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Biostatistics and Epidemiology Flashcards

7 cards from real NBME practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

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  1. The specificity of a diagnostic test is BEST defined as:

    Answer: True negatives / (True negatives + False positives)

    Specificity = TN / (TN + FP); it measures the proportion of truly disease-free individuals who test negative (the true negative rate).

  2. A meta-analysis reports an odds ratio of 2.5 (95% CI: 1.8–3.4) for the association between smoking and lung cancer. Which conclusion is CORRECT?

    Answer: Statistically significant because the 95% CI does not cross 1.0

    When a 95% confidence interval for an odds ratio or relative risk does not include 1.0, the result is statistically significant at the α = 0.05 level.

  3. A case-control study asks patients to recall dietary habits from 10 years ago. The type of bias MOST likely introduced is:

    Answer: Recall bias

    Recall bias occurs when cases systematically remember or report past exposures differently from controls, distorting the measured association.

  4. The standard error of the mean (SEM) is calculated as:

    Answer: Standard deviation divided by the square root of n

    SEM = SD / √n; it estimates how much the sample mean would vary across repeated samples drawn from the same population.

  5. A rapid strep test is compared to throat culture (gold standard). It is positive in 95 of 100 culture-positive patients and negative in 90 of 100 culture-negative patients. What is the sensitivity of the rapid test?

    Answer: 95%

    Sensitivity = TP / (TP + FN) = 95 / 100 = 95%; it captures 95% of truly infected patients.

  6. In a normal distribution, approximately what percentage of values fall within 2 standard deviations of the mean?

    Answer: 95%

    The empirical rule states that ~68% of data falls within 1 SD, ~95% within 2 SD, and ~99.7% within 3 SD of the mean.

  7. Lead-time bias in cancer screening studies results in:

    Answer: Apparent prolongation of survival without actual improvement in the time of death

    Lead-time bias inflates measured survival time because screening detects disease earlier, but if the natural history is unchanged, patients simply know about their disease longer without living longer.