Biostatistics Practice Questions

Q: Which of the following is NOT evaluated by a cohort study?

Odds ratio. **Explanation** In epidemiology, the choice of study design dictates which measures of association can be calculated. A **Cohort Study** is a longitudinal, prospective study that starts with a group of exposed and non-exposed individuals and follows them over time to observe the development of an outcome. **Why Odds Ratio is the Correct Answer:** The **Odds Ratio (OR)** is the primary measure of association used in **Case-Control studies**. It estimates the odds of exposure among cases compared to controls. While OR can be calculated in a cohort study, it is not the standard or intended evaluation metric because cohort studies allow for the direct calculation of risk. **Analysis of Incorrect Options:** * **A. Incidence:** Cohort studies are the only observational design that can directly calculate incidence (the number of new cases in a population at risk) because they follow subjects from a healthy state to the onset of disease. * **B. Attributable Risk (AR):** AR measures the impact of an exposure (Incidence in exposed – Incidence in non-exposed). Since cohort studies provide incidence, AR can be easily derived. * **C. Relative Risk (RR):** Also known as Risk Ratio, this is the hallmark measure of a cohort study. It compares the incidence of disease in the exposed group to the incidence in the non-exposed group. **High-Yield Clinical Pearls for NEET-PG:** * **Cohort Study:** Proceeds from **Cause to Effect**. Best for rare exposures. * **Case-Control Study:** Proceeds from **Effect to Cause**. Best for rare diseases. * **Incidence** can *only* be calculated in Cohort studies (and Randomized Controlled Trials). * If a disease is rare, the Odds Ratio (from a case-control study) numerically approximates the Relative Risk.

Q: For the diagnosis of Deep Vein Thrombosis, two tests are done together: Impedance Plethysmography and leg scanning after injecting 125I fibrinogen. What is the primary purpose of combining these diagnostic procedures?

Increasing the negative predictive value. ### Explanation In clinical practice, diagnostic tests can be performed in two ways: **Parallel Testing** (tests done together) or **Serial Testing** (tests done one after another). **1. Why the correct answer is right (Option B):** The scenario describes **Parallel Testing**. When two tests are performed simultaneously, a patient is considered "positive" if *either* test is positive and "negative" only if *both* tests are negative. * **Mechanism:** This approach maximizes **Sensitivity** because it is less likely to miss a case of the disease. * **Impact on Predictive Value:** As sensitivity increases, the **Negative Predictive Value (NPV)** also increases. A negative result in parallel testing provides high confidence that the patient truly does not have Deep Vein Thrombosis (DVT), effectively "ruling out" the disease. **2. Why the incorrect options are wrong:** * **Option A & D:** Increasing the **Positive Predictive Value (PPV)** and **Specificity** is the goal of **Serial Testing** (e.g., an ELISA followed by a Western Blot for HIV). Serial testing "rules in" a disease by ensuring that only those who pass multiple diagnostic hurdles are labeled positive. * **Option C:** **Pretest odds** (or pretest probability) are determined by the prevalence of the disease in the population and the clinical presentation of the patient *before* any tests are conducted. Performing diagnostic tests does not change the pretest odds. **3. High-Yield Clinical Pearls for NEET-PG:** * **Parallel Testing:** ↑ Sensitivity, ↑ NPV, ↓ Specificity. (Used for **Screening** or emergency "rule-out"). * **Serial Testing:** ↑ Specificity, ↑ PPV, ↓ Sensitivity. (Used for **Confirmation** of a diagnosis). * **Net Sensitivity in Parallel:** $1 - [(1 - \text{Sens}_1) \times (1 - \text{Sens}_2)]$. * **Net Specificity in Parallel:** $\text{Spec}_1 \times \text{Spec}_2$.

Q: A screening test was carried out among 120 people. 20 had the disease, and 40 showed a positive test result, out of which 15 had the disease. What is the specificity of the test?

