Table 2.

Summary of primary signal detection algorithms adopted in this study.

Algorithm	Publicity	Continuity correction	Standard for generating signals
ROR	$ROR=\frac{a/b}{c/d}$	+0.5 to all cells if any cell = 0	Lower 95% CI > 1, N ≥ 3
PRR	$PRR=\frac{\text{a}/(\text{a}+\text{b})}{c/(c+d)}$	+0.5 to all cells if any cell = 0	χ² ≥ 4, PRR ≥ 2, N ≥ 3
	χ² = [(ad-bc)^2](a+b+c+d)/[(a+b)(c+d)]
MGPS	$EBGM=\frac{\text{a}(\text{a}+\text{b}+\text{c}+\text{d})}{(a+b)(a+c)}$ 95% CI = eln(EBGM) ± 1.96(1/a+1/b+1/c+1/d) ^ 0.5	Empirical Bayesian shrinkage (no artificial correction needed)	EBGM05 > 2
BCPNN	$IC={\log }_2\frac{a(a+b+c+d)}{(a+b)(a+c)}$ 95% CI = E (IC) ± 2V (IC)^0.5	Empirical Bayesian shrinkage (no artificial correction needed)	IC025 > 0, N > 0

CI, confidence interval; EBGM, Empirical Bayes Geometric Mean; EBGM05, the lower 5th percentile of EBGM; IC, Information Component; IC025, the lower 5th percentile of IC; N, number of reports. A continuity correction of 0.5 was applied to zero - cell cases for frequentist algorithms (ROR and PRR). For Bayesian algorithms (MGPS and BCPNN), shrinkage estimation inherently stabilises variance without cell - wise correction.