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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
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A Utilitarian Perspective on Risk Quantification for Clinical Significance in Binary Outcomes
1Pukyong National University, Busan, Korea.
Summary
This study introduces risk difference (RD) as a preferred effect size (ES) for medical research, enhancing clarity on clinical intervention impact and patient benefits. It advocates for reporting RDs with baseline risks for transparent, patient-centered decision-making.
Area of Science:
- Medical Statistics
- Clinical Research Methodology
- Evidence-Based Medicine
Background:
- Null hypothesis significance testing (NHST) is being supplemented by estimation statistics like effect sizes (ESs) and confidence intervals (CIs).
- Current methods for binary outcomes may not fully convey clinical significance or patient impact.
- A need exists for improved statistical measures in medical research to enhance applicability to patient care.
Purpose of the Study:
- To evaluate the expression of ESs and CIs for binary outcomes in medical research.
- To propose a utilitarian framework for assessing clinical significance using risk difference (RD).
- To compare the performance of RD against other measures (RR, OR, Cohen's h) in individual studies and meta-analyses.
Main Methods:
- Proposed a utilitarian framework emphasizing beneficiaries and impact level.
- Introduced minimal clinically important risk difference (MCIRD) based on event magnitude (EM).
- Compared statistical power of RD versus RR, OR, and Cohen's h in individual studies; assessed visual information conveyance in meta-analyses.
Main Results:
- Risk difference (RD) maintains statistical power comparable to other measures in individual studies.
- RDs provide clarity on clinical intervention impact without compromising statistical integrity.
- Meta-analyses using RDs enhance transparency, uncover heterogeneity, and address misaligned assumptions.
Conclusions:
- Adopting RD as a preferred ES, reported with baseline risks (BRs), fosters a transparent, patient-focused research ethos.
- This approach quantifies clinical effectiveness, facilitating research application to patient care and shared decision-making.
- Recommends standardized presentation of RDs and BRs for accurate representation of treatment effects.
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