Biostatistics Practice Questions

Q: A 60-year-old man presents with a chronic cough and is found to have a lung lesion on chest X-ray. What is the significance of high sensitivity in a diagnostic test for lung cancer?

It correctly identifies those with the disease. ***It correctly identifies those with the disease*** - A test with **high sensitivity** is good at ruling out disease when the result is negative because it has a low chance of missing true cases. - In lung cancer screening, high sensitivity helps ensure that individuals who actually have lung cancer are **identified**, reducing false negatives. *It incorrectly identifies those without the disease* - This statement describes a test with **low specificity**, where many healthy individuals are misidentified as having the disease (many false positives). - A high sensitivity test focuses on identifying true positives, not on incorrectly identifying healthy individuals. *It indicates the proportion of false negatives among all actual positives.* - The proportion of **false negatives among all actual positives** is the complement of sensitivity (1 - sensitivity). - High sensitivity implies a **low false-negative rate**, meaning few true cases are missed. *It indicates the proportion of true positives among all positive results.* - This describes **positive predictive value (PPV)**, which is the probability that a positive test result is truly positive. - While related to test utility, PPV is influenced by disease prevalence, whereas sensitivity is an intrinsic property of the test.

Q: In a community-based intervention, the incidence of a disease is found to decrease after vaccination. What study design is most appropriate to confirm vaccine efficacy?

Randomized controlled trial. ***Randomized controlled trial*** - A **randomized controlled trial (RCT)** is the most appropriate study design to confirm vaccine efficacy because it allows for a robust comparison between a vaccinated group and a control group (placebo or no intervention) by **randomly assigning participants** to each. - This design minimizes bias and allows researchers to establish a direct **cause-and-effect relationship** between the vaccine and the prevention of the disease by controlling for confounding factors. *Cohort study* - A **cohort study** observes groups over time, but participants are not randomized to receive the intervention (vaccine), which can introduce **selection bias** if those who choose to be vaccinated differ from those who do not. - While useful for studying prognosis or the effectiveness of interventions in real-world settings, it is less ideal for definitively establishing efficacy compared to an RCT due to the lack of **randomized assignment**. *Case-control study* - A **case-control study** compares individuals with a disease (cases) to those without the disease (controls) and looks back retrospectively for exposure to a risk factor (e.g., lack of vaccination). - This design is prone to **recall bias** and is suitable for rare outcomes, but it cannot directly measure vaccine efficacy or incidence in the same way an RCT can. *Cross-sectional study* - A **cross-sectional study** assesses exposure and outcome simultaneously at a single point in time, providing a snapshot of prevalence. - This design cannot establish temporality (which came first, exposure or outcome) and is therefore unsuitable for confirming vaccine efficacy or a **cause-and-effect relationship**.

Q: In a clinical study assessing the impact of lifestyle changes on hypertension, which outcome measure would be the most appropriate to evaluate effectiveness?

Blood pressure measurement. ***Blood pressure measurement*** - The primary definition of **hypertension** is elevated blood pressure [4]. Therefore, changes in blood pressure are direct and **objective measures** of the intervention's success [2]. - **Systolic and diastolic blood pressure** readings directly reflect the disease state and its improvement or worsening [1]. *Patient self-reported wellness* - While important for overall patient experience, **wellness is subjective** and not a direct, quantifiable measure of hypertension control. - It can be influenced by various factors unrelated to blood pressure and may not accurately reflect the physiological changes. *Frequency of exercise* - **Frequency of exercise** is an **intervention component**, not an outcome measure of the disease itself. - Increased exercise may lead to lower blood pressure, but the exercise frequency itself doesn't quantify the **effectiveness of reducing hypertension**. *Dietary intake logs* - Similar to exercise frequency, **dietary intake logs** assess adherence to the intervention, not the direct outcome on the disease. - While diet significantly impacts hypertension, the logs serve as a measure of **compliance with the lifestyle change**, not the physiological response of blood pressure [3].

Q: A randomized controlled trial of antihypertensives shows a p-value of 0.04 for the difference in blood pressure reduction. What is the most accurate interpretation?

