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Psych MEQs / SAQsFoundations — biostatistics for psychiatry exams

Psych MEQs / SAQs · Foundations — biostatistics for psychiatry exams

Biostatistics calculations from a psychiatry abstract (MEQ)

FRANZCP/MRCPsych-style MEQ on ARR/NNT, RR vs OR, p-value definition, CI reading, and base-rate dependence of PPV.

20 marks20 min1 min readVerification in progress

Target exams

FRANZCPMRCPsychABPNMD-DNB
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Target exams

FRANZCPMRCPsychABPNMD-DNB
Prompt
Abstract (fictional numbers for exam practice): Double-blind RCT of Drug X versus placebo in adults with moderate major depression. N=200 (100 per arm). Primary dichotomous outcome: response (50% HAM-D reduction) at 8 weeks by ITT. Response: Drug X 52/100, placebo 34/100. Authors headline a '53% relative improvement in response odds' and p=0.01. Secondary: mean HAM-D difference −2.8 (95% CI −4.9 to −0.7). A diagnostic substudy of a new brief screen vs structured interview in the same sample (prevalence of MDD by interview = 100% of enrolees by design — not a screening population) is not reported with community predictive values. (i) Calculate CER, EER, ARR, RRR, RR, and NNT for response; interpret in one sentence. (ii) Explain why the '53% relative improvement in odds' is not the same as RRR and when OR ≈ RR. (iii) Define the p-value for the primary comparison and state what it does not mean. (iv) Interpret the mean difference CI clinically versus statistically. (v) Explain why PPV from this clinic sample cannot be exported unchanged to a 3% prevalence primary-care screen. (20 marks)

Model answer

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(i) Rates and NNT. CER (placebo response) = 34/100 = 0.34. EER = 52/100 = 0.52. Absolute benefit = 0.52 − 0.34 = 0.18. RR = 0.52/0.34 ≈ 1.53. RRR for non-response framing is less natural here; for response, relative increase = 0.18/0.34 ≈ 53% of the control response rate — note this is not "53% of patients improved." NNT = 1/0.18 ≈ 5.6 → about 6 patients treated for 8 weeks for one extra responder.[1][6]

(ii) Odds vs risk. Odds drug = 52/48; odds placebo = 34/66; OR = (52/48)/(34/66) ≈ 2.1, which can be spun as roughly a doubling of odds — different from RR ≈ 1.53 and from a 53% relative risk increase. OR ≈ RR only when the outcome is uncommon; at 34–52% response, OR is not a safe substitute for RR.[2]

(iii) p-value. p = 0.01 means that if H0 of no difference in response proportions (and model assumptions) were true, data this extreme or more would occur about 1% of the time. It is not the probability Drug X does not work, nor proof of clinical importance.[3]

(iv) Mean difference CI. −2.8 points (95% CI −4.9 to −0.7) excludes zero → statistically significant mean benefit; magnitude is modest and may or may not exceed an MCID depending on scale and context — separate statistical from clinical importance; continuous outcomes do not give NNT without dichotomisation.[4]

(v) Base rates. PPV depends on prevalence. A sample of trial enrolees with known MDD is not a screening population; exporting clinic PPV to 3% prevalence primary care without Bayes/recalculation is base-rate neglect and will overstate the chance a positive screen is true disease.[5]

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References6ShowHide
  1. [1]Cook RJ, Sackett DL The number needed to treat: a clinically useful measure of treatment effect BMJ, 1995.PMID 7873954
  2. [2]Bland JM, Altman DG Statistics notes. The odds ratio BMJ, 2000.PMID 10827061
  3. [3]Greenland S, Senn SJ, Rothman KJ, et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations Eur J Epidemiol, 2016.PMID 27209009
  4. [4]Gardner MJ, Altman DG Confidence intervals rather than P values: estimation rather than hypothesis testing Br Med J (Clin Res Ed), 1986.PMID 3082422
  5. [5]Altman DG, Bland JM Diagnostic tests 2: Predictive values BMJ, 1994.PMID 8038641
  6. [6]Laupacis A, Sackett DL, Roberts RS An assessment of clinically useful measures of the consequences of treatment N Engl J Med, 1988.PMID 3374545
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