Biostatistics Practice Questions

Q: In a study of 200 patients, CA-125 testing was performed. Among the 100 patients who tested positive, 60 had ovarian cancer confirmed by histopathology. Among the 100 patients who tested negative, 20 had ovarian cancer confirmed by histopathology. What is the negative predictive value of this test?

80/100. ***80/100*** - The **negative predictive value (NPV)** is the probability that a patient who tests negative actually does not have the disease. - In this case, 100 patients tested negative, and 20 of them *did* have ovarian cancer, meaning 80 **did not** have ovarian cancer. Thus, NPV = 80/100. *20/100* - This represents the number of **false negatives** among all patients who tested negative, not the negative predictive value. - A false negative occurs when the test result is negative, but the disease is actually present. *40/100* - This value represents the number of patients who tested positive but **did not** have the disease (false positives), calculated as 100 (total positive tests) - 60 (true positives) = 40. - This is not the calculation for negative predictive value. *60/100* - This represents the number of **true positives** among all patients who tested positive. - This is a component of **positive predictive value**, not negative predictive value.

Q: In the context of statistical analysis, if you have the value of one variable, which coefficient would you use to predict the value of another variable?

Coefficient of regression. ***Coefficient of regression*** - The **coefficient of regression** (or **regression coefficient**) is fundamental in **regression analysis**, which is specifically designed to predict the value of a **dependent variable** based on the value of one or more **independent variables**. - It quantifies the expected change in the dependent variable for a unit change in the independent variable. *Coefficient of variation* - The **coefficient of variation** is a measure of **relative variability** or dispersion, expressing the standard deviation as a percentage of the mean. - It describes the extent of variation in relation to the mean but does not provide a basis for predicting one variable from another. *Coefficient of correlation* - The **coefficient of correlation** measures the **strength and direction of a linear relationship** between two variables. - While it indicates how well two variables move together, it does not directly enable the prediction of one variable's value from another; that is the role of regression. *Coefficient of determination* - The **coefficient of determination (R²)** represents the **proportion of the variance** in the dependent variable that can be explained by the independent variable(s) in a regression model. - It quantifies how well the regression model fits the observed data, but it is not used directly for prediction; rather it is for assessing the predictive power of the model.

Q: Which measure indicates the diagnostic power of a test to correctly identify those with a disease?

Sensitivity. ***Positive predictive value*** - It refers to the probability that subjects with a positive test result truly have the disease, highlighting the test's **diagnostic accuracy** [1]. - A high positive predictive value indicates that the test is effective at diagnosing the disease in the population tested. *Sensitivity* - Sensitivity measures the ability of a test to correctly identify those with the disease (true positives), but does not account for the test result's predictive capability [1]. - It is important for screening, but **not directly the diagnostic power** for those already tested. *Negative predictive value* - This indicates the probability that subjects with a negative test result truly do not have the disease, focusing on true negatives rather than correct diagnosis of the condition [1]. - While informative, it does not assess the ability to correctly diagnose the disease when the result is positive. *Specificity* - Specificity is the measure of a test's ability to correctly identify those without the disease (true negatives), not diagnosing the disease accurately among those tested [1]. - It is essential for determining false positives but not for assessing the overall diagnostic power of a test. **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: What is a key benefit of Randomized Controlled Trials (RCTs) in clinical research?

They minimize selection bias.. ***They minimize selection bias.*** - **Randomization** in RCTs ensures that participants have an equal chance of being assigned to any of the treatment groups, thereby balancing potential **confounding factors** across groups. - This balance helps to ensure that any observed differences in outcomes between groups are more likely due to the intervention being studied rather than pre-existing differences among participants, thus minimizing **selection bias**. *They can be conducted more quickly than other study types.* - RCTs often require **extensive planning**, recruitment, and follow-up periods, making them one of the **most time-consuming** study designs. - The need for sufficient **power** to detect meaningful differences often translates into longer study durations. *They are ideal for studying rare diseases.* - Due to the requirement for **large sample sizes** to demonstrate statistical significance, RCTs are **not practical** for diseases with low prevalence. - Recruiting enough participants with a rare disease for an RCT can be extremely challenging and often **unfeasible**. *They are generally less expensive than other study types.* - RCTs are typically among the **most expensive** study designs because they involve extensive participant recruitment, intervention administration, data collection, and long-term follow-up. - The costs associated with staff, resources, and monitoring for ethical compliance contribute to their **high financial burden**.

