scholarly journals Subgroup Analysis in Pulmonary Hypertension-specific Therapy Trials: a Systematic Review

2021 ◽  
Author(s):  
H Rodríguez-Ramallo ◽  
N Báez-Gutiérrez ◽  
R Otero Candelera ◽  
S Flores-Moreno ◽  
L Abdel-kader Martín
Keyword(s):  
Systematic Review ◽  
Pulmonary Hypertension ◽  
Subgroup Analysis ◽  
Treatment Decisions ◽  
Poor Quality ◽  
Specific Therapy ◽  
Intervention Effect ◽  
Subgroup Analyses ◽  
Subgroup Effects ◽  
Interaction Test

Abstract Background. Pulmonary hypertension (PH) treatment decisions are driven by randomized controlled trials (RCTs) results. Subgroup analyses are often performed to assess whether the intervention effect will change due to the patient’s characteristics. As subgroup claims may mislead clinician treatment decisions, there is a need for standards of such analyses.Objective. To evaluate the appropriateness and interpretation of subgroup analysis performed in pulmonary hypertension-specific therapy RCTs.Methods. A systematic review of the literature for pulmonary hypertension-specific therapy RCTs published between January 2000 and December 2020 was conducted. Claims of subgroup effects were evaluated with Sun X et al., 2012 criteria.Results. 30 RCTs were included. Evaluated subgroup analyses presented: a high number of subgroup analyses reported, lack of prespecification, and interaction test. The trial protocol was not available for most RCTs; significant differences were found in those articles which published the protocol. Authors reported 13 claims of subgroup effect, with 12 claims meeting 4 or fewer Sun criteria. Conclusion. Subgroup analyses in pulmonary hypertension-specific therapies are of poor quality. The lack of published protocols limited our capability to assess whether the published results correspond to the initially predefined analyses. Most claims of subgroup effect did not meet critical criteria.

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.

Use of docetaxel in low- and high-burden metastatic hormone-sensitive prostate cancer: A systematic review and assessment of subgroup analyses

2021 ◽  
Vol 27 (7) ◽  
pp. 1743-1750
Author(s):  
Manuel David Gil-Sierra ◽  
Emilio Jesus Alegre-del Rey ◽  
Catalina Alarcon de la Lastra-Romero ◽  
Marina Sánchez-Hidalgo
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Clinical Trials ◽  
Metastatic Disease ◽  
Subgroup Analysis ◽  
Randomised Clinical Trial ◽  
Randomised Clinical Trials ◽  
High Burden ◽  
Subgroup Analyses ◽  
Hormone Sensitive

Background Use of docetaxel in low- and high-burden metastatic hormone-sensitive prostate cancer presents considerable controversy. There is literature suggesting lack of benefit for low-volume of metastases. Objective The study aims to develop a systematic review and methodological assessment of subset analysis about use of docetaxel in metastatic hormone-sensitive prostate cancer regarding volume of metastatic disease. Methods A systematic review in the Pubmed® database was conducted up to 25 September 2020. A reference tracking was also developed. Randomised clinical trials with subgroup analysis according volume of metastatic disease for overall survival were selected. Two methodologies were used. One of them considered statistical interaction of subsets ( p(i) < 0.1), pre-specification, biological plausibility and consistency among subset results of similar randomised clinical trials. The second methodology was a two-part validated tool: preliminary questions to discard subset analysis without minimal relevance and a checklist The checklist provides recommendations for applicability of subgroup analysis in clinical practice. Results A total of 31 results were found in systematic reviews in the Pubmed® database. One result was identified in the reference tracking. Of the total of 32 results, four randomised clinical trials were included in the study. About first methodology, statistical interaction among subgroups was obtained in one randomised clinical trial. Subgroup analysis was pre-specified in two randomised clinical trials. Biological plausibility was reasonable. No external consistency among results of subgroup analyses in randomised clinical trials was observed. Preliminary questions of second methodology rejected applicability of subgroup analysis in three randomised clinical trials. A ‘null’ recommendation for applicability of subset results was obtained in the remaining randomised clinical trial. Conclusions Patients with low- and high-burden metastatic hormone-sensitive prostate cancer would benefit from docetaxel therapy. No consistent differences for overall survival were observed in subgroup analyses regarding volume of metastatic disease.

scholarly journals A statistical primer on subgroup analyses

2020 ◽  
Vol 30 (6) ◽  
pp. 839-845 ◽  
Author(s):  
Milan Milojevic ◽  
Aleksandar Nikolic ◽  
Peter Jüni ◽  
Stuart J Head
Keyword(s):  
Patient Outcomes ◽  
Subgroup Analysis ◽  
Clinical Characteristics ◽  
Modern Medicine ◽  
Raising Awareness ◽  
Subgroup Analyses ◽  
Decision Making Processes ◽  
Increasing Demand ◽  
Optimal Approach ◽  
Subgroup Effects

Abstract Resources for clinical research are limited. With increasing demand for patient-centred care, which is growing into an integral component of modern medicine, studying outcomes of patients with specific clinical characteristics is becoming increasingly important. Given the high cost of clinical trials and the time it takes to complete an investigation, it has become compulsory for investigators to assess not only treatment effects between the main randomized groups but also to try to identify clinically relevant subgroups that may particularly benefit from specific treatments. Publications of subgroup analyses turned out to be prevalent, and more importantly, these findings play a significant role in strategic planning and decision-making processes. Therefore, raising awareness among clinicians about the concepts and values of subgroup analysis is an aspect of improving patient outcomes. In this statistical primer, we give a broad introduction to the topic of subgroup analysis in scientific research. We furthermore discuss the concept of subgroup analysis; the motivation for assessing subgroups; the types of subgroup analyses and the paradigm of hypothesis-generating research; the proper statistical methods for the examination of subgroup effects; and the optimal approach for interpretation of results. Finally, this review establishes the comprehensive users’ guide for analysing and reporting subgroup studies on a point-by-point basis, using real-world examples that may help readers to gain experience to pursue their own subgroup analyses or interpret those of others.

Systematic review and meta-analysis of Altruistic and Game-playing Love

2020 ◽  
Author(s):  
Hossein Dabiriyan Tehrani ◽  
Sara Yamini
Keyword(s):  
Systematic Review ◽  
Subgroup Analysis ◽  
Meta Analysis ◽  
Game Playing ◽  
Love Styles ◽  
Collectivistic Culture ◽  
Meta Regression ◽  
Collectivistic Cultures ◽  
The Relationship

This systematic review aimed to find attitudes toward Altruistic and Game-playing love styles across individualistic and collectivistic cultures. Addressing major moderators concerning Altruistic and Game-playing love styles are the secondary objectives of this review. This review included 102 articles comprising samples from 37 countries (N = 41997). The findings of this meta-analysis show that there is a collectivistic and individualistic difference in Game-playing but not in the Altruistic love style. Collectivistic and individualistic cultures, on average, demonstrate the same perception concerning the Altruistic love style, whereas collectivistic culture shows the Game-playing love style more strongly. To explain the role of moderators in key measures, the subgroup analysis and meta-regression show that both Game-playing and Altruistic love styles decline by increasing the length of the relationship. Likewise, having children affects these love styles such that the Altruistic love style is improved, and the Game-playing love style is reduced by the presence of children in families.

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