Objective:The fragility index is a clinically interpretable metric increasingly used to interpret the robustness of clinical trials results that is generally not incorporated in sample size calculation and applied post-hoc. In this manuscript, we propose to base the sample size calculation on the fragility index in a way that supplements the classical prefixed alpha and power cutoffs and we provide a dedicated R software package for the design and analysis tools.Study design and setting:This approach follows from a novel hypothesis testing framework that is based on the fragility index and builds on the classical testing approach. As case studies, we re-analyse the design of two important trials in cardiovascular medicine, the FAME and FAMO...
More than one million peri-operative patients die each year. Thus, small improvements in peri-opera...
Importance In science and medical research, extreme and dichotomous conclusions may be drawn base...
Background: The Fragility Index (FI) and Reverse Fragility Index are powerful tools to supplement th...
Statistical significance is widely used to evaluate research findings but has limitations around rep...
This article proposes the Percent Fragility Index (PFI) as an improved measure of statistical fragil...
AbstractObjectivesA P-value <0.05 is one metric used to evaluate the results of a randomized control...
Rationale Aims and Objectives: The fragility index (FI) and fragility quotient (FQ) are increasingly...
Data suggest inadequacy of common statistical techniques for reporting outcomes in clinical trials. ...
Aims: Guidelines for the management of chronic heart failure (CHF) cite the results of randomized co...
Abstract Background Clinical trials routinely have pa...
Background: RCTs (randomized controlled trials) are the preferred source of evidence to support prof...
Background: RCTs (randomized controlled trials) are the preferred source of evidence to support prof...
Objectives: The Fragility Index, which represents the number of patients responsible for a statistic...
OBJECTIVES:To perform fragility index (FI) analysis on the evidence that forms the basis of the guid...
The fragility index (FI), the number of events the statistical significance a result depends on, and...
More than one million peri-operative patients die each year. Thus, small improvements in peri-opera...
Importance In science and medical research, extreme and dichotomous conclusions may be drawn base...
Background: The Fragility Index (FI) and Reverse Fragility Index are powerful tools to supplement th...
Statistical significance is widely used to evaluate research findings but has limitations around rep...
This article proposes the Percent Fragility Index (PFI) as an improved measure of statistical fragil...
AbstractObjectivesA P-value <0.05 is one metric used to evaluate the results of a randomized control...
Rationale Aims and Objectives: The fragility index (FI) and fragility quotient (FQ) are increasingly...
Data suggest inadequacy of common statistical techniques for reporting outcomes in clinical trials. ...
Aims: Guidelines for the management of chronic heart failure (CHF) cite the results of randomized co...
Abstract Background Clinical trials routinely have pa...
Background: RCTs (randomized controlled trials) are the preferred source of evidence to support prof...
Background: RCTs (randomized controlled trials) are the preferred source of evidence to support prof...
Objectives: The Fragility Index, which represents the number of patients responsible for a statistic...
OBJECTIVES:To perform fragility index (FI) analysis on the evidence that forms the basis of the guid...
The fragility index (FI), the number of events the statistical significance a result depends on, and...
More than one million peri-operative patients die each year. Thus, small improvements in peri-opera...
Importance In science and medical research, extreme and dichotomous conclusions may be drawn base...
Background: The Fragility Index (FI) and Reverse Fragility Index are powerful tools to supplement th...