scholarly journals The quality of the reported sample size calculation in clinical trials on COVID-19 patients indexed in PubMed

2020 ◽  
Vol 77 ◽  
pp. 139-140 ◽  
Author(s):  
Paul H. Lee
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Sample Size Calculation

An Evaluation of the Quality of Clinical Trials in Anesthesia

2001 ◽  
Vol 95 (5) ◽  
pp. 1068-1073 ◽  
Author(s):  
Hwee Leng Pua ◽  
Jerrold Lerman ◽  
Mark W. Crawford ◽  
James G. Wright
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Type I Error ◽  
Sample Size Calculation ◽  
Adverse Outcomes ◽  
Random Allocation ◽  
Type I ◽  
Trial Methodology ◽  
Eligibility Criteria

Background The authors evaluated the quality of clinical trials published in four anesthesia journals during the 20-yr period from 1981-2000. Methods Trials published in four major anesthesia journals during the periods 1981-1985, 1991-1995, and the first 6 months of 2000 were grouped according to journal and year. Using random number tables, four trials were selected from all of the eligible clinical trials in each journal in each year for the periods 1981-1985 and 1991-1995, and five trials were selected from all of the trials in each journal in the first 6 months of 2000. Methods and results sections from the 160 trials from 1981-1985 and 1991-1995 were randomly ordered and distributed to three of the authors for blinded review of the quality of the study design according to 10 predetermined criteria (weighted equally, maximum score of 10): informed consent and ethics approval, eligibility criteria, sample size calculation, random allocation, method of randomization, blind assessment of outcome, adverse outcomes, statistical analysis, type I error, and type II error. After these trials were evaluated, 20 trials from the first 6 months of 2000 were randomly ordered, distributed, and evaluated as described. Results The mean (+/- SD) analysis scores pooled for the four journals increased from 5.5 +/- 1.4 in 1981-1985 to 7.0 +/- 1.1 in 1991-1995 (P < 0.00001) and to 7.8 +/- 1.5 in 2000. For 7 of the 10 criteria, the percentage of trials from the four journals that fulfilled the criteria increased significantly between 1981-1985 and 1991-1995. During the 20-yr period, the reporting of sample size calculation and method of randomization increased threefold to fourfold, whereas the frequency of type I statistical errors remained unchanged. Conclusion Although the quality of clinical trials in four major anesthesia journals has increased steadily during the past two decades, specific areas of trial methodology require further attention.

scholarly journals The Quality of Sample Size Calculation (SSC) Reporting in Cancer Clinical Trials

2012 ◽  
Vol 23 ◽  
pp. ix450
Author(s):  
G.M. Bariani ◽  
A.C.R.C. Ferrari ◽  
P.M. Hoff ◽  
R. Arai ◽  
M. Precivale ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Sample Size Calculation ◽  
Cancer Clinical Trials

scholarly journals A review of trauma and orthopaedic randomised clinical trials published in high-impact general medical journals

2021 ◽  
Author(s):  
Luke Farrow ◽  
William T. Gardner ◽  
Andrew D. Ablett ◽  
Vladislav Kutuzov ◽  
Alan Johnstone
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Trial Design ◽  
Sample Size Calculation ◽  
High Impact ◽  
Risk Of Bias ◽  
Randomised Clinical Trials ◽  
Medical Journals ◽  
General Medical Journals

Abstract Introduction The recent past has seen a significant increase in the number of trauma and orthopaedic randomised clinical trials published in “the big five” general medical journals. The quality of this research has, however, not yet been established. Methods We therefore set out to critically appraise the quality of available literature over a 10-year period (April 2010–April 2020) through a systematic search of these 5 high-impact general medical journals (JAMA, NEJM, BMJ, Lancet and Annals). A standardised data extraction proforma was utilised to gather information regarding: trial design, sample size calculation, results, study quality and pragmatism. Quality assessment was performed using the Cochrane Risk of Bias 2 tool and the modified Delphi list. Study pragmatism was assessed using the PRECIS-2 tool. Results A total of 25 studies were eligible for inclusion. Over half of the included trials did not meet their sample size calculation for the primary outcome, with a similar proportion of these studies at risk of type II error for their non-significant results. There was a high degree of pragmatism according to PRECIS-2. Non-significant studies had greater pragmatism that those with statistically significant results (p < 0.001). Only 56% studies provided adequate justification for the minimum clinically important difference (MCID) in the population assessed. Overall, very few studies were deemed high quality/low risk of bias. Conclusions These findings highlight that there are some important methodological concerns present within the current evidence base of RCTs published in high-impact medical journals. Potential strategies that may improve future trial design are highlighted. Level of evidence Level 1.

