Considerations on Subgroup Analysis in Design and Analysis of Multi-Regional Clinical Trials

2020 ◽  
pp. 93-113
Author(s):  
Hui Quan ◽  
Xuezhou Mao ◽  
Jun Wang ◽  
Ji Zhang
Keyword(s):  
Clinical Trials ◽  
Subgroup Analysis

Subgroup analysis in obstetrics clinical trials

2007 ◽  
Vol 197 (2) ◽  
pp. 119-122 ◽  
Author(s):  
Mark A. Klebanoff
Keyword(s):  
Clinical Trials ◽  
Subgroup Analysis

scholarly journals Rainforest plots for the presentation of patient-subgroup analysis in clinical trials

2017 ◽  
pp. 485-485 ◽  
Author(s):  
Zhongheng Zhang ◽  
Michael Kossmeier ◽  
Ulrich S. Tran ◽  
Martin Voracek ◽  
Haoyang Zhang
Keyword(s):  
Clinical Trials ◽  
Subgroup Analysis ◽  
Patient Subgroup

scholarly journals Guidelines on how to assess the validity of results presented in subgroup analysis of clinical trials

2002 ◽  
Vol 57 (2) ◽  
pp. 83-88 ◽  
Author(s):  
Edson Duarte Moreira ◽  
Ezra Susser
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Randomized Clinical Trial ◽  
Subgroup Analysis ◽  
Observational Studies ◽  
Randomized Clinical Trials ◽  
Usual Method ◽  
Validity Of Results ◽  
Results Of Treatment ◽  
Trial Participants

In observational studies, identification of associations within particular subgroups is the usual method of investigation. As an exploratory method, it is the bread and butter of epidemiological research. Nearly everything that has been learned in epidemiology has been derived from the analysis of subgroups. In a randomized clinical trial, the entire purpose is the comparison of the test subjects and the controls, and when there is particular interest in the results of treatment in a certain section of trial participants, a subgroup analysis is performed. These subgroups are examined to see if they are liable to a greater benefit or risk from treatment. Thus, analyzing patient subsets is a natural part of the process of improving therapeutic knowledge through clinical trials. Nevertheless, the reliability of subgroup analysis can often be poor because of problems of multiplicity and limitations in the numbers of patients studied. The naive interpretation of the results of such examinations is a cause of great confusion in the therapeutic literature. We emphasize the need for readers to be aware that inferences based on comparisons between subgroups in randomized clinical trials should be approached more cautiously than those based on the main comparison. That is, subgroup analysis results derived from a sound clinical trial are not necessarily valid; one must not jump to conclusions and accept the validity of subgroup analysis results without an appropriate judgment.

Subgroup analysis in clinical trials

2004 ◽  
Vol 180 (6) ◽  
pp. 289-291 ◽  
Author(s):  
David I Cook ◽  
Val J Gebski ◽  
Anthony C Keech
Keyword(s):  
Clinical Trials ◽  
Subgroup Analysis

Subgroup analysis in MS trials

2016 ◽  
Vol 23 (1) ◽  
pp. 34-35 ◽  
Author(s):  
Maria Pia Sormani
Keyword(s):  
Clinical Trials ◽  
Treatment Effect ◽  
Subgroup Analysis ◽  
Multiple Testing ◽  
Main Issue ◽  
Future Research ◽  
Specific Subset ◽  
Subgroup Analyses ◽  
Post Hoc ◽  
Interaction Test

Subgroup analysis is often conducted as a post-hoc evaluation of clinical trials. The aim of a subgroup analysis is the evaluation of the treatment effect that was tested in the trial, in a specific subgroups of patients. It can be run both on positive trials (to provide information about patients receiving the highest benefit from the treatment) and on negative trials (to test whether the treatment that had no effect on the overall population can be of any benefit in a specific subset of patients). A subgroup analysis is aimed at generating hypotheses for future research. Subgroup analyses have statistical challenges involving multiple testing and unplanned and low powered analyses; however the main issue, at least in subgroup analysis conducted so far in MS studies, seems to be related to the reporting and interpretation of results. In this viewpoint I will try to show the misleading ways of reporting subgroup analysis in MS trials, along with the correct approach based on an interaction test.

ISSUES RELATED TO SUBGROUP ANALYSIS IN CLINICAL TRIALS

2002 ◽  
Vol 12 (3) ◽  
pp. 347-358 ◽  
Author(s):  
Lu Cui ◽  
H. M. James Hung ◽  
Sue Jane Wang ◽  
Yi Tsong
Keyword(s):  
Clinical Trials ◽  
Subgroup Analysis

scholarly journals Pelargonium Extract EPs 7630 in the Treatment of Human Corona Virus-Associated Acute Respiratory Tract Infections – A Secondary Subgroup-Analysis of an Open-Label, Uncontrolled Clinical Trial

2021 ◽  
Vol 12 ◽  
Author(s):  
Tilman Keck ◽  
Andreas Strobl ◽  
Andreas Weinhaeusel ◽  
Petra Funk ◽  
Martin Michaelis
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Nucleic Acids ◽  
Common Cold ◽  
Subgroup Analysis ◽  
Viral Infections ◽  
Open Label ◽  
Pelargonium Sidoides ◽  
Number Of Patients ◽  
Tract Infections

Background: Experience in treating human coronavirus (HCoV) infections might help to identify effective compounds against novel coronaviruses. We therefore performed a secondary subgroup-analysis of data from an open-label, uncontrolled clinical trial published in 2015 investigating the proanthocyanidin-rich Pelargonium sidoides extract EPs 7630 in patients with the common cold.Methods: 120 patients with common cold and at least 2 out of 10 common cold symptoms received one film-coated 20 mg tablet EPs 7630 thrice daily for 10 days in an uncontrolled, interventional multicentre trial (ISRCTN65790556). At baseline, viral nucleic acids were detected by polymerase chain reaction. Common cold-associated symptoms and treatment satisfaction were evaluated after 5 days and at treatment end. Based on the data of patients with proof of viral nucleic acids, we compared the course of the disease in patients with or without HCoV infection.Results: In 61 patients, viral nucleic acids were detected. Of these, 23 (37.7%) were tested positive for at least one HCoV (HCoV subset) and 38 (62.3%) for other viruses only (non-HCoV subset). Patients of both subsets showed a significant improvement of common cold symptoms already after 5 days of treatment, although the observed change tended to be more pronounced in the HCoV subset. At treatment end, more than 80% of patients of both groups were completely recovered or majorly improved. In both subsets, less than 22% of patients took concomitant paracetamol for antipyresis. The mean number of patients’ days off work or school/college was similar (0.9 ± 2.6 days in HCoV subset vs 1.3 ± 2.8 days in non-HCoV subset). In both groups, most patients were satisfied or very satisfied with EPs 7630 treatment.Conclusion: EPs 7630 treatment outcomes of common cold patients with confirmed HCoV infection were as favourable as in patients with other viral infections. As this trial was conducted before the pandemic, there is currently no evidence from clinical trials for the efficacy of EPs 7630 in patients with SARS-CoV-2 infection. Dedicated non-clinical studies and clinical trials are required to elucidate the potential of EPs 7630 in the early treatment of HCoV infections.

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