical to improve on their methodology and reporting.


Author(s):  
Richard Gray ◽  
Daniel Bressington ◽  
Martin Jones ◽  
David R. Thompson

The manipulation of participant allocation in randomized controlled trials to achieve equal groups sizes may introduce allocation bias potentially leading to larger treatment effect estimates. This study aimed to estimate the proportion of nursing trials that have precisely equal group sizes and examine if there was an association with trial outcome. Data were extracted from a sample of 148 randomized controlled trials published in nursing science journals in 2017. One hundred trials (68%) had precisely equal group sizes. Respectively, a positive outcome was reported in 70% and 58% of trials with equal/unequal groups. Trials from Asia were more likely to have equal group sizes than those from the rest of the world. Most trials reported a sample size calculation (n=105, 71%). In a third of trials (n=36, 34%), the number of participants recruited precisely matched the requirement of the sample size calculation; this was significantly more common in studies with equal group sizes. The high number of nursing trials with equal groups may suggest nurses con-ducting clinical trials are manipulating participant allocation to ensure equal group size increasing the risk of bias.


Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Brent Strong ◽  
John A Oostema ◽  
Nadia Nikroo ◽  
Murtaza Hussain ◽  
Mathew J Reeves

Introduction: A priori sample size determination is an essential step in designing randomized controlled trials (RCTs). Failure to reach pre-planned sample size introduces risk of both falsely negative and spuriously positive findings. We undertook a systematic review of contemporary acute stroke trials to document the prevalence and reasons for termination of trials prior to completion of enrollment. Methods: We searched MEDLINE for RCTs of acute stroke therapy published between 2013 and 2018 in 9 major journals. Manuscripts describing the final primary results of phase 3 and large phase 2 trials of any therapeutic intervention were eligible for inclusion. Study characteristics, including the presence of a data monitoring committee (DMC) and stopping rules, risk-of-bias assessment, funding sources and conflicts of interest, were abstracted from published manuscripts and trial protocols by two independent reviewers. The prevalence of and reasons for early termination were quantified. Multivariable logistic regression was used to identify study-level predictors of early termination. Results: Of 756 hits, 60 were eligible for inclusion, 21 (35%) of which were terminated early. Among the trials stopped early, 10 (48%) reported stopping for benefit or newly available evidence while 11 (52%) were terminated for futility; 20 (95%) reported a DMC and 17 (81%) reported the use of a pre-specified statistical stopping rule. Factors associated with early termination included study location in North America, larger planned sample size, and industry funding (Table). Study location in North America and larger planned sample size retained statistical significance in a multivariable model. Conclusions: One in three contemporary stroke trials were terminated prior to completion of enrollment. Reasons for termination were evenly split between benefit and futility. Further study is needed to understand the reasons for and impact of early termination on study results.


2010 ◽  
Vol 17 (1-2) ◽  
pp. 30-34
Author(s):  
Virginijus ŠAPOKA ◽  
Vytautas KASIULEVIČIUS ◽  
Janina DIDŽIAPETRIENĖ

Randomized controlled trials (RCTs) and systematic reviews are the most reliable methods of determining the effects of treatment. The randomization procedure gives a randomized controlled trial its strength. Random allocation means that all participants have the same chance of being assigned to each of the study groups. The choice of which end point(s) to select is critical to any study design. Intention-to-treat is the preferred approach to the analysis of clinical trials. Sample size calculations and data analyses have an important impact on the planning, interpretation, and conclusions of randomized trials. In this article, we discuss the problematic areas that can affect the outcome of a trial, such as blinding, sample size calculation, randomization; concealment allocation; intention of treating the analysis; selection of end points; selection of traditional versus equivalence testing, early stopped trials, selective publications. Keywords: randomized controlled trials, sample size, outcomes, type of analyses


Author(s):  
Friederike M.-S. Barthel ◽  
Patrick Royston ◽  
Abdel Babiker

Royston and Babiker (2002) presented a menu-driven Stata program for the calculation of sample size or power for complex clinical trial designs under a survival time or binary outcome. In the present article, the package is updated to Stata 8 under the new name ART. Furthermore, the program has been extended to incorporate noninferiority designs and provides more detailed output. This package is the only realistic sample size tool for survival studies available in Stata.


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