Sample size calculation for clinical trials in which entry criteria and outcomes are counts of events

1994 ◽  
Vol 13 (8) ◽  
pp. 859-870 ◽  
Author(s):  
Robert P. McMahon ◽  
Michael Proschan ◽  
Nancy L. Geller ◽  
Peter H. Stone ◽  
George Sopko
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Sample Size Calculation

Statistical Principles for Clinical Trials

1998 ◽  
Vol 26 (2) ◽  
pp. 57-65 ◽  
Author(s):  
R Kay
Keyword(s):  
Clinical Trials ◽  
Confidence Interval ◽  
Sample Size ◽  
Sample Size Calculation ◽  
P Value ◽  
Clinical Value ◽  
Treatment Groups ◽  
Correct Calculation ◽  
Intent To Treat ◽  
Comparative Trials

If a trial is to be well designed, and the conclusions drawn from it valid, a thorough understanding of the benefits and pitfalls of basic statistical principles is required. When setting up a trial, appropriate sample-size calculation is vital. If initial calculations are inaccurate, trial results will be unreliable. The principle of intent-to-treat in comparative trials is examined. Randomization as a method of selecting patients to treatment is essential to ensure that the treatment groups are equalized in terms of avoiding biased allocation in the mix of patients within groups. Once trial results are available the correct calculation and interpretation of the P-value is important. Its limitations are examined, and the use of the confidence interval to help draw valid conclusions regarding the clinical value of treatments is explored.

scholarly journals Approaches to sample size calculation for clinical trials in rare diseases

2018 ◽  
Vol 17 (3) ◽  
pp. 214-230 ◽  
Author(s):  
Frank Miller ◽  
Sarah Zohar ◽  
Nigel Stallard ◽  
Jason Madan ◽  
Martin Posch ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Rare Diseases ◽  
Sample Size Calculation

scholarly journals Design and analysis of a clinical trial using previous trials as historical control

2019 ◽  
Vol 16 (5) ◽  
pp. 531-538 ◽  
Author(s):  
David Alan Schoenfeld ◽  
Dianne M Finkelstein ◽  
Eric Macklin ◽  
Neta Zach ◽  
David L Ennist ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Amyotrophic Lateral Sclerosis ◽  
Sample Size ◽  
Standard Error ◽  
Controlled Trial ◽  
Sample Size Calculation ◽  
Control Group ◽  
Controlled Trials ◽  
Number Of Patients ◽  
Lateral Sclerosis

Background/AimsFor single arm trials, a treatment is evaluated by comparing an outcome estimate to historically reported outcome estimates. Such a historically controlled trial is often analyzed as if the estimates from previous trials were known without variation and there is no trial-to-trial variation in their estimands. We develop a test of treatment efficacy and sample size calculation for historically controlled trials that considers these sources of variation.MethodsWe fit a Bayesian hierarchical model, providing a sample from the posterior predictive distribution of the outcome estimand of a new trial, which, along with the standard error of the estimate, can be used to calculate the probability that the estimate exceeds a threshold. We then calculate criteria for statistical significance as a function of the standard error of the new trial and calculate sample size as a function of difference to be detected. We apply these methods to clinical trials for amyotrophic lateral sclerosis using data from the placebo groups of 16 trials.ResultsWe find that when attempting to detect the small to moderate effect sizes usually assumed in amyotrophic lateral sclerosis clinical trials, historically controlled trials would require a greater total number of patients than concurrently controlled trials, and only when an effect size is extraordinarily large is a historically controlled trial a reasonable alternative. We also show that utilizing patient level data for the prognostic covariates can reduce the sample size required for a historically controlled trial.ConclusionThis article quantifies when historically controlled trials would not provide any sample size advantage, despite dispensing with a control group.

scholarly journals Validation of a scale assessing the impact of periodontal diseases on patients' quality of life in Bulgaria (pilot research)

