Clinical Trials

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❘❙❚■ Chapter 18 | Significance Tests and Confidence IntervalsTable 3. Point estimate and 95% CI for the difference in mean weight change from baseline between the activedrug and placebo groups in four hypothetical trials of two weight-reduction drugs.Trial Drug No. of Difference in mean Standard Standard 95% CI P-valuepatients weight change from deviation of error of for differenceper group baseline (kg) between difference differencethe active drug andplacebo groups1 A 40 –6 15 3.4 –12.6 0.6 0.0742 A 400 –6 15 1.1 –8.1 –3.9
Clinical Trials: A Practical Guide ■❚❙❘Table 4. Summary of the key points from the results described in Table 3.Key points from significance test and CIExamplesIn a small study, a large P-value does not mean that the null hypothesis is true – Trials 1 and 3‘absence of evidence is not evidence of absence’A large study has a better chance of detecting a given treatment effect than a small Trials 2 and 4study, and is therefore more powerfulA small study usually produces a CI for the treatment effect that is too wide to allow Trials 1 and 3any useful conclusionA large study usually produces a narrow CI, and therefore a precise estimate of Trials 2 and 4treatment effectThe smaller the P-value, the lower the chance of falsely rejecting the null hypothesis, Trials 2 and 4and the stronger the evidence for rejecting the null hypothesisEven if the P-value shows a statistically significant result, it does not mean that the Trial 4treatment effect is clinically significant. The clinical importance of the estimated effectsshould always be assessedConclusionBased on the assumption of no bias or confounding in an ideal clinical trial, statisticalinference assesses whether an observed treatment difference is real or due to chance.The most common type of inference involves comparing different parameters,such as means and proportions, by performing a hypothesis test and estimating aCI. The former indicates the strength of the evidence against the null hypothesis,while the latter gives us a point estimate of the population difference, togetherwith the range of values within which we are reasonably confident that thetrue population difference lies.Both P-values and CIs for the main outcomes should be reported in an analysisreport. Any statistical inferential results are subject to two types of errors:Type I (false positive) and Type II (false negative). Finally, it should be statedthat a statistically significant difference is not always the same as a clinicallysignificant difference, and both should be considered when interpretingtrial results.References1. Zelen M. Inference. In: Encyclopedia of Biostatistics. Armitage P, Colton T, editors. New York:John Wiley & Sons, 1998:2035–46.2. Altman DG. Practical Statistics for Medical Research. London: Chapman & Hall, 1999.3. Kirkwood B, Sterne J. Essential Medical Statistics, 2nd edition. Oxford: Blackwell Publishing, 2003.195
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❘❙❚■ ContributorsStephen L
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Clinical Trials: A Practical Guide
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■■❚❙❘Chapter 3Protocol De
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■■❚❙❘Chapter 4EndpointsAm
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■■❚❙❘Part IIAlternativeTr
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❘❙❚■ Chapter 10 | Crossover
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■■❚❙❘Part IVSpecial Trial
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■■❚❙❘Chapter 22Intention-
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■■❚❙❘Chapter 23Subgroup A
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■■❚❙❘Chapter 24Regression
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■■❚❙❘Chapter 25Adjustment
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■■❚❙❘Chapter 32Overview o
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■■❚❙❘Chapter 33Trial Prof
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■■❚❙❘GlossaryGlossary453
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■■❚❙❘IndexIndex467
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Clinical Trials

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