A researcher is designing a randomized controlled trial to evaluate the efficacy of a new antihypertensive drug in Indian adults. To detect a clinically meaningful difference of 5 mmHg in systolic blood pressure between the intervention and control groups with 80% power and a two-tailed alpha of 0.05, which investigation/calculation is the most appropriate FIRST step?

Explanation

## Sample Size Calculation in RCT Design **Key Point:** Sample size calculation is the foundational step in RCT planning—it must precede recruitment and randomization. It ensures the trial is adequately powered to detect the hypothesized effect. ### Why Sample Size Calculation is Essential The formula `n = 2[(Z_α + Z_β)² × σ²] / d²` incorporates: - **Z_α** = critical value for Type I error (0.05 two-tailed = 1.96) - **Z_β** = critical value for Type II error (80% power = 0.84) - **σ²** = variance in the outcome (systolic BP variability) - **d** = clinically meaningful difference (5 mmHg) **High-Yield:** Without adequate sample size, the trial risks: - Type II error (failure to detect a true effect) - Underpowered conclusions - Wasted resources ### Logical Sequence in RCT Design | Step | Timing | Purpose | |------|--------|----------| | Sample size calculation | **Before** recruitment | Determine how many participants needed | | Randomization | During recruitment | Allocate participants to arms | | Blinding & outcome assessment | During follow-up | Reduce bias | | Analysis (ITT, per-protocol) | After data collection | Evaluate efficacy | **Clinical Pearl:** The investigator must calculate sample size *a priori* (before enrolling a single participant). Post-hoc power calculations are not valid and suggest poor planning. **Mnemonic:** **PARD** — **P**lan (sample size) → **A**llocate (randomize) → **R**un (collect data) → **D**erive (analyze).