Q: Which of the following is an example of a case-control study?

PVC exposure and angiosarcoma of the liver. ***PVC exposure and angiosarcoma of the liver*** - This is a classic example of a **case-control study** where individuals with a rare disease (angiosarcoma of the liver) are identified (cases) and compared to a control group without the disease to determine past exposures (PVC). - The study looked back in time to identify differences in exposure between cases and controls. *Framingham heart study (cohort study)* - The Framingham Heart Study is a well-known **prospective cohort study** that has followed participants over time to observe the development of cardiovascular disease. - In a cohort study, researchers identify a group of individuals and follow them forward in time to see who develops the outcome of interest, making it different from a case-control design. *Doll & Hill Study (cohort study)* - The Doll & Hill study is a landmark **cohort study** that investigated the association between smoking and lung cancer by following a group of British doctors over several years. - This study started with healthy individuals and observed them over time to see who developed lung cancer, which is characteristic of a cohort design. *Thalidomide exposure and its association with teratogenicity* - While the thalidomide tragedy led to crucial epidemiological investigations, the initial identification of the association was often through **case series** or **descriptive epidemiology**, noting an unusual clustering of rare birth defects among infants whose mothers took thalidomide. - Subsequent studies might have incorporated case-control elements, but the prompt asks for an example of a case-control study, and this event itself is generally cited for its role in pharmacovigilance and observational studies rather than a single, classic case-control study example in the way "PVC and angiosarcoma" is.

Q: In a community of 1,000,000 population, 105 children were born in a year, out of which 5 were stillbirths and 4 died within the first year of life. What is the Infant Mortality Rate (IMR)?

40. ***40*** - **Infant Mortality Rate (IMR)** = (Deaths in first year of life / Live births) × 1,000 - Live births = Total births - Stillbirths = 105 - 5 = **100** - IMR = (4 / 100) × 1,000 = **40 per 1,000 live births** - Stillbirths are excluded from both numerator and denominator as IMR only counts deaths after live birth *90* - This would result from incorrectly using total births (105) instead of live births (100) in the denominator - Wrong calculation: (4 / 105) × 1,000 ≈ 38, not 90 - This option represents a common error but with incorrect arithmetic *120* - This could result from including stillbirths in the numerator: (5+4) / 100 × 1,000 = 90, not 120 - Or from other miscalculations mixing up the numerator and denominator - Does not follow the standard IMR formula *150* - This represents a significant calculation error - May result from using wrong base (per 100 instead of per 1,000) or including stillbirths incorrectly - Such high IMR does not match the given data of 4 infant deaths per 100 live births

Q: Which study design is most effective for investigating rare adverse effects of a drug?

Case-control study. ***Case-control study*** - This design starts by identifying individuals with the **rare adverse effect (cases)** and a control group without the effect to look back for exposure to the drug. - It is efficient for studying rare outcomes because it doesn't require following a large population for a long time to observe few events. *Cohort study* - A **cohort study** follows a group of individuals exposed and unexposed to a drug forward in time to observe outcomes. - While good for common outcomes, it would require an **extremely large sample size** and a long follow-up period to observe rare adverse drug effects. *Cross-sectional study* - A **cross-sectional study** assesses exposure and outcome simultaneously at a single point in time. - This design is suitable for determining **prevalence** but cannot establish temporal relationships between drug exposure and rare adverse effects, nor is it efficient for rare outcomes. *Clinical trial/experimental study* - **Clinical trials** are primarily designed to test the efficacy and safety of new interventions, usually focusing on common adverse effects. - They are generally **not powered** or long enough to detect rare adverse events, as such events would occur in very few participants, if any.

Q: Bladder cancer can occur in those who are working in dye industry for 25 years. Which study design is most appropriate for establishing a causal relationship between dye industry work and bladder cancer?

