In clinical research, statistically significant study outcomes are frequently regarded as clinically significant. Clinical significance represents the study’s influence on clinical practice, whereas statistical significance demonstrates the study’s trustworthiness. According to Ranganathan et. al, (2015), the “clinical significance” of a finding in clinical practice is determined by its consequences for current practice, with treatment effect size being one of the most significant variables driving treatment decisions. Statistical significance is heavily influenced by the sample size of a study; with large sample sizes, even minor treatment effects (which are clinically insignificant) can appear statistically significant; as a result, the reader must carefully consider whether this “significance” is clinically meaningful.
advanced pancreatic cancer
Overall survival was compared in 569 patients with advanced pancreatic cancer who were randomly assigned to receive erlotinib with gemcitabine vs gemcitabine alone, according to a research published in the Journal of Clinical Oncology. The erlotinib plus gemcitabine arm had a “significantly” longer median survival (6.24 months vs. 5.91 months, P = 0.038). The P = 0.038 indicates that there is only a 3.8 percent probability that the observed difference between the groups happened by chance (less than the conventional cut-off of 5%), making it statistically significant. In this case, the “treatment effect” or difference in median survival between 6.24 and 5.91 months – a mere 10 days, which most oncologists would agree is a clinically irrelevant “improvement” in outcomes, especially when considering the added toxicity and costs associated with the combination – is the clinical relevance of this “positive” study.
Statistical significance must always be established before clinical significance can be assessed in evidence-based research. Clinical significance, on the other hand, is generally a subjective assessment that cannot be determined by a single experience test. By ensuring that the result is statistically significant, I may leverage clinical significance to support good results in my project outcome. This is because the vast majority of statistically significant discoveries have therapeutic implications.
Ranganathan, P., Pramesh, C. S., & Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in clinical research, 6(3), 169–170. https://doi.org/10.4103/2229-3485.159943
t Sapio 1 postsRe: Topic 8 DQ 2
To successfully implement evidence-based practice, it is important to understand and interpret research. In this regard, it is important to understand the difference between statistical significance and clinical significance. Statistical significance refers to when a relationship between variable is accurate and not random or caused by luck. It is used to determine the reliability of findings. In this regard, statistical significance as a parameter in evidence-based practice shows the extent or the likelihood that finding from research is true and does not occur by a chance (Heavey, 2015).
Clinical significance is essentially a subjective interpretation of research findings as meaningful for patient under care, and therefore likely to influence the behaviour of healthcare provider (Heavey, 2015). A clinically significant result occurs when medical experts believe that the finding is considerable enough to be medically crucial and hence be applied as a guide in provision of care to patients.
In evidence-based research practice, statistical significance must always be determined before determination of clinical significance. However, clinical significance is usually a subjective evaluation and cannot be established by a single experiential test. I can use clinical significance to support positive outcomes in my project outcome by ensuring that the result is statistically significant. This is because majority of statistically significant findings normally have clinical significance.
Heavey, E.(2015). Differentiating statistical significance and clinical significance. American Nurse Today