Rational Diagnostic Testing — MCQs
Calculate the sensitivity of a screening test: True Positives=80, False Negatives=20, True Negatives=90, False Positives=10
Specificity of a diagnostic test is defined as:
Which of the following statements about screening for disease is false?
If prevalence of a disease increases, what is true?
What does specificity in a diagnostic test measure?
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.
In a clinical study evaluating a new diagnostic test for a disease, the test was found to have 60 true positives out of 100 positive results. What is the positive predictive value of the test?
A patient with jaundice is found to have a pancreatic head mass. What is the best diagnostic test?
Which one of the following statements regarding predictive value of a positive test is true?
Which of the following statements about Wilson's disease is true?
Rational Diagnostic Testing Indian Medical PG Practice Questions and MCQs
Question 1: Calculate the sensitivity of a screening test: True Positives=80, False Negatives=20, True Negatives=90, False Positives=10
- A. 90%
- B. 85%
- C. 80% (Correct Answer)
- D. 95%
Explanation: ***80%*** - Sensitivity is calculated as **True Positives / (True Positives + False Negatives)**. In this case, 80 / (80 + 20) = 80/100, which equals 0.8 or 80%. - This metric represents the proportion of **actual positive cases** that are correctly identified by the test. *90%* - This value might represent the **specificity** (True Negatives / (True Negatives + False Positives)) if calculated with the given numbers (90 / (90 + 10) = 90%). - However, the question specifically asks for **sensitivity**, which is a different measure. *85%* - This percentage would be obtained if the total number of true positives and false negatives was 94 (e.g., 80 / 94), which is not the case here. - It does not correspond to the correct formula for **sensitivity** using the provided data. *95%* - This result would occur if the test correctly identified 95 out of 100 actual positive cases (e.g., 95 TP and 5 FN). - The given data of **80 True Positives** and **20 False Negatives** leads to a lower sensitivity.
Question 2: Specificity of a diagnostic test is defined as:
- A. 0.95 (Correct Answer)
- B. 0.05
- C. 0.4
- D. 0.8
Explanation: ***0.95*** - **Specificity** is the proportion of individuals without disease who test negative, calculated as **TN/(TN+FP)**. - A specificity of 0.95 (95%) indicates an excellent test that correctly identifies 95% of healthy individuals as negative. *0.05* - This value represents the **false positive rate** (1 - specificity), not specificity itself. - A specificity of 0.05 would mean only 5% of healthy individuals test negative, indicating a very poor test. *0.4* - This value is too low for specificity and could represent other test parameters like **positive predictive value**. - A specificity of 0.4 would incorrectly classify 60% of healthy individuals as positive, making the test clinically unreliable. *0.8* - This value typically represents **sensitivity**, which is the proportion of diseased individuals who test positive. - **Sensitivity** is calculated as **TP/(TP+FN)**, which is different from specificity that focuses on healthy individuals.
Question 3: Which of the following statements about screening for disease is false?
- A. Time consuming
- B. Arbitrary and final (Correct Answer)
- C. Rarely a basis for starting treatment without further confirmation
- D. Done on apparently healthy people
Explanation: ***Arbitrary and final*** ✓ **FALSE Statement - Correct Answer** - Screening tests are **NOT arbitrary** - they use **established diagnostic criteria**, validated cutoff points, and standardized protocols - Screening is **NOT final** - positive screening results always require **confirmatory diagnostic tests** before treatment decisions - This statement is false because screening follows **evidence-based protocols** and serves as a **preliminary step** in disease detection, not a definitive diagnosis *Time consuming* - TRUE Statement - Mass screening programs are indeed **time-consuming** due to large population coverage, scheduling logistics, and follow-up requirements - The process includes **participant recruitment**, **test administration**, **result notification**, and **tracking** of screen-positive individuals *Rarely a basis for starting treatment without further confirmation* - TRUE Statement - Screening tests are designed to **identify high-risk individuals** who require further evaluation, not to make treatment decisions - **Confirmatory diagnostic tests** with higher specificity are required before initiating treatment - Starting treatment based solely on screening results risks **overdiagnosis** and **unnecessary interventions** in false-positive cases *Done on apparently healthy people* - TRUE Statement - Screening specifically targets **asymptomatic populations** to detect disease in **preclinical stages** - The goal is **early detection** before symptoms appear, when intervention may be most effective - Distinguishes screening from diagnostic testing, which is performed on symptomatic individuals
Question 4: If prevalence of a disease increases, what is true?
