Epidemiology — MCQs

Epidemiology Indian Medical PG Practice Questions and MCQs

Question 1541: A new mammography technique has 95% sensitivity and 88% specificity for breast cancer detection. The current standard has 85% sensitivity and 95% specificity. Both techniques cost the same to implement. Which approach would be most appropriate for a national screening program?

A. Use new technique for high-risk patients only
B. Use current standard due to higher specificity
C. Continue current standard until more data available
D. Use new technique due to higher sensitivity (Correct Answer)

Explanation: ***Use new technique due to higher sensitivity*** - For a **national screening program**, **high sensitivity** is crucial to detect as many cases as possible and minimize **false negatives**, which could lead to delayed diagnosis and worse outcomes. - While the new technique has slightly lower specificity, the benefit of catching more true positives outweighs the increased number of false positives in a **screening context**, especially since costs are equal. *Use new technique for high-risk patients only* - This approach does not address the question of which technique is **most appropriate for a national screening program**, which typically targets the general population or a broad risk group. - Limiting the use to high-risk patients would still necessitate a choice of technique for the general population or exclude a significant portion of patients who could benefit from the new technique's higher sensitivity. *Use current standard due to higher specificity* - Although the current standard has higher specificity (95% vs. 88%), meaning fewer **false positives**, a screening program prioritizes **sensitivity** to avoid missing cases. - The goal of screening is to identify potential disease early in a large population, and accepting a slightly higher rate of false positives (which can be followed up with further diagnostic tests) is often preferred over missing actual cases. *Continue current standard until more data available* - The problem states that the new technique is available with defined sensitivity and specificity, implying sufficient data for consideration. - Delaying the adoption of a technique with **higher sensitivity** would mean continuing to miss more cases than necessary, which is not ideal for a screening program.

Question 1542: A screening program implements two tests in parallel (positive if either test is positive) for a disease. Test A has 80% sensitivity and 90% specificity. Test B has 70% sensitivity and 95% specificity. Analyze the expected performance of the combined approach.

A. Both sensitivity and specificity will be higher
B. Combined sensitivity will be lower than either individual test
C. Combined specificity will be higher but sensitivity will be lower
D. Combined sensitivity will be higher but specificity will be lower (Correct Answer)

Explanation: ***Combined sensitivity will be higher but specificity will be lower*** - When tests are used in **parallel** (positive if either test is positive), the probability of detecting the disease (sensitivity) increases because a positive result from either test leads to identification. - However, this also increases the likelihood of a **false positive** result (reducing specificity) because a false positive from either test will result in an overall positive screening. *Both sensitivity and specificity will be higher* - This scenario would only occur if the tests were perfectly complementary and both had very high performance individually, which is not guaranteed or typical when combining in parallel. - Using tests in parallel typically causes a trade-off where an increase in sensitivity often comes at the cost of decreased specificity. *Combined sensitivity will be lower than either individual test* - This is incorrect for tests used in parallel; sensitivity generally increases because there are more opportunities to correctly identify a diseased individual (if test A or test B is positive). - A lower combined sensitivity would be more characteristic of tests used in **series** (both must be positive). *Combined specificity will be higher but sensitivity will be lower* - This outcome is characteristic of tests used in **series**, where both tests must be positive for a combined positive result. - In a series approach, false positives are reduced (higher specificity) because both tests have to agree, but true positives might be missed if one test is negative, leading to lower sensitivity. *The tests will have identical performance when combined* - This is incorrect; combining tests in any manner (parallel or series) will alter the overall sensitivity and specificity from that of the individual tests. - The performance of the combined approach is a function of the individual test characteristics and the method of combination.

Question 1543: A case-control study of breast cancer finds that women with the disease are more likely to recall family history of cancer than healthy controls. This could represent recall bias. Analyze how this bias would affect the study's conclusions.

