Implications of p-values and confidence intervals in patient management decisions revolve around their roles in interpreting the reliability and clinical relevance of study findings to inform shared decision-making.
P-values indicate the probability that observed effects are due to chance, but relying solely on statistical significance (p-values) can be misleading for clinical decisions because they do not convey the magnitude or clinical importance of an effect NICE NG5.
Confidence intervals (CIs), by contrast, provide a range within which the true effect size is likely to lie, offering insight into the precision and potential clinical impact of an intervention, which is crucial for evaluating benefit versus harm in individual patients NICE NG5.
Integrating CIs with measures such as effect size and minimal clinically important difference (MCID) enhances interpretation by highlighting whether observed changes are meaningful to patients, beyond mere statistical significance Fleischmann & Vaughan 2019.
This approach aligns with NICE guidance promoting shared decision-making, where clinicians and patients consider the balance of risks and benefits informed by robust evidence, including the uncertainty expressed by CIs, rather than relying on p-values alone NICE NG5,NICE NG197.
Therefore, in patient management, p-values should not be the sole determinant; instead, confidence intervals combined with clinical context and patient preferences guide safer, more effective, and personalised treatment decisions NICE NG5,NICE NG197 Shakespeare et al. 2001Fleischmann & Vaughan 2019.
Key References
- NG5 - Medicines optimisation: the safe and effective use of medicines to enable the best possible outcomes
- NG197 - Shared decision making
- CG76 - Medicines adherence: involving patients in decisions about prescribed medicines and supporting adherence
- (Shakespeare et al., 2001): Improving interpretation of clinical studies by use of confidence levels, clinical significance curves, and risk-benefit contours.
- (Fleischmann and Vaughan, 2019): Commentary: Statistical significance and clinical significance - A call to consider patient reported outcome measures, effect size, confidence interval and minimal clinically important difference (MCID).