2018
DOI: 10.1136/bmjebm-2018-111056
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What is the threshold for a clinical minimally important drug effect?

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Cited by 5 publications
(8 citation statements)
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“…A statistically significant result neither proves that the null hypothesis is false nor that the alternative hypothesis is true ( 8 , 9 , 11 ). Interpreting a statistically significant drug-placebo difference as evidence that drugs work is therefore a logical fallacy ( 12 ). The null hypothesis is always false, as a true null-association between natural variables (i.e., d = 0.0) is nearly impossible due to residual confounding and correlational noise ( 8 , 9 ).…”
Section: Statistical Vs Clinical Significancementioning
confidence: 99%
See 1 more Smart Citation
“…A statistically significant result neither proves that the null hypothesis is false nor that the alternative hypothesis is true ( 8 , 9 , 11 ). Interpreting a statistically significant drug-placebo difference as evidence that drugs work is therefore a logical fallacy ( 12 ). The null hypothesis is always false, as a true null-association between natural variables (i.e., d = 0.0) is nearly impossible due to residual confounding and correlational noise ( 8 , 9 ).…”
Section: Statistical Vs Clinical Significancementioning
confidence: 99%
“…With a total sample size of n = 116,477 as in the most recent meta-analysis ( 1 ), it is therefore not surprising that any given drug-placebo difference, however small it may be, reaches statistical significance. Thus, since statistical significance does not imply clinical significance ( 10 , 12 , 13 ), readers need to consider what the reported mean effect of d = 0.3 practically means.…”
Section: Statistical Vs Clinical Significancementioning
confidence: 99%
“…Similarly, if a drug is found to have only modest efficacy across all patients but notable side effects, then it would be important to know if there are patients (eg, those defined via a specific biomarker) who are benefiters. The latter example corresponds with the pharmacological treatment of major depression, because the average efficacy of antidepressants (ADs) is modest, corresponding to, on average, only about 2 points difference on the Hamilton Depression Rating Scale (HDRS) between AD groups and placebo in short-term randomised controlled trials (RCTs) 1–5. Put differently, according to our most recent estimate, there is about 88% overlap in distribution of depression scores between ADs and placebo at the end of acute treatment 2…”
Section: Introductionmentioning
confidence: 99%
“…The short-term remission rate for antidepressants in real-world patients with mostly moderate depression (28%)19 is just marginally better than that observed in placebo recipients in efficacy trials (26%)11 and it is also just slightly better than that seen in untreated people (23%) 17. Although the remission rate in antidepressant groups is significantly higher than in placebo groups, this small difference is clinically probably not relevant 11 25. Moreover, direct comparisons do not indicate that the placebo response differs significantly from spontaneous improvements seen in untreated people with depression,15 16 but this could also be due to a lack of statistical power.…”
Section: Discussionmentioning
confidence: 91%