Cohort study. ***Cohort study*** - A **cohort study** tracks a group of individuals exposed to a risk factor (dye industry work) and a group not exposed over time to see who develops the outcome (bladder cancer). - This design allows for the calculation of **incidence rates** and relative risk, which are crucial for establishing a causal link, especially when the exposure is rare or specific. - Cohort studies establish **temporal relationship** (exposure precedes disease) and can demonstrate a **dose-response relationship**, both essential for proving causality. *Cross-sectional study* - A **cross-sectional study** assesses exposure and outcome simultaneously at a single point in time, making it difficult to determine the temporal sequence of events. - While it can identify associations, it cannot definitively establish a **cause-and-effect relationship** because it doesn't observe outcomes developing over time. *Case-control study* - A **case-control study** compares individuals with the outcome (cases) to individuals without the outcome (controls) and retrospectively looks for differences in past exposures. - While useful for studying **rare diseases** and can suggest associations, it is prone to **recall bias** regarding exposure history and cannot establish causality as definitively as cohort studies. *Randomized control trial* - A **randomized controlled trial (RCT)** involves randomly assigning participants to an intervention group or a control group and following them prospectively. - While RCTs provide the strongest evidence for causality, it would be **unethical** to intentionally expose people to a known carcinogen like dye industry chemicals for research purposes.

Question 1

In a study of 200 patients, CA-125 testing was performed. Among the 100 patients who tested positive, 60 had ovarian cancer confirmed by histopathology. Among the 100 patients who tested negative, 20 had ovarian cancer confirmed by histopathology. What is the negative predictive value of this test?

Accepted Answer

80/100

Answer

20/100

Answer

40/100

Answer

60/100

Question 2

In the context of statistical analysis, if you have the value of one variable, which coefficient would you use to predict the value of another variable?

Accepted Answer

Coefficient of regression

Answer

Coefficient of variation

Answer

Coefficient of correlation

Answer

Coefficient of determination

Question 3

In a screening test for DM out of 1000 population, 90 were positive. When the gold standard test was applied to the entire population, 100 were found to have the disease. Assuming all 90 screening positives were confirmed as true positives by the gold standard, calculate the sensitivity.

Accepted Answer

True positives divided by total actual positives (90%)

Answer

All positives identified by the test assumed as true positives (100%)

Answer

Underestimated true positives divided by total actual positives (80%)

Answer

Total positives identified by the test divided by total actual positives (90%)

Question 4

Which measure indicates the diagnostic power of a test to correctly identify those with a disease?

Accepted Answer

Sensitivity

Answer

Negative predictive value

Answer

Specificity

Answer

Positive predictive value

Question 5

What is a key benefit of Randomized Controlled Trials (RCTs) in clinical research?

Accepted Answer

They minimize selection bias.

Answer

They can be conducted more quickly than other study types.

Answer

They are ideal for studying rare diseases.

Answer

They are generally less expensive than other study types.

Question 6

Which of the following is an example of a case-control study?

Accepted Answer

PVC exposure and angiosarcoma of the liver

Answer

Framingham heart study

Answer

Doll & Hill Study

Answer

Thalidomide exposure and its association with teratogenicity

Question 7

In a community of 1,000,000 population, 105 children were born in a year, out of which 5 were stillbirths and 4 died within the first year of life. What is the Infant Mortality Rate (IMR)?

Accepted Answer

40

Answer

90

Answer

120

Answer

150

Question 8

Which of the following statements is true regarding a combined prospective-retrospective study?

Accepted Answer

Retrospective identification of cohort followed by prospective follow-up

Answer

Only prospective follow-up from current time point

Answer

Cross-sectional assessment at a single time point

Answer

Only retrospective data collection from past records

Question 9

Which study design is most effective for investigating rare adverse effects of a drug?

Accepted Answer

Case-control study

Answer

Cohort study

Answer

Cross-sectional study

Answer

Clinical trial/experimental study

Question 10

Bladder cancer can occur in those who are working in dye industry for 25 years. Which study design is most appropriate for establishing a causal relationship between dye industry work and bladder cancer?

Accepted Answer

Cohort study

Answer

Cross-sectional study

Answer

Case-control study

Answer

Randomized control trial

Biostatistics — MCQs

Biostatistics — MCQs

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