- A. PPV increases (Correct Answer)
- B. PPV decreases
- C. No effect on PPV
- D. NPV increases
Explanation: ***PPV increases*** - As the **prevalence** of a disease increases in a population, the **pre-test probability** of an individual having the disease also increases. - A higher pre-test probability directly leads to an **increased Positive Predictive Value (PPV)**, meaning a positive test result is more likely to indicate true disease. - **Formula connection**: PPV = (Sensitivity × Prevalence) / [(Sensitivity × Prevalence) + ((1-Specificity) × (1-Prevalence))] *PPV decreases* - This statement is incorrect; an increase in disease prevalence is associated with an **increase**, not a decrease, in PPV. - **Decreased prevalence** would lead to a decrease in PPV, as a positive test result becomes more likely to be a false positive. *No effect on PPV* - This is incorrect. **Prevalence** is a crucial factor in determining the PPV of a diagnostic test. - PPV is directly influenced by the prevalence of the disease in the population being tested, alongside the test's sensitivity and specificity. *NPV increases* - This statement is incorrect. When prevalence increases, the **Negative Predictive Value (NPV)** actually **decreases**, not increases. - A higher prevalence means that even a negative test result is less reassuring that the individual does not have the disease, as more true cases exist in the population.
Question 5: What does specificity in a diagnostic test measure?
- A. True positive
- B. True negative (Correct Answer)
- C. False positive
- D. False negative
Explanation: ***True negative*** - Specificity measures the **proportion of true negatives** correctly identified by the test. - It indicates the test's ability to correctly identify individuals **without the disease** who test negative. - **Formula: Specificity = TN / (TN + FP)** where TN = True Negatives, FP = False Positives. *True positive* - **True positives** are measured by **sensitivity**, not specificity. - Sensitivity measures the proportion of people with the disease who test positive. *False positive* - **False positives** reduce specificity but are not what specificity measures. - High specificity means fewer false positives (more specific for the disease). *False negative* - **False negatives** are related to **sensitivity**, not specificity. - A test with low sensitivity will have a higher rate of false negatives.
Question 6: 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.
- A. All positives identified by the test assumed as true positives (100%)
- B. True positives divided by total actual positives (90%) (Correct Answer)
- C. Underestimated true positives divided by total actual positives (80%)
- D. Total positives identified by the test divided by total actual positives (90%)
Explanation: ***True positives divided by total actual positives (90%)*** - **Sensitivity** is the proportion of true positives correctly identified by a screening test among all individuals who actually have the disease. It is calculated by (Number of True Positives) / (Total Number of Diseased Individuals). - In this case, 90 people screened positive and were confirmed as **true positives**. The total number of people with the disease (actual positives) is 100. So, sensitivity = 90/100 = **90%**. *Total positives identified by the test divided by total actual positives (90%)* - While this option states the correct percentage (90%), the phrasing "total positives identified by the test" is misleading terminology. In screening test evaluation, this could be confused with all test positives (which would include false positives if they existed). - The correct terminology is "true positives" divided by "total actual positives," not "total positives identified by the test." The distinction is important: true positives are confirmed cases, while test positives might include false positives. *All positives identified by the test assumed as true positives (100%)* - This option incorrectly assumes that because all 90 screening positives were confirmed as true positives, the sensitivity must be 100%. However, sensitivity measures how many of ALL diseased individuals were caught, not just those who screened positive. - There were 100 actual diseased individuals, and only 90 were identified by the screening test; therefore, the sensitivity cannot be 100%. The test missed 10 diseased individuals (false negatives). *Underestimated true positives divided by total actual positives (80%)* - This option presents an arbitrary percentage that does not reflect the given data. There is no information to suggest that the true positives were underestimated or that the calculation would result in 80%. - The actual number of true positives (90) and actual positives (100) directly leads to a sensitivity calculation of 90%, not 80%.
Question 7: In a clinical study evaluating a new diagnostic test for a disease, the test was found to have 60 true positives out of 100 positive results. What is the positive predictive value of the test?
- A. 40/100
- B. 60/100 (Correct Answer)
- C. 40/300
- D. 240/300
Explanation: ***60/100*** - The **positive predictive value (PPV)** is the proportion of **true positives** among all positive test results. - Given 60 true positives out of 100 positive results, the calculation is 60 divided by 100. *40/100* - This value would represent the number of **false positives** (positive test results that are actually negative) out of all positive test results, which is not the positive predictive value. - The PPV is specifically concerned with the reliability of a positive result indicating the presence of the disease. *40/300* - This fraction does not correspond to a standard measure of diagnostic test validity given the provided information regarding true positives and total positive results. - It might incorrectly combine disparate data points or represent a miscalculation based on other variables not supplied. *240/300* - This value is not derived from the provided numbers for true positives and total positive results in the context of positive predictive value. - It could potentially represent sensitivity or specificity calculations, but it is not the **positive predictive value**.