4% chance of this or more extreme result if null true. ***4% chance of this or more extreme result if null true*** - A **p-value of 0.04** signifies that if the **null hypothesis** (no true difference between treatments) were true, there would be a **4% probability** of observing results as extreme as, or more extreme than, those obtained in the study. - This value is often compared to a predetermined **significance level (alpha)**, typically 0.05. Since 0.04 < 0.05, the result is considered statistically significant, leading to the rejection of the null hypothesis. *4% chance that the null hypothesis is true* - This statement incorrectly interprets a p-value as the **probability of the null hypothesis being true**. A p-value is the probability of observing the data, or more extreme data, given that the null hypothesis is true, not the probability of the null hypothesis itself. - The p-value does not provide the **prior probability** or the **posterior probability** of the null hypothesis being true. *96% chance that the alternative hypothesis is true* - This is an incorrect interpretation; a p-value does not indicate the **probability of the alternative hypothesis being true**. It is a measure related to the evidence against the null hypothesis, assuming the null is true. - The complement of the p-value (1 - p) does not represent the probability of the alternative hypothesis or the **power of the study**. *4% chance that the difference is due to random chance* - This interpretation is close but not entirely accurate; the p-value represents the probability of observing the data (or more extreme data) by **random chance alone** *if the null hypothesis were true*. - It does not state that the observed difference *is* due to random chance, but rather quantifies how likely such a difference is under the assumption of **no true effect**.

Q: In a study of 100 patients, the standard deviation of their blood pressure measurements is found to be 10 mmHg. What is the standard error of the mean?

1. ***Correct Option: 1*** - The **standard error of the mean (SEM)** is calculated by dividing the **standard deviation (SD)** by the square root of the **sample size (n)**. - Formula: SEM = SD / √n - Given an SD of **10 mmHg** and a sample size of **100**, SEM = 10 / √100 = 10 / 10 = **1 mmHg**. *Incorrect Option: 10* - This value represents the **standard deviation** of the sample, not the **standard error of the mean**. - The standard error accounts for the variability of sample means around the true population mean, which is always smaller than the standard deviation for n > 1. *Incorrect Option: 0.1* - This value would result if the standard deviation was 1 and the sample size was 100, or if the standard deviation was 10 and the sample size was 10,000. - It does not correctly reflect the given data of **SD = 10** and **n = 100**. *Incorrect Option: 2* - This value would result if the standard deviation was 20 and the sample size was 100, or if the standard deviation was 10 and the sample size was 25. - It does not align with the provided **standard deviation of 10** and a **sample size of 100**.

Q: During a health survey, data was collected to calculate the prevalence of hypertension in a population. Which statistical measure is used to describe the central tendency of systolic blood pressure readings in this survey?

Mean. ***Mean*** - The **mean** is the most common measure of central tendency for **continuously distributed data** like systolic blood pressure readings. - It uses all values in the dataset to calculate the average, providing a comprehensive representation of the central point. *Median* - The median represents the **middle value** in an ordered dataset and is more appropriate for **skewed distributions** or when outliers might disproportionately affect the mean. - While it describes central tendency, it does not use all data points in its calculation and is less sensitive to extreme values, which isn't the primary goal when describing the average blood pressure in a general population. *Mode* - The mode identifies the **most frequently occurring value** in a dataset and is primarily useful for categorical or discrete data. - For continuous data like blood pressure, the mode may not be unique or meaningful since exact repeated values are less common. *Range* - The range indicates the **spread or variability** of the data, calculated as the difference between the maximum and minimum values. - It is a measure of dispersion, not a measure of central tendency.

Q: Which observational study design is most appropriate for analyzing the long-term effects of an exposure or treatment over a specified timeline?

