Assessing assumptions for statistical analyses in randomised clinical trials

2019 ◽  
Vol 24 (5) ◽  
pp. 185-189 ◽  
Author(s):  
Emil Eik Nielsen ◽  
Anders Kehlet Nørskov ◽  
Theis Lange ◽  
Lehana Thabane ◽  
Jørn Wetterslev ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Statistical Methods ◽  
Statistical Power ◽  
Current Practice ◽  
Statistical Analyses ◽  
Randomised Clinical Trials ◽  
Validity Of Results ◽  
Medical Journals ◽  
Statistical Assumptions

In order to ensure the validity of results of randomised clinical trials and under some circumstances to optimise statistical power, most statistical methods require validation of underlying statistical assumptions. The present paper describes how trialists in major medical journals report tests of underlying statistical assumptions when analysing results of randomised clinical trials. We also consider possible solutions how to improve current practice by adequate reporting of tests of underlying statistical assumptions. We conclude that there is a need to reach consensus on which underlying assumptions should be assessed, how these underlying assumptions should be assessed and what should be done if the underlying assumptions are violated.

scholarly journals SYSTEMATIC REVIEW PROTOCOL: The reporting standards of Randomised Clinical Trials in leading medical journals between 2019-2020

2020 ◽  
Author(s):  
Mairead McErlean ◽  
Jack Samways ◽  
Peter Godolphin ◽  
Yang Chen
Keyword(s):  
Systematic Review ◽  
Clinical Trials ◽  
Medical Specialty ◽  
Randomised Clinical Trials ◽  
Reporting Standards ◽  
Systematic Review Protocol ◽  
Quality Of Reporting ◽  
Medical Journals ◽  
Review Protocol

This is a systematic review protocol which outlines the basis and methodology for our intended review which at the time of writing is in the study screening phase. Our aim is to answer the fundamental questions:To systematically identify RCTs published in the four leading medical journals between January 1st 2019 to May 31st 2020.To assess the quality of reporting of such RCTs using the CONSORT 2010 statement.To identify any association with medical specialty or size or type of RCT and the rate of adherence to the CONSORT 2010 statement.

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.

Assessment of assumptions of statistical analysis methods in randomised clinical trials: the what and how

2020 ◽  
pp. bmjebm-2019-111268 ◽  
Author(s):  
Anders Kehlet Nørskov ◽  
Theis Lange ◽  
Emil Eik Nielsen ◽  
Christian Gluud ◽  
Per Winkel ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Logistic Regression ◽  
Linear Regression ◽  
Cox Regression ◽  
Randomised Clinical Trial ◽  
Randomised Clinical Trials ◽  
Consensus Process ◽  
Statistical Assumptions ◽  
Clinical Trial Results ◽  
Research Centres

When analysing and presenting results of randomised clinical trials, trialists rarely report if or how underlying statistical assumptions were validated. To avoid data-driven biased trial results, it should be common practice to prospectively describe the assessments of underlying assumptions. In existing literature, there is no consensus on how trialists should assess and report underlying assumptions for the analyses of randomised clinical trials. With this study, we developed suggestions on how to test and validate underlying assumptions behind logistic regression, linear regression, and Cox regression when analysing results of randomised clinical trials.Two investigators compiled an initial draftbased on a review of the literature. Experienced statisticians and trialists from eight different research centres and trial units then participated in a anonymised consensus process, where we reached agreement on the suggestions presented in this paper.This paper provides detailed suggestions on 1) which underlying statistical assumptions behind logistic regression, multiple linear regression and Cox regression each should be assessed; 2) how these underlying assumptions may be assessed; and 3) what to do if these assumptions are violated.We believe that the validity of randomised clinical trial results will increase if our recommendations for assessing and dealing with violations of the underlying statistical assumptions are followed.

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