PEBC Part I (MCQ) · Competency 2 Knowledge and Expertise (about 11%)

Evidence-based Practice & Drug Information

Knowledge and Expertise items test critical appraisal and biostatistics: study designs and bias, NNT and risk measures, confidence intervals and p-values, diagnostic test statistics, meta-analysis, pharmacoeconomics and answering drug information requests.

2 Knowledge & Expertise2 min read6 sections

Checked against the Guyatt G et al. Users' Guides to the Medical Literature, 3rd ed. (2015); Straus SE et al. Evidence-Based Medicine, 5th ed. (2018); Cochrane Handbook v6.5 (2024); CONSORT 2010 and non-inferiority extension (2012); CADTH economic evaluation guidelines (2017); checked 13 Oct 2026. Not affiliated with or endorsed by The Pharmacy Examining Board of Canada (PEBC).

Must-know for the exam

ARR = control event rate - treatment event rate; NNT = 1/ARR, always with a time frame.
RRR = 1 - RR; relative measures overstate benefit for low-risk patients.
Apply a constant RRR to the patient's own baseline risk to get an individual NNT.
A 95% CI for a ratio that includes 1.0 means the result is not significant at p < 0.05.
Type I error: false positive (alpha); type II error: false negative, more likely with low power.
Case-control studies suit rare outcomes and report odds ratios; cohorts report relative risks.
Intention-to-treat keeps patients in their randomised groups; report per-protocol too in non-inferiority trials.
Sensitivity and specificity are fixed; predictive values change with prevalence.
I-squared above about 75% indicates considerable heterogeneity.
Cost-utility analysis uses QALYs; ICER = difference in cost / difference in effect.

On this page · 6 sections

Traps that cost marks

Using the relative risk reduction instead of the absolute risk reduction when calculating NNT.
Reporting the relative risk (70%) or the absolute difference (1.5%) as the relative risk reduction.
Taking the reciprocal of the event rate in one arm instead of the difference between arms.
Judging significance from the point estimate rather than from whether the interval crosses the line of no effect.
Mixing up type I (false positive) and type II (false negative) errors.
Treating 'no significant difference' as proof that two treatments are the same.
Dividing exposure proportions instead of exposure odds in a case-control design.
Choosing a cohort study for a rare outcome, which needs impractically large samples.

How this is tested on Part I

About 11% of Part I. Items give trial or study data and ask for a calculation or the correct interpretation, plus questions on bias, design choice and drug information practice.

Study design and bias

Allocation concealment prevents selection bias; blinding protects subjective outcomes.

Observational associations can reflect confounding (healthy-user effect, confounding by indication).

Post hoc subgroups in a negative trial are hypothesis-generating.

Composite outcomes: check which component drives the result.

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Exam-style questions

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Educational practice material for exam preparation only. Not medical advice and not a substitute for current product monographs, clinical guidelines or professional judgement. Questions have not yet been reviewed by a licensed pharmacist.