Positive predictive value (PPV) US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Positive predictive value (PPV). These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Positive predictive value (PPV) US Medical PG Question 1: A scientist in Chicago is studying a new blood test to detect Ab to EBV with increased sensitivity and specificity. So far, her best attempt at creating such an exam reached 82% sensitivity and 88% specificity. She is hoping to increase these numbers by at least 2 percent for each value. After several years of work, she believes that she has actually managed to reach a sensitivity and specificity much greater than what she had originally hoped for. She travels to China to begin testing her newest blood test. She finds 2,000 patients who are willing to participate in her study. Of the 2,000 patients, 1,200 of them are known to be infected with EBV. The scientist tests these 1,200 patients' blood and finds that only 120 of them tested negative with her new exam. Of the patients who are known to be EBV-free, only 20 of them tested positive. Given these results, which of the following correlates with the exam's specificity?
- A. 82%
- B. 90%
- C. 84%
- D. 86%
- E. 98% (Correct Answer)
Positive predictive value (PPV) Explanation: ***98%***
- **Specificity** measures the proportion of **true negatives** among all actual negatives.
- In this case, 800 patients are known to be EBV-free (actual negatives), and 20 of them tested positive (false positives). This means 800 - 20 = 780 tested negative (true negatives). Specificity = (780 / 800) * 100% = **98%**.
*82%*
- This value represents the *original sensitivity* before the scientist’s new attempts to improve the test.
- It does not reflect the *newly calculated specificity* based on the provided data.
*90%*
- This value represents the *newly calculated sensitivity* of the test, not the specificity.
- Out of 1200 EBV-infected patients, 120 tested negative (false negatives), meaning 1080 tested positive (true positives). Sensitivity = (1080 / 1200) * 100% = 90%.
*84%*
- This percentage is not directly derived from the information given for either sensitivity or specificity after the new test results.
- It does not correspond to any of the calculated values for the new test's performance.
*86%*
- This percentage is not directly derived from the information given for either sensitivity or specificity after the new test results.
- It does not correspond to any of the calculated values for the new test's performance.
Positive predictive value (PPV) US Medical PG Question 2: A 36-year-old female presents to clinic inquiring about the meaning of a previous negative test result from a new HIV screening test. The efficacy of this new screening test for HIV has been assessed by comparison against existing gold standard detection of HIV RNA via PCR. The study includes 1000 patients, with 850 HIV-negative patients (by PCR) receiving a negative test result, 30 HIV-negative patients receiving a positive test result, 100 HIV positive patients receiving a positive test result, and 20 HIV positive patients receiving a negative test result. Which of the following is most likely to increase the negative predictive value for this test?
- A. Decreased prevalence of HIV in the tested population (Correct Answer)
- B. Increased prevalence of HIV in the tested population
- C. Increased number of false positive test results
- D. Increased number of false negative test results
- E. Decreased number of false positive test results
Positive predictive value (PPV) Explanation: ***Decreased prevalence of HIV in the tested population***
- A **lower prevalence** of a disease in the population means there are fewer actual cases, making a **negative test result** more reliable in ruling out the disease.
- This increases the probability that a person with a negative test truly does not have the disease, thus elevating the **negative predictive value (NPV)**.
*Increased prevalence of HIV in the tested population*
- A **higher prevalence** means there are more actual cases of HIV in the population.
- In this scenario, a negative test result is less reassuring, as there's a greater chance of missing a true positive case, leading to a **decreased NPV**.
*Increased number of false positive test results*
- **False positives** are instances where a test indicates disease when it's not present; they do not directly impact the ability of a negative test to predict absence of disease.
- While they affect the **positive predictive value (PPV)**, they do not directly alter the reliability of a negative result to exclude disease, so the NPV is not increased.
*Increased number of false negative test results*
- **False negatives** occur when a test indicates no disease, but the disease is actually present.
- An increase in false negatives directly implies that a negative test result is less trustworthy, leading to a **decrease in the NPV**.
*Decreased number of false positive test results*
- A decrease in false positive results primarily improves the **positive predictive value (PPV)**.
- While it indicates a more accurate test overall, it does not directly affect NPV, which measures the reliability of a negative test result in ruling out disease.
Positive predictive value (PPV) US Medical PG Question 3: A 25-year-old man with a genetic disorder presents for genetic counseling because he is concerned about the risk that any children he has will have the same disease as himself. Specifically, since childhood he has had difficulty breathing requiring bronchodilators, inhaled corticosteroids, and chest physiotherapy. He has also had diarrhea and malabsorption requiring enzyme replacement therapy. If his wife comes from a population where 1 in 10,000 people are affected by this same disorder, which of the following best represents the likelihood a child would be affected as well?
- A. 0.01%
- B. 2%
- C. 0.5%
- D. 1% (Correct Answer)
- E. 50%
Positive predictive value (PPV) Explanation: ***Correct Option: 1%***
- The patient's symptoms (difficulty breathing requiring bronchodilators, inhaled corticosteroids, and chest physiotherapy; diarrhea and malabsorption requiring enzyme replacement therapy) are classic for **cystic fibrosis (CF)**, an **autosomal recessive disorder**.