75%. ### Explanation To solve this problem, we must first organize the data into a standard **2x2 Contingency Table**. | | Disease Present (D+) | Disease Absent (D-) | Total | | :--- | :---: | :---: | :---: | | **Test Positive (T+)** | 15 (True Positive) | 25 (False Positive) | 40 | | **Test Negative (T-)** | 5 (False Negative) | 75 (True Negative) | 80 | | **Total** | **20** | **100** | **120** | **Step-by-Step Calculation:** 1. **Total Population:** 120. 2. **Disease Present (D+):** 20. Therefore, **Disease Absent (D-):** $120 - 20 = 100$. 3. **Test Positive (T+):** 40. Out of these, 15 have the disease (True Positives). 4. **False Positives (FP):** $40 - 15 = 25$. 5. **True Negatives (TN):** Total Disease Absent (100) minus False Positives (25) = **75**. **Specificity Formula:** $$\text{Specificity} = \frac{\text{True Negatives (TN)}}{\text{Total Disease Absent (D-)}} \times 100$$ $$\text{Specificity} = \frac{75}{100} \times 100 = \mathbf{75\%}$$ --- #### Analysis of Incorrect Options: * **A (50%):** This is an incorrect calculation, likely confusing the ratio of test positives to the total diseased. * **B (65%):** No direct statistical correlation to the data provided. * **D (25%):** This represents the **False Positive Rate** ($25/100$). Remember: $\text{Specificity} = 1 - \text{False Positive Rate}$. --- #### NEET-PG Clinical Pearls: * **Specificity (SIn):** Highly specific tests, when positive, help **Rule In** the disease (SpPIn). It measures the ability of a test to identify true health. * **Sensitivity (SnOut):** Highly sensitive tests, when negative, help **Rule Out** the disease (SnNOut). * **Screening vs. Diagnosis:** Screening tests require high sensitivity (to catch all cases), while confirmatory/diagnostic tests require high specificity (to avoid false labeling). * **Prevalence:** Note that Sensitivity and Specificity are **independent** of disease prevalence, whereas Predictive Values (PPV/NPV) are prevalence-dependent.

Q: How much area under a normal distribution curve is covered by 3 standard deviations from the mean?

99.7%. ### Explanation The Normal Distribution (Gaussian Distribution) is a fundamental concept in biostatistics, characterized by a bell-shaped, symmetrical curve where the mean, median, and mode coincide at the center. **1. Why the Correct Answer is Right:** The area under the normal curve represents the probability or percentage of data points within a specific range. This is governed by the **Empirical Rule (68-95-99.7 Rule)**: * **Mean ± 1 Standard Deviation (SD):** Covers **68.3%** of the area. * **Mean ± 2 Standard Deviations (SD):** Covers **95.4%** of the area. * **Mean ± 3 Standard Deviations (SD):** Covers **99.7%** of the area. Therefore, 99.7% of all observations in a normally distributed population fall within 3 SDs of the mean, leaving only 0.3% in the extreme tails (0.15% in each tail). **2. Analysis of Incorrect Options:** * **Option A (63.6%) & B (66.6%):** These figures do not correspond to any standard significance levels or SD boundaries in a normal distribution. * **Option C (95%):** This represents the area covered by approximately **1.96 SD** (often rounded to 2 SD for simplicity). This is the standard threshold used to define the "normal range" in clinical medicine. **3. High-Yield Clinical Pearls for NEET-PG:** * **Z-score:** Indicates how many standard deviations a value is from the mean. A Z-score of +3 means the value is 3 SDs above the mean. * **Standard Normal Curve:** A specific normal distribution where the **Mean = 0** and **SD = 1**. * **Skewness:** If the curve is not symmetrical, it is "skewed." If the tail is longer on the right, it is **Positively Skewed** (Mean > Median > Mode). If longer on the left, it is **Negatively Skewed** (Mode > Median > Mean). * **Precision vs. Accuracy:** SD is a measure of precision (dispersion); a smaller SD indicates higher precision.

Q: Which of the following is NOT a characteristic of a case-control study?