Cohort Study. ***Cohort Study*** - A **cohort study** tracks a group of individuals (cohort) who share a common characteristic or exposure over a period, making it ideal for observing **long-term effects** and outcomes. - Researchers follow participants forward in time to see who develops the outcome of interest, providing strong evidence for **causality** in observational settings. *Cross-sectional study* - A **cross-sectional study** assesses exposure and outcome simultaneously at a single point in time, failing to establish temporality or long-term effects. - This design is suitable for determining **prevalence** but not for analyzing changes over time or causal relationships. *Randomized Control Trials* - **Randomized controlled trials (RCTs)** are interventional studies where participants are randomly assigned to treatment or control groups, providing the strongest evidence for **causality** in the short to medium term. - While excellent for assessing treatment efficacy, RCTs are often impractical or unethical for very long-term follow-up due to cost, logistical challenges, and participant retention issues. *Interventional Studies* - **Interventional studies** involve researchers actively manipulating an intervention (e.g., a treatment) and observing its effects. - This broad category includes RCTs, but simply being an "interventional study" does not inherently make it the most appropriate for analyzing **long-term effects** over an extended timeline, which is better suited for the observational follow-up of a cohort study.

Q: Which type of study determines the odds ratio?

Case control. ***Case control*** - **Case-control studies** compare individuals with a disease (cases) to individuals without the disease (controls) and look back in time to identify previous exposures. - The **odds ratio** is the primary measure of association used in case-control studies, quantifying the odds of exposure among cases versus controls. *Cohort* - **Cohort studies** follow groups of individuals over time, some exposed to a risk factor and some not, to determine the incidence of a disease. - They typically determine **relative risk**, which is the ratio of incidence rates in exposed versus unexposed groups. *Cross sectional* - **Cross-sectional studies** assess the prevalence of disease and exposure at a single point in time. - They primarily measure **prevalence** and can be used to calculate a **prevalence odds ratio**, but they do not establish temporality between exposure and outcome. *RCT* - **Randomized controlled trials (RCTs)** are interventional studies where participants are randomly assigned to an intervention or control group to determine the effectiveness of a treatment or exposure. - The main measure of effect in RCTs is often the **relative risk reduction**, **absolute risk reduction**, or **number needed to treat**, rather than the odds ratio for observational exposure.

Q: The ability of a diagnostic test to correctly identify individuals who have the disease (detect disease when present) is called-

Sensitivity (True Positive Rate). ***Positive predictive value*** - It refers to the probability that individuals with a positive test result actually have the disease, indicating the test's ability to correctly diagnose the condition [1]. - A high **positive predictive value** means the test is effective in diagnosing the disease among those who test positive. *Sensitivity* - Sensitivity measures the proportion of actual positives correctly identified by the test, but does not directly indicate diagnostic power. - A test can be sensitive but still have a low positive predictive value if the prevalence of the disease is low. *Negative predictive value* - Negative predictive value indicates the probability that individuals with a negative test result truly do not have the disease, thus not reflecting the test's diagnostic power [1]. - It is more concerned with the test's ability to rule out a disease rather than to confirm it. *Specificity* - Specificity measures the proportion of actual negatives that are correctly identified, which is not concerned with the correct diagnosis of the disease itself [1]. - A test can have high specificity but not be useful for diagnosing if it lacks positive predictive value. **References:** [1] Cross SS. Underwood's Pathology: A Clinical Approach. 6th ed. (Basic Pathology) introduces the student to key general principles of pathology, both as a medical science and as a clinical activity with a vital role in patient care. Part 2 (Disease Mechanisms) provides fundamental knowledge about the cellular and molecular processes involved in diseases, providing the rationale for their treatment. Part 3 (Systematic Pathology) deals in detail with specific diseases, with emphasis on the clinically important aspects., pp. 253-254.

Q: In a screening test for diabetes mellitus (DM) conducted on a population of 1000, the screening test identified 90 individuals as positive. When the gold standard test was performed on the entire population, it confirmed that 100 individuals actually had diabetes. Calculate the sensitivity of the screening test.