- For an autosomal recessive disorder with a prevalence of 1 in 10,000 in the general population, **q² = 1/10,000**, so **q = 1/100 = 0.01**. The carrier frequency **(2pq)** is approximately **2q = 2 × (1/100) = 1/50 = 0.02**.
- The affected man is **homozygous recessive (aa)** and will always pass on the recessive allele. His wife has a **1/50 chance of being a carrier (Aa)**. If she is a carrier, she has a **1/2 chance of passing on the recessive allele**.
- Therefore, the probability of an affected child = **(Probability wife is a carrier) × (Probability wife passes recessive allele) = 1/50 × 1/2 = 1/100 = 1%**.
*Incorrect Option: 0.01%*
- This percentage is too low and does not correctly account for the carrier frequency in the population and the probability of transmission from a carrier mother.
*Incorrect Option: 2%*
- This represents approximately the carrier frequency (1/50 ≈ 2%), but does not account for the additional 1/2 probability that a carrier mother would pass on the recessive allele.
*Incorrect Option: 0.5%*
- This value would be correct if the carrier frequency were 1/100 instead of 1/50, which does not match the given population prevalence.
*Incorrect Option: 50%*
- **50%** would be the risk if both parents were carriers of an autosomal recessive disorder (1/4 chance = 25% for affected, but if we know one parent passes the allele, conditional probability changes). More accurately, 50% would apply if the disorder were **autosomal dominant** with one affected parent, which is not the case here.
Positive predictive value (PPV) US Medical PG Question 4: An infectious disease investigator is evaluating the diagnostic accuracy of a new interferon-gamma-based assay for diagnosing tuberculosis in patients who have previously received a Bacillus Calmette-Guérin (BCG) vaccine. Consenting participants with a history of BCG vaccination received an interferon-gamma assay and were subsequently evaluated for tuberculosis by sputum culture. Results of the study are summarized in the table below.
Tuberculosis, confirmed by culture No tuberculosis Total
Positive interferon-gamma assay 90 6 96
Negative interferon-gamma assay 10 194 204
Total 100 200 300
Based on these results, what is the sensitivity of the interferon-gamma-based assay for the diagnosis of tuberculosis in this study?
- A. 90/96
- B. 100/300
- C. 194/200
- D. 90/100 (Correct Answer)
- E. 194/204
Positive predictive value (PPV) Explanation: ***90/100***
- **Sensitivity** measures the proportion of **true positive** cases that are correctly identified by the test.
- In this study, there are 90 true positive results (positive interferon-gamma assay in patients with confirmed tuberculosis) out of a total of 100 individuals with confirmed tuberculosis (90 + 10).
*90/96*
- This calculation represents the **positive predictive value** (90 true positives / 96 total positive tests).
- It answers the question: "If the test is positive, what is the likelihood that the patient actually has the disease?"
*100/300*
- This value represents the prevalence of tuberculosis in the study population (100 confirmed cases / 300 total participants).
- It does not reflect a measure of the test's diagnostic accuracy.
*194/200*
- This value represents the **specificity** of the test (194 true negatives / 200 total individuals without tuberculosis).
- Specificity measures the proportion of true negative cases that are correctly identified by the test.
*194/204*
- This calculation represents the **negative predictive value** (194 true negatives / 204 total negative tests).
- It answers the question: "If the test is negative, what is the likelihood that the patient does not have the disease?"
Positive predictive value (PPV) US Medical PG Question 5: A scientist in Boston is studying a new blood test to detect Ab to the parainfluenza virus with increased sensitivity and specificity. So far, her best attempt at creating such an exam reached 82% sensitivity and 88% specificity. She is hoping to increase these numbers by at least 2 percent for each value. After several years of work, she believes that she has actually managed to reach a sensitivity and specificity even greater than what she had originally hoped for. She travels to South America to begin testing her newest blood test. She finds 2,000 patients who are willing to participate in her study. Of the 2,000 patients, 1,200 of them are known to be infected with the parainfluenza virus. The scientist tests these 1,200 patients’ blood and finds that only 120 of them tested negative with her new test. Of the following options, which describes the sensitivity of the test?
- A. 82%
- B. 86%
- C. 98%
- D. 90% (Correct Answer)
- E. 84%
Positive predictive value (PPV) Explanation: ***90%***
- **Sensitivity** is calculated as the number of **true positives** divided by the total number of individuals with the disease (true positives + false negatives).
- In this scenario, there were 1200 infected patients (total diseased), and 120 of them tested negative (false negatives). Therefore, 1200 - 120 = 1080 patients tested positive (true positives). The sensitivity is 1080 / 1200 = 0.90, or **90%**.
*82%*
- This value was the **original sensitivity** of the test before the scientist improved it.
- The question states that the scientist believes she has achieved a sensitivity "even greater than what she had originally hoped for."
