PLAB 1 Medical Ethics, Consent & Evidence-Based Medicine 2 — Questions and Answers
Question 1: A clinical trial reports that a new drug reduces the relative risk of myocardial infarction by 50% compared to placebo. The absolute event rates are 2% (treatment) and 4% (control). What is the Number Needed to Treat (NNT)?
- 2
- 50 (Correct answer)
- 100
- 25
Correct answer: 50
NNT = 1 / Absolute Risk Reduction (ARR). ARR = 4% - 2% = 2% = 0.02. NNT = 1/0.02 = 50. The NNT of 50 means you need to treat 50 patients to prevent one MI. While the relative risk reduction (50%) sounds impressive, the NNT provides more clinically meaningful information.
Question 2: What is a 'double-blind randomised controlled trial' (RCT) and why is it considered the gold standard for establishing therapeutic efficacy?
- A trial where two different treatments are compared without any controls
- A trial where neither participants nor investigators know which group receives treatment or placebo, eliminating allocation bias and expectation bias — the best evidence for causality (Correct answer)
- A trial examining two different outcomes simultaneously
- A trial conducted across two different hospital sites
Correct answer: A trial where neither participants nor investigators know which group receives treatment or placebo, eliminating allocation bias and expectation bias — the best evidence for causality
A double-blind RCT: random allocation prevents selection bias and balances confounders; blinding participants prevents placebo effect; blinding investigators prevents observer bias. The combination of randomisation and blinding provides the most robust evidence for causality in therapeutic research.
Question 3: What is 'sensitivity' of a diagnostic test?
- The proportion of people without disease who test negative (true negative rate)
- The proportion of people with the disease who test positive (true positive rate) — a sensitive test rarely misses disease (Correct answer)
- The probability that a positive test correctly identifies disease
- The proportion of all positive tests that are true positives
Correct answer: The proportion of people with the disease who test positive (true positive rate) — a sensitive test rarely misses disease
Sensitivity = True Positives / (True Positives + False Negatives). A highly sensitive test has a low false-negative rate — it rarely misses cases of the disease. Mnemonic: SnNout — a Sensitive test, when Negative, rules OUT disease. Useful for screening tests.
Question 4: What is 'specificity' of a diagnostic test?
- The proportion of diseased patients who test positive
- The proportion of disease-free individuals who test negative (true negative rate) — a specific test rarely gives false positives (Correct answer)
- The accuracy of the test across all populations
- The proportion of all negative tests that are true negatives
Correct answer: The proportion of disease-free individuals who test negative (true negative rate) — a specific test rarely gives false positives
Specificity = True Negatives / (True Negatives + False Positives). A highly specific test rarely gives a positive result in people without disease. Mnemonic: SpPin — a Specific test, when Positive, rules IN disease. Useful for confirmatory tests.
Question 5: What does 'intention-to-treat' (ITT) analysis mean in clinical trials?
- Analysis of only participants who completed the full treatment protocol
- Analysis that includes all participants as originally allocated, regardless of whether they completed or received the allocated treatment — preserving the integrity of randomisation (Correct answer)
- Analysis focused on the primary intention of the intervention
- Analysis performed before unblinding the trial
Correct answer: Analysis that includes all participants as originally allocated, regardless of whether they completed or received the allocated treatment — preserving the integrity of randomisation
ITT analysis maintains all participants in the groups to which they were originally randomised, regardless of non-compliance, withdrawal, or crossover. This preserves the prognostic balance of randomisation and gives a real-world estimate of treatment effect. Per-protocol analysis (completers only) may overestimate treatment benefit.
Question 6: What does a 'confidence interval' (CI) tell you in clinical research?
- The range within which a test value is considered normal
- The range within which the true population value is likely to lie with a specified probability (e.g., 95% CI) — a wide CI indicates less precision (Correct answer)
- The statistical significance of a result
- The range of values that guarantee clinical significance
Correct answer: The range within which the true population value is likely to lie with a specified probability (e.g., 95% CI) — a wide CI indicates less precision
A 95% CI means that if the study were repeated 100 times, 95 of the resulting CIs would contain the true population value. A wide CI reflects high uncertainty (often from small sample size); a narrow CI indicates precision. If a CI for a risk ratio includes 1.0, the result is not statistically significant at the 5% level.
PLAB 1 Medical Ethics, Consent & Evidence-Based Medicine 2
A clinical trial reports that a new drug reduces the relative risk of myocardial infarction by 50% compared to placebo.
The absolute event rates are 2% (treatment) and 4% (control).
What is the Number Needed to Treat (NNT)?