Question 8: A patient with jaundice is found to have a pancreatic head mass. What is the best diagnostic test?
- A. CT scan (Correct Answer)
- B. ERCP
- C. Ultrasound
- D. MRI
Explanation: ***CT scan*** - A **CT scan of the abdomen with contrast** is the initial investigation of choice for suspected pancreatic head mass due to its high diagnostic accuracy [1]. It provides detailed images of the pancreas, surrounding structures, and can help stage the disease [1]. - It effectively visualizes the **mass, evaluates for vascular invasion, and detects metastatic disease**, which are crucial for treatment planning [1]. *ERCP* - **Endoscopic retrograde cholangiopancreatography (ERCP)** is a therapeutic procedure primarily used for bile duct decompression, particularly in cases of obstructive jaundice [2]. - While it can visualize the bile ducts and pancreatic duct, it is **invasive** and not typically used as the primary diagnostic imaging modality for a pancreatic mass itself. *Ultrasound* - **Abdominal ultrasound** can detect a mass and dilated bile ducts, but it is operator-dependent and often has **limited sensitivity** for small pancreatic lesions, particularly in obese patients or those with bowel gas [1]. - It is often used as a first-line screening tool for jaundice but is usually followed by more definitive imaging like CT or MRI due to its **limited detail and penetration**. *MRI* - **Magnetic Resonance Imaging (MRI) with MRCP (Magnetic Resonance Cholangiopancreatography)** provides excellent soft tissue contrast, especially for assessing bile duct obstruction and assessing for vascular invasion [1]. - While highly sensitive, it is **more expensive and less readily available** than CT, making CT the preferred initial diagnostic test.
Question 9: Which one of the following statements regarding predictive value of a positive test is true?
- A. It does not tell about diagnostic power of test
- B. The more prevalent the disease, the less accurate the test is
- C. It tells the probability that a patient with positive test does not have the disease in question
- D. It tells the probability that a patient with positive test has the disease in question (Correct Answer)
Explanation: ***It tells the probability that a patient with positive test has the disease in question*** - The **positive predictive value (PPV)** is the probability that an individual with a **positive test result** actually has the disease. - It helps clinicians understand the likelihood of a true positive diagnosis in a given population. *It does not tell about diagnostic power of test* - While PPV is influenced by disease prevalence, it is a crucial measure of a test's **diagnostic utility** in a clinical setting. - It helps in interpreting the meaning of a positive result for an individual patient. *The more prevalent the disease, the less accurate the test is* - This statement is incorrect; the **higher the prevalence**, the **higher the positive predictive value** (PPV) of a test, assuming sensitivity and specificity remain constant. - Test accuracy (sensitivity and specificity) is independent of disease prevalence. *It tells the probability that a patient with positive test does not have the disease in question* - This describes the **false positive rate** or **1 - positive predictive value (PPV)**, not the PPV itself. - The PPV specifically refers to the probability of having the disease given a positive result.
Question 10: Which of the following statements about Wilson's disease is true?
- A. Low serum ceruloplasmin and low urinary copper
- B. Low serum ceruloplasmin and high urinary copper (Correct Answer)
- C. High serum ceruloplasmin and low urinary copper
- D. High serum ceruloplasmin and high urinary copper
Explanation: ***Low serum ceruloplasmin and high urinary copper*** - In **Wilson's disease**, there is a defect in **copper transport**, leading to impaired incorporation of copper into ceruloplasmin and reduced biliary excretion. - This results in **low serum ceruloplasmin** levels (since ceruloplasmin is the main copper-carrying protein in the blood) and **increased urinary copper excretion** as the body attempts to eliminate excess free copper. *Low serum ceruloplasmin and low urinary copper* - While **low serum ceruloplasmin** is characteristic, **low urinary copper** would indicate adequate copper elimination or a different condition, which is not the case for Wilson's disease. - Patients with Wilson's disease have **excess copper accumulation**, and increased urinary excretion is a compensatory mechanism [1]. *High serum ceruloplasmin and low urinary copper* - **High serum ceruloplasmin** is inconsistent with Wilson's disease, as ceruloplasmin levels are typically low due to the impaired copper binding. - **Low urinary copper** excretion would indicate normal or low total body copper, which contradicts the copper overload seen in Wilson's disease. *High serum ceruloplasmin and high urinary copper* - **High serum ceruloplasmin** would suggest normal or increased ceruloplasmin synthesis or release, which is contrary to the pathophysiology of Wilson's disease. - Although **high urinary copper** is a feature, it isn't accompanied by high ceruloplasmin in this condition, as ceruloplasmin is primarily involved in carrying copper in the blood rather than excreting excess copper [1].
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