A. Recall bias would not affect the study results
B. Recall bias can be corrected through statistical adjustment
C. Recall bias would overestimate the association between family history and breast cancer (Correct Answer)
D. Recall bias would underestimate the association between family history and breast cancer

Explanation: ***Recall bias would overestimate the association between family history and breast cancer*** - **Recall bias** causes individuals with a disease (cases) to remember past exposures (like family history) more readily or thoroughly than healthy controls. - This differential recall leads to an artificially inflated perception of the association between the exposure and the disease, making the observed risk appear higher than it truly is. *Recall bias would not affect the study results* - This statement is incorrect because recall bias is a **systematic error** in data collection, directly impacting the accuracy of the exposure information. - As a form of **information bias**, it inherently distorts the relationship between exposure and outcome. *Recall bias can be corrected through statistical adjustment* - While some biases might be amenable to statistical adjustment, **recall bias** is often difficult to fully correct statistically because it stems from the inherent inaccuracy of reported data. - Statistical methods can sometimes mitigate its impact if the nature and extent of the bias are well-understood, but they cannot perfectly reconstruct the true exposure information. *Recall bias would underestimate the association between family history and breast cancer* - **Underestimation** would occur if cases remembered past exposures *less* accurately or frequently than controls, or if the bias pushed the observed association towards the null. - In situations of recall bias, particularly when individuals with the disease are more motivated to search for potential causes, the tendency is to **overestimate** the exposure in cases.

Question 1544: A diagnostic test for a rare disease has 99% sensitivity and 95% specificity. In a population with 0.1% disease prevalence, analyze the clinical utility of this test for screening purposes.

A. The test should only be used for high-risk patients
B. The test performance is inadequate for any clinical use
C. The test is not suitable for screening due to low prevalence (Correct Answer)
D. The test is excellent for screening due to high sensitivity and specificity

Explanation: ***The test is not suitable for screening due to low prevalence*** - In situations with **low disease prevalence**, even a test with high sensitivity and specificity will yield a **low positive predictive value (PPV)**. This means a high proportion of positive results will be **false positives**. - A low PPV implies that many individuals would be incorrectly identified as diseased, leading to unnecessary anxiety, further costly diagnostic workups, and potential harm from subsequent invasive procedures. - With 0.1% prevalence, 99% sensitivity, and 95% specificity, the **PPV would be approximately 2%**, meaning 98% of positive results would be false positives, making population screening impractical and harmful. *The test should only be used for high-risk patients* - While this option highlights a more appropriate use, the question asks about **screening purposes** in a general population scenario. - In a high-risk group, the **prevalence would be higher**, which would improve the **positive predictive value** of the test and make it more clinically useful. *The test performance is inadequate for any clinical use* - This statement is too absolute; the test might be useful in **confirmatory diagnosis** or in cases of **high clinical suspicion** where the pre-test probability is higher. - High sensitivity and specificity are valuable for diagnostic tests, but their utility depends heavily on the **pre-test probability** of disease, which is low in general screening for rare conditions. *The test is excellent for screening due to high sensitivity and specificity* - While **high sensitivity (99%)** and **specificity (95%)** are desirable characteristics for a diagnostic test, they alone do not dictate its suitability for population screening. - The extremely **low prevalence (0.1%)** of the disease significantly diminishes the **positive predictive value**, rendering it unsuitable for mass screening despite excellent statistical performance metrics. - This is a common misconception—students must understand that **prevalence** is a critical factor in determining screening test utility.

Question 1545: A screening program for colorectal cancer uses fecal occult blood testing (FOBT) with 70% sensitivity and 95% specificity. When positive, patients undergo colonoscopy. Analyze the strategy's effectiveness in a population with 3% colorectal cancer prevalence.

A. The strategy is optimal for this population
B. The strategy has limited effectiveness due to low sensitivity
C. The strategy is highly effective due to high specificity
D. The strategy would result in too many unnecessary colonoscopies (Correct Answer)

Explanation: ***The strategy would result in too many unnecessary colonoscopies*** - With a 3% prevalence and 95% specificity, a significant number of healthy individuals (false positives) will be referred for **invasive and costly colonoscopies**. - For every 10,000 people, roughly 485 healthy individuals (9,700 × 5%) would have a positive FOBT, compared to only 210 true positives (300 × 70%). - This yields a **positive predictive value of only ~30%**, meaning most positive results lead to unnecessary procedures. *The strategy is optimal for this population* - This statement is incorrect because the high number of **false positives** leading to unnecessary invasive procedures makes the strategy suboptimal for a low-prevalence population. - An optimal strategy would balance the benefits of early detection with the risks and costs of follow-up diagnostics. *The strategy has limited effectiveness due to low sensitivity* - While a sensitivity of 70% means 30% of actual cancer cases (90 out of 300) would be missed as **false negatives**, this is actually acceptable for a screening test. - However, the primary issue in a low-prevalence population is the burden of **false positives**, not the sensitivity limitation. *The strategy is highly effective due to high specificity* - High specificity (95%) is generally good, but in a low-prevalence population (3%), even a small percentage of false positives translates into a large absolute number. - For every 10,000 individuals, 485 healthy people would receive a positive result, leading to **unnecessary follow-up** procedures that outweigh the 210 true positives detected.

