In a clinical trial, a new drug reduces blood pressure by a mean of 2 mmHg (95% CI: 1.8–2.2 mmHg, p < 0.001). A clinician states the result is not clinically meaningful. The discrepancy between the statistical and clinical conclusions is best explained by:
- A Type I error due to multiple comparisons
- B Inadequate power of the study
- C A very large sample size producing a statistically significant but clinically trivial effect ✓
- D Confounding by unmeasured variables
Explanation
With very large sample sizes, even tiny, clinically meaningless differences become statistically significant because the standard error shrinks, narrowing confidence intervals and producing very small p-values. Statistical significance indicates that an effect is unlikely due to chance, not that it is large enough to matter clinically. A 2 mmHg reduction in BP is below the clinically meaningful threshold (typically 5–10 mmHg for antihypertensive therapy). This illustrates why effect sizes and clinical judgment must accompany p-values in interpreting trial results.
Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.
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