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Difficulty: HardHypothesis Testing and Statistical Power

A team of cardiologists is designing a randomized, double-blind, placebo-controlled trial to evaluate the efficacy of a novel sodium-glucose cotransporter-2 (SGLT2) inhibitor in reducing heart failure exacerbations among patients with preserved ejection fraction. The primary endpoint is the number of hospital admissions for heart failure over a 12-month period. Preliminary sample size calculations using a predetermined significance level (α\alpha) of 0.05 yield a statistical power of 65%. The investigators wish to modify the trial design to achieve a minimum power of 80% to ensure they do not miss a clinically significant benefit.

Which of the following adjustments to the study design would independently increase the statistical power of this trial? (Select all that apply)

  1. Expanding the recruitment target to enroll a larger number of total participantsAnswer
  2. B
    Broadening the inclusion criteria to create a clinically more heterogeneous study population
  3. C
    Decreasing the predetermined significance level (α\alpha) for the primary analysis from 0.05 to 0.01
  4. Employing a rigorous, centralized adjudication process for the primary endpoint to decrease outcome variabilityAnswer
  5. E
    Altering the randomization allocation ratio between the treatment and placebo groups from 1:1 to 2:1 while maintaining the same total sample size

Answer

The trial modifications that independently increase statistical power are expanding the total recruitment target and employing a centralized adjudication process to decrease outcome variability.
Statistical power (1−β1 - \beta) represents the study's ability to detect a true clinical effect. Power is fundamentally driven by the standard error of the mean difference between groups. The correct options identify the two primary ways to reduce the standard error: increasing the sample size (which directly adds more data points) and reducing the variance of the outcome variable. Employing a rigorous, centralized adjudication committee minimizes measurement error, which effectively lowers the outcome variability (variance) and thereby increases statistical power.

Step-by-Step Solution

1
Identify the primary objective described in the clinical vignette
The investigators need to increase the statistical power (1−β1 - \beta) of their trial from 65% to at least 80%
Understanding the goal is necessary to evaluate which study modifications mathematically increase the probability of detecting a true effect
2
Recall the variables that determine statistical power
Statistical power is directly proportional to sample size, alpha (α\alpha) level, and effect size, but inversely proportional to population variance and unbalanced group allocations
These variables dictate the overlap between the null and alternative hypothesis distributions
3
Evaluate the impact of each proposed study design adjustment
Expanding recruitment increases sample size. Centralized adjudication decreases measurement variance. Both of these changes will increase statistical power
This isolates the correct modifications from the distractors that would actually decrease power (such as lowering alpha, increasing population heterogeneity, or shifting away from a 1:1 allocation ratio)

Key Concept

Statistical power (1−β1 - \beta) is the probability of correctly rejecting a false null hypothesis. It is increased by a larger sample size, a larger expected effect size, a higher alpha level, lower population variance, and equal (1:1) group allocation.
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Topics

Hypothesis Testing and Statistical Power

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