Question 1546: A cohort study follows 10,000 nurses for 20 years to study the relationship between night shift work and breast cancer. The study finds a hazard ratio of 1.3 (95% CI: 1.1-1.6). However, 30% of participants were lost to follow-up. Analyze how this affects the validity of the results.

A. The loss to follow-up may introduce bias depending on reasons for dropout (Correct Answer)
B. The hazard ratio is likely underestimated
C. The results are invalid due to high loss to follow-up
D. The confidence interval accounts for the loss to follow-up

Explanation: ***The loss to follow-up may introduce bias depending on reasons for dropout*** - A significant **loss to follow-up (30%)** can lead to **selection bias** if the reasons for dropout are related to both the exposure (night shift work) and the outcome (breast cancer). - For example, if nurses with higher risk or early symptoms of breast cancer are more likely to drop out, the observed hazard ratio could be either underestimated or overestimated. *The hazard ratio is likely underestimated* - It's not definitively true that the hazard ratio is underestimated; the direction of bias depends on whether those lost to follow-up had a higher or lower incidence of the outcome. - If nurses who developed breast cancer or had risk factors for it were more likely to drop out, the hazard ratio for the remaining cohort might be underestimated. Conversely, if healthier nurses dropped out, it could be overestimated. *The results are invalid due to high loss to follow-up* - While a 30% loss to follow-up is substantial and raises concerns about **validity**, it doesn't automatically invalidate the entire study. - The impact depends on the characteristics of those lost and the methods used to address missing data; sensitivity analyses might still provide useful insights. *The confidence interval accounts for the loss to follow-up* - The **confidence interval** primarily reflects the **precision** of the estimate, taking into account random error and sample size, not systematic biases introduced by loss to follow-up. - While a smaller effective sample size due to loss to follow-up might widen the CI, it does not correct for potential **selection bias**.

Question 1547: A diagnostic test for COVID-19 has 95% sensitivity and 98% specificity. In a community with 2% prevalence, analyze the implications of implementing this test for mass screening versus using it for symptomatic patients only.

A. Mass screening would be more effective due to high sensitivity
B. Testing symptomatic patients only would be more efficient (Correct Answer)
C. The test is not suitable for either approach
D. Both approaches would have similar effectiveness

Explanation: ***Testing symptomatic patients only would be more efficient*** - In a low-prevalence setting (2%), testing symptomatic patients means the **pre-test probability** of disease is higher, and the test's **positive predictive value** will be more reliable. - In a population with 2% prevalence, if 1000 people are tested, there are 20 true cases. With 98% specificity, 2% of the 980 healthy individuals (approximately 20 people) will incorrectly test positive, resulting in a **high number of false positives** compared to actual cases (PPV ≈ 50%). - Focusing on symptomatic individuals optimizes resource allocation and minimizes the number of **false positives** that would arise in mass screening of a general population with low disease prevalence. *Mass screening would be more effective due to high sensitivity* - While high sensitivity (95%) is good for detecting true positives, in a low-prevalence population, even a high sensitivity test will yield a significant number of **false positives** relative to true positives. - The effectiveness of mass screening is limited by the **positive predictive value**, which decreases significantly with low disease prevalence, making it less efficient despite high sensitivity. *The test is not suitable for either approach* - The test's 95% sensitivity and 98% specificity are generally considered **good performance characteristics** for a diagnostic test. - The issue is not the test's inherent suitability but rather the **context of its application** (low prevalence mass screening vs. higher prevalence symptomatic testing). *Both approaches would have similar effectiveness* - The effectiveness of testing strategies is heavily influenced by the **prevalence of the disease** in the tested population. - Due to the significant difference in prevalence between a general population (2%) and a symptomatic patient population (likely much higher), the **positive predictive value** and overall efficiency would differ substantially.

Question 1548: A case-control study finds an odds ratio of 3.5 (95% CI: 2.1-5.8) for the association between smoking and lung cancer. However, the researchers did not control for occupational exposures, which are known risk factors for lung cancer. Analyze how this affects the interpretation of the results.