2012 ◽  
Vol 23 (5) ◽  
pp. 570-574 ◽  
Author(s):  
Nina Musurlieva ◽  
Maria Stoykova ◽  
Doychin Boyadjiev
Keyword(s):  
Quality Of Life ◽  
Sample Size ◽  
Periodontal Diseases ◽  
Sample Size Calculation ◽  
Discrimination Power ◽  
Related Quality ◽  
Health Related ◽  
Initial Interviews ◽  
The Impact

The aim of the paper is to present the validation of a scale for assessing the impact of periodontal diseases on individuals' quality of life in Bulgaria. A pilot research was made among 30 diagnosed patients with periodontitis visiting the Department of Periodontology, Faculty of Dental Medicine, Medical University of Plovdiv, Bulgaria. The minimum sample size of 30 people was established based on a power analysis for sample size calculation. The mean age of participants was 48.95 ± 11.85 years, being 56.67 ± 9.05 years for males and 43.33 ± 9.05 years for females. Standard interviews were conducted using a specific instrument: self-designed questionnaire and a 5-degree ranked scale, containing initially 11 questions. The interviews were repeated after 3 months with the same patients for retest analysis. The data was statistically processed using SPSS v.13 software. Results received after the initial interviews: Cronbach's coefficient (α=0.882), Spearman-Brown coefficient (r sb=0.998), average inter-item correlation coefficient (R=0.426), difficulty of the questions from 0.173 to 0.757 and discrimination power from 0.405 to 0.809. Results after the second interviews: α=0.883, r sb=0.998, R=0.507, difficulty from 0.287 to 0.757 and discrimination power from 0.524 to 0.809. In two of the questions, a low level of inter-item correlation with the rest of the items was found and they were excluded. The final version of the questionnaire contained 9 questions. The validation proved that the developed scale is sufficiently reliable and will be used in the final research, the first one to use such an instrument for measuring oral health-related quality of life in Bulgaria.

Quality of Split-Mouth Trials in Dentistry: 1998, 2008, and 2018

2020 ◽  
Vol 99 (13) ◽  
pp. 1453-1460
Author(s):  
D. Qin ◽  
F. Hua ◽  
H. He ◽  
S. Liang ◽  
H. Worthington ◽  
...  
Keyword(s):  
Sample Size ◽  
Methodological Quality ◽  
Linear Models ◽  
Sample Size Calculation ◽  
Reporting Quality ◽  
Treatment Groups ◽  
Item Checklist ◽  
The Mean ◽  
Over Time

The objectives of this study were to assess the reporting quality and methodological quality of split-mouth trials (SMTs) published during the past 2 decades and to determine whether there has been an improvement in their quality over time. We searched the MEDLINE database via PubMed to identify SMTs published in 1998, 2008, and 2018. For each included SMT, we used the CONsolidated Standards Of Reporting Trials (CONSORT) 2010 guideline, CONSORT for within-person trial (WPT) extension, and a new 3-item checklist to assess its trial reporting quality (TRQ), WPT-specific reporting quality (WRQ), and SMT-specific methodological quality (SMQ), respectively. Multivariable generalized linear models were performed to analyze the quality of SMTs over time, adjusting for potential confounding factors. A total of 119 SMTs were included. The mean overall score for the TRQ (score range, 0 to 32), WRQ (0 to 15), and SMQ (0 to 3) was 15.77 (SD 4.51), 6.06 (2.06), and 1.12 (0.70), respectively. The primary outcome was clearly defined in only 28 SMTs (23.5%), and only 27 (22.7%) presented a replicable sample size calculation. Only 45 SMTs (37.8%) provided the rationale for using a split-mouth design. The correlation between body sites was reported in only 5 studies (4.2%) for sample size calculation and 4 studies (3.4%) for statistical results. Only 2 studies (1.7%) performed an appropriate sample size calculation, and 46 (38.7%) chose appropriate statistical methods, both accounting for the correlation among treatment groups and the clustering/multiplicity of measurements within an individual. Results of regression analyses suggested that the TRQ of SMTs improved significantly with time ( P < 0.001), while there was no evidence of improvement in WRQ or SMQ. Both the reporting quality and methodological quality of SMTs still have much room for improvement. Concerted efforts are needed to improve the execution and reporting of SMTs.

Sign in / Sign up

Export Citation Format

Share Document