Attribute risk calculation. **Explanation:** In epidemiology, the choice of study design dictates which measures of association can be calculated. **Why Option A is the Correct Answer:** **Attributable Risk (AR)** can only be calculated in studies where the **Incidence** of a disease can be measured. Since a Case-Control study starts with people who already have the disease (cases) and compares them to those without it (controls), it proceeds backwards from effect to cause. Because it does not follow a population over time, it cannot determine the rate of new cases (incidence). Therefore, Attributable Risk and Relative Risk are characteristics of **Cohort Studies**, not Case-Control studies. **Analysis of Incorrect Options:** * **B. Measurement of exposure:** This is a core step in Case-Control studies. After selecting cases and controls, the investigator looks back in time (retrospective) to measure the frequency of exposure to a suspected risk factor in both groups. * **C. Use of matching:** Matching is a process used specifically in Case-Control studies to eliminate **confounding factors**. It ensures that cases and controls are comparable regarding factors like age, sex, or socio-economic status. * **D. Calculation of odds ratio:** Since incidence cannot be calculated, the **Odds Ratio (OR)** is the standard measure of association used in Case-Control studies to estimate the strength of the relationship between exposure and outcome. **High-Yield Pearls for NEET-PG:** * **Case-Control:** Retrospective, starts with disease, uses Odds Ratio, good for **rare diseases**. * **Cohort:** Prospective, starts with exposure, uses Relative Risk/Attributable Risk, good for **rare exposures**. * **Matching** prevents confounding but can lead to "over-matching" if not done carefully. * **Neyman Bias:** A type of selection bias common in case-control studies using prevalent rather than incident cases.

Q: A patient with a blood pressure of 210/120mmHg is classified under which type of hypertension?

Categorical. **Explanation:** The correct answer is **Categorical**. In biostatistics, data is classified based on how it is measured and recorded. While blood pressure (BP) is measured as a numerical value (e.g., 210/120 mmHg), the question asks how the patient is **classified**. By assigning the patient to a specific group (e.g., "Stage 2 Hypertension" or "Hypertensive Crisis") based on predefined cut-off points, the data is transformed from a raw number into a **category**. **Why other options are incorrect:** * **Numerical & Quantitative:** These terms refer to the raw data itself (the actual numbers 210 and 120). While BP is quantitative by nature, the act of "classifying" a patient into a diagnostic tier makes the variable categorical (specifically, ordinal). * **Continuous:** This describes data that can take any value within a range (including decimals). While BP is a continuous variable, "classification" implies discrete groupings, which contradicts the definition of continuous data. **High-Yield Clinical Pearls for NEET-PG:** * **Types of Data:** * **Nominal:** Categories with no inherent order (e.g., Gender, Blood Group). * **Ordinal:** Categories with a logical rank/order (e.g., Stages of Hypertension, Socio-economic status, Pain scales). * **Hypertension Classification (ACC/AHA):** * Normal: 180/120 mmHg (as seen in this patient). * **Key Concept:** When a continuous variable (like BP or Blood Sugar) is used to diagnose a condition based on a threshold, it is treated as **Categorical/Ordinal data** for clinical decision-making.

Q: What is the unit of study in a randomized controlled trial?

Patient. ### Explanation **1. Why "Patient" is the Correct Answer:** In a **Randomized Controlled Trial (RCT)**, the primary objective is to evaluate the efficacy and safety of a therapeutic or preventive intervention. The study begins with individuals who already have the condition or are at high risk, and these individuals are randomly assigned to either a treatment group or a control group. Therefore, the **individual (the patient)** is the basic unit of study and randomization. **2. Why Other Options are Incorrect:** * **Population:** This is the unit of study for **Ecological Studies**. In these studies, data is analyzed at the aggregate level (e.g., comparing disease rates between different countries) rather than the individual level. * **Healthy Person:** This is the unit of study for **Field Trials**. Field trials evaluate preventive measures (like vaccines) in individuals who are currently free of the disease. * **Sample Group:** While an RCT involves a sample group, the "unit of study" refers to the smallest component being analyzed and randomized, which is the individual patient, not the group as a whole (unless it is a Cluster Randomized Trial). **3. Clinical Pearls & High-Yield Facts for NEET-PG:** * **Hierarchy of Evidence:** RCTs are considered the "Gold Standard" of study designs (specifically Systematic Reviews/Meta-analyses of RCTs sit at the top). * **Randomization:** Its primary purpose is to eliminate **selection bias** and ensure that both known and unknown confounding factors are distributed equally between groups. * **Blinding:** Used in RCTs to eliminate **observer/procedural bias**. * **Community Trials:** The unit of study here is the **Community** (e.g., fluoridation of water in a whole town).