90/100. ***90/100*** - **Sensitivity** measures the proportion of **true positives** correctly identified by the screening test among all individuals who actually have the disease. - **Formula:** Sensitivity = True Positives / (True Positives + False Negatives) - In this scenario, the gold standard confirmed **100 individuals** as truly positive for diabetes. - Of these 100 disease-positive individuals, the screening test correctly identified **90 as positive** (true positives). - The remaining **10 individuals** with diabetes tested negative on the screening test (false negatives). - **Sensitivity = 90/100 = 0.90 or 90%** *100/110* - This calculation is incorrect as it uses **110 as the denominator**, which has no basis in the given data. - Sensitivity denominator should be the **total number of disease-positive individuals** according to the gold standard, which is **100**, not 110. - This does not represent any standard epidemiological measure in this context. *80/100* - This option incorrectly assumes **80 true positives** were detected by the screening test. - The question clearly states that **90 individuals tested positive** on the screening test, not 80. - This contradicts the given information. *100/100* - This would represent **perfect sensitivity** (100%), meaning the screening test identified all individuals with diabetes. - However, the screening test only identified **90 positives** while the gold standard confirmed **100 positives**. - This means **10 individuals with diabetes were missed** by the screening test (false negatives), so sensitivity cannot be 100%.

Question 1

A 60-year-old man presents with a chronic cough and is found to have a lung lesion on chest X-ray. What is the significance of high sensitivity in a diagnostic test for lung cancer?

Accepted Answer

It correctly identifies those with the disease

Answer

It incorrectly identifies those without the disease

Answer

It indicates the proportion of true positives among all positive results

Answer

It indicates the proportion of false negatives among all actual positives

Question 2

In a community-based intervention, the incidence of a disease is found to decrease after vaccination. What study design is most appropriate to confirm vaccine efficacy?

Accepted Answer

Randomized controlled trial

Answer

Cohort study

Answer

Case-control study

Answer

Cross-sectional study

Question 3

In a clinical study assessing the impact of lifestyle changes on hypertension, which outcome measure would be the most appropriate to evaluate effectiveness?

Accepted Answer

Blood pressure measurement

Answer

Patient self-reported wellness

Answer

Frequency of exercise

Answer

Dietary intake logs

Question 4

A randomized controlled trial of antihypertensives shows a p-value of 0.04 for the difference in blood pressure reduction. What is the most accurate interpretation?

Accepted Answer

4% chance of this or more extreme result if null true

Answer

4% chance that the null hypothesis is true

Answer

96% chance that the alternative hypothesis is true

Answer

4% chance that the difference is due to random chance

Question 5

In a study of 100 patients, the standard deviation of their blood pressure measurements is found to be 10 mmHg. What is the standard error of the mean?

Accepted Answer

1

Answer

10

Answer

0.1

Answer

2

Question 6

During a health survey, data was collected to calculate the prevalence of hypertension in a population. Which statistical measure is used to describe the central tendency of systolic blood pressure readings in this survey?

Accepted Answer

Mean

Answer

Median

Answer

Mode

Answer

Range

Question 7

Which observational study design is most appropriate for analyzing the long-term effects of an exposure or treatment over a specified timeline?

Accepted Answer

Cohort Study

Answer

Cross sectional study

Answer

Randomized Control Trials

Answer

Interventional Studies

Question 8

Which type of study determines the odds ratio?

Accepted Answer

Case control

Answer

Cohort

Answer

Cross sectional

Answer

RCT

Question 9

The ability of a diagnostic test to correctly identify individuals who have the disease (detect disease when present) is called-

Accepted Answer

Sensitivity (True Positive Rate)

Answer

Negative predictive value

Answer

Specificity (True Negative Rate)

Answer

Positive predictive value (PPV)

Question 10

In a screening test for diabetes mellitus (DM) conducted on a population of 1000, the screening test identified 90 individuals as positive. When the gold standard test was performed on the entire population, it confirmed that 100 individuals actually had diabetes. Calculate the sensitivity of the screening test.

Accepted Answer

90/100

Answer

100/110

Answer

80/100

Answer

100/100

Biostatistics — MCQs

Biostatistics — MCQs

On this page

Practice by Chapter

Want unlimited practice?