A. The lack of control for occupational exposures has no impact
B. The confidence interval indicates the results are not significant
C. The association is likely overestimated due to confounding (Correct Answer)
D. The odds ratio is underestimated due to confounding

Explanation: ***The association is likely overestimated due to confounding*** - **Confounding occurs** when an unmeasured or uncontrolled factor (**occupational exposures**) is associated with both the exposure (smoking) and the outcome (lung cancer). - If occupational exposures are also a risk factor for lung cancer and are more common in smokers, the observed odds ratio for smoking would be **inflated**, suggesting a stronger association than truly exists. *The lack of control for occupational exposures has no impact* - This statement is incorrect because **occupational exposures are known risk factors for lung cancer** and could be associated with smoking status. - Ignoring such a factor violates the assumptions of a valid association measure, leading to a potentially **spurious association**. *The confidence interval indicates the results are not significant* - The 95% confidence interval (2.1-5.8) for the odds ratio **does not include 1.0**, which means the results are statistically significant. - A significant finding only implies that the observed association is unlikely due to **random chance**, not that it is free from bias. *The odds ratio is underestimated due to confounding* - For confounding to cause underestimation, occupational exposures would need to be negatively associated with smoking or positively associated with the lack of smoking. - Given that occupational exposures are additional risk factors for lung cancer and often correlate with smoking, **overestimation of the odds ratio** is a more probable outcome.

Question 1549: A cross-sectional study surveys 5,000 adults about their exercise habits and measures their BMI at the same time. What is the main limitation of this study design?

A. It cannot measure multiple variables simultaneously
B. It is too expensive to conduct
C. It cannot establish prevalence of obesity
D. It cannot determine temporal relationships (Correct Answer)

Explanation: ***It cannot determine temporal relationships*** - A **cross-sectional study** collects data at a single point in time, making it impossible to determine which came first: the exercise habits or the BMI. - This limitation prevents the establishment of **cause-and-effect relationships**, as the temporal sequence of events cannot be ascertained. *It cannot measure multiple variables simultaneously* - This statement is incorrect; cross-sectional studies are perfectly capable of measuring **multiple variables** (e.g., exercise habits, BMI, age, gender) at the same time. - The purpose of such studies often involves examining **associations** between various factors present concurrently. *It is too expensive to conduct* - Cross-sectional studies are generally **less expensive** and quicker to conduct compared to longitudinal studies, as they don't require follow-up over time. - Therefore, cost is typically considered an advantage, not a major limitation, especially for large sample sizes. *It cannot establish prevalence of obesity* - This statement is incorrect; a cross-sectional study is ideal for estimating the **prevalence** of a condition (like obesity) within a population at a specific time. - By measuring BMI in 5,000 adults, the study can directly calculate the proportion of individuals classified as obese.

Question 1550: A screening test for diabetes has a sensitivity of 95% and specificity of 85%. When applied to a high-risk population (prevalence 15%), what can be concluded about the test's performance?

A. The specificity is too low for clinical use
B. The test will miss 5% of diabetic patients (Correct Answer)
C. The test will correctly identify 95% of all patients
D. The test is not suitable for screening purposes

Explanation: ***The test will miss 5% of diabetic patients*** - **Sensitivity** is the proportion of true positives that are correctly identified, meaning a 95% sensitivity indicates that **95% of people with diabetes will test positive**. - Conversely, a sensitivity of 95% means that **5% of people with diabetes will test negative**, representing **false negatives** or missed cases. *The specificity is too low for clinical use* - A specificity of 85% means that **85% of individuals without the disease will correctly test negative**; this is a reasonable specificity for screening tests, especially with high sensitivity. - The acceptability of specificity depends on the **disease and clinical context**, and 85% is not necessarily "too low" in all screening scenarios, particularly when high sensitivity is prioritized. *The test will correctly identify 95% of all patients* - **Sensitivity** refers only to the correct identification of those *with the disease* (true positives), and **specificity** to the correct identification of those *without the disease* (true negatives). - The overall correct identification rate of all patients (accuracy) depends on both sensitivity and specificity, as well as the **prevalence of the disease**, and cannot be simply assumed from sensitivity alone. *The test is not suitable for screening purposes* - A sensitivity of 95% and specificity of 85% can be considered **suitable for screening**, especially for diseases where early detection is crucial. - The high sensitivity ensures that a large proportion of affected individuals are detected, which is a key goal of **screening programs**.

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Principles of Epidemiology

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Measures of Disease Frequency

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Epidemiological Study Designs

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Experimental Epidemiology

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Screening for Disease

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Surveillance Systems

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Investigation of an Epidemic

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Association and Causation

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Modern Epidemiological Methods

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Critical Appraisal of Epidemiological Studies

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