Q: If 25 persons are working on a project for 30 years, how many person-years of employment are generated?

750. ### Explanation **1. Why the Correct Answer is Right:** The concept of **Person-Years** is a measure of "person-time," which is the sum of the periods of time that all persons in a study or project are exposed to a specific condition or are under observation. It is the denominator used to calculate **Incidence Density**. The formula for calculating person-years is: $$\text{Total Person-Years} = \text{Number of Persons} \times \text{Duration of Time (in years)}$$ In this question: * Number of persons = 25 * Duration = 30 years * Calculation: $25 \times 30 = \mathbf{750 \text{ person-years}}$. This means the total "work experience" or "exposure time" generated by this group is equivalent to one person working for 750 years. **2. Why the Incorrect Options are Wrong:** * **Option A (75):** This is a mathematical error, likely from multiplying $25 \times 3$ or a simple decimal placement mistake. * **Option C (120):** This does not follow any standard epidemiological calculation for these figures. * **Option D (1200):** This would be the result if there were 40 persons working for 30 years, or 25 persons working for 48 years. **3. Clinical Pearls & High-Yield Facts for NEET-PG:** * **Incidence Density:** Unlike cumulative incidence (which uses the population at risk at the start), Incidence Density uses **person-time** as the denominator. It is more accurate when members of a cohort enter or leave the study at different times. * **Unit:** The unit is always "person-time" (e.g., person-years, person-months, or person-days). * **Application:** Person-years are frequently used in longitudinal (cohort) studies and occupational health to measure the risk of developing a disease over varying exposure periods. * **Key Formula:** $\text{Incidence Density} = \frac{\text{Number of new cases}}{\text{Total person-time of observation}}$.

Question 1

If a Hemoccult test is negative for screening of colonic cancer, no further test is done. If the Hemoccult test is positive, the individual will have a second stool sample tested with Hemoccult II test. If this second sample is positive for blood, the individual will be referred for more extensive evaluation. What is the effect of this screening method on net sensitivity and net specificity?

Accepted Answer

Net sensitivity is decreased and net specificity is increased.

Answer

Net sensitivity and net specificity are both increased.

Answer

Net sensitivity is increased and net specificity is decreased.

Answer

Net sensitivity remains the same and net specificity is increased.

Question 2

Which of the following is NOT evaluated by a cohort study?

Accepted Answer

Odds ratio

Answer

Incidence

Answer

Attributable risk

Answer

Relative risk

Question 3

A cessation experiment is a type of:

Accepted Answer

Randomized controlled trial (RCT)

Answer

Cohort study

Answer

Case control study

Answer

Cross-sectional study

Question 4

For the diagnosis of Deep Vein Thrombosis, two tests are done together: Impedance Plethysmography and leg scanning after injecting 125I fibrinogen. What is the primary purpose of combining these diagnostic procedures?

Accepted Answer

Increasing the negative predictive value

Answer

Increasing the positive predictive value

Answer

Increasing the pretest odds

Answer

Increasing the specificity

Question 5

A screening test was carried out among 120 people. 20 had the disease, and 40 showed a positive test result, out of which 15 had the disease. What is the specificity of the test?

Accepted Answer

75%

Answer

50%

Answer

65%

Answer

25%

Question 6

How much area under a normal distribution curve is covered by 
3 standard deviations from the mean?

Accepted Answer

99.7%

Answer

63.6%

Answer

66.6%

Answer

95%

Question 7

Which of the following is NOT a characteristic of a case-control study?

Accepted Answer

Attribute risk calculation

Answer

Measurement of exposure

Answer

Use of matching

Answer

Calculation of odds ratio

Question 8

A patient with a blood pressure of 210/120mmHg is classified under which type of hypertension?

Accepted Answer

Categorical

Answer

Numerical

Answer

Quantitative

Answer

Continuous

Question 9

What is the unit of study in a randomized controlled trial?

Accepted Answer

Patient

Answer

Population

Answer

Healthy person

Answer

Sample group

Question 10

If 25 persons are working on a project for 30 years, how many person-years of employment are generated?

Accepted Answer

750

Answer

75

Answer

120

Answer

1200

Biostatistics — MCQs

Biostatistics — MCQs

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