*86%*
- This value is not directly derivable from the given data for the new test's sensitivity.
- It might represent an intermediate calculation or an incorrect interpretation of the provided numbers.
*98%*
- This would imply only 24 false negatives out of 1200 true disease cases, which is not the case (120 false negatives).
- A sensitivity of 98% would be significantly higher than the calculated 90% and the initial stated values.
*84%*
- This value is not derived from the presented data regarding the new test's performance.
- It could be mistaken for an attempt to add 2% to the original 82% sensitivity, but the actual data from the new test should be used.
Positive predictive value (PPV) US Medical PG Question 6: A 6-month-old male presents for a routine visit to his pediatrician. Two months ago, the patient was seen for tachypnea and wheezing, and diagnosed with severe respiratory syncytial virus (RSV) bronchiolitis. After admission to the hospital and supportive care, the patient recovered and currently is not experiencing any trouble breathing. Regarding the possibility of future reactive airway disease, which of the following statements is most accurate?
- A. “There is no clear relationship between RSV and the development of asthma.”
- B. “Your child has a greater than 20% chance of developing asthma” (Correct Answer)
- C. “Your child’s risk of asthma is less than the general population.”
- D. “Your child has a less than 5% chance of developing asthma”
- E. “Your child’s risk of asthma is the same as the general population.”
Positive predictive value (PPV) Explanation: ***“Your child has a greater than 20% chance of developing asthma”***
- Severe **RSV bronchiolitis** in infancy is a significant risk factor for the development of **recurrent wheezing** and **childhood asthma**.
- Studies estimate that a substantial proportion, often greater than 20%, of infants with severe RSV bronchiolitis will go on to develop **asthma** later in childhood.
*“There is no clear relationship between RSV and the development of asthma.”*
- This statement is incorrect as there is a **well-established link** between severe RSV infection in early life and an increased risk of developing **asthma**.
- Numerous epidemiological and longitudinal studies have documented this association.
*“Your child’s risk of asthma is less than the general population.”*
- This is incorrect, as severe RSV infection **increases** the risk of asthma, not decreases it.
- Children with a history of severe RSV have a **higher incidence** of asthma compared to the general pediatric population.
*“Your child has a less than 5% chance of developing asthma”*
- This percentage is **too low** given the known association between severe RSV bronchiolitis and subsequent asthma.
- The actual risk is considerably higher, typically falling into the range of 20-50% for those with severe RSV.
*“Your child’s risk of asthma is the same as the general population.”*
- This statement is inaccurate because severe RSV infection in infancy is a recognized independent **risk factor** for **asthma development**.
- Therefore, the child's risk is elevated above that of the general population.
Positive predictive value (PPV) US Medical PG Question 7: A pharmaceutical corporation is developing a research study to evaluate a novel blood test to screen for breast cancer. They enrolled 800 patients in the study, half of which have breast cancer. The remaining enrolled patients are age-matched controls who do not have the disease. Of those in the diseased arm, 330 are found positive for the test. Of the patients in the control arm, only 30 are found positive. What is this test’s sensitivity?
- A. 330 / (330 + 30)
- B. 330 / (330 + 70) (Correct Answer)
- C. 370 / (30 + 370)
- D. 370 / (70 + 370)
- E. 330 / (400 + 400)
Positive predictive value (PPV) Explanation: ***330 / (330 + 70)***
- **Sensitivity** measures the proportion of actual **positives** that are correctly identified as such.
- In this study, there are **400 diseased patients** (half of 800). Of these, 330 tested positive (true positives), meaning 70 tested negative (false negatives). So sensitivity is **330 / (330 + 70)**.
*330 / (330 + 30)*
- This calculation represents the **positive predictive value**, which is the probability that subjects with a positive screening test truly have the disease. It uses **true positives / (true positives + false positives)**.
- It does not correctly calculate **sensitivity**, which requires knowing the total number of diseased individuals.
*370 / (30 + 370)*
- This expression is attempting to calculate **specificity**, which is the proportion of actual negatives that are correctly identified. It would be **true negatives / (true negatives + false positives)**.
- However, the numbers used are incorrect for specificity in this context given the data provided.
*370 / (70 + 370)*
- This formula is an incorrect combination of values and does not represent any standard epidemiological measure like **sensitivity** or **specificity**.
- It is attempting to combine false negatives (70) and true negatives (370 from control arm) in a non-standard way.
*330 / (400 + 400)*
- This calculation attempts to divide true positives by the total study population (800 patients).
- This metric represents the **prevalence of true positives within the entire study cohort**, not the test's **sensitivity**.
Positive predictive value (PPV) US Medical PG Question 8: A medical research study is beginning to evaluate the positive predictive value of a novel blood test for non-Hodgkin’s lymphoma. The diagnostic arm contains 700 patients with NHL, of which 400 tested positive for the novel blood test. In the control arm, 700 age-matched control patients are enrolled and 0 are found positive for the novel test. What is the PPV of this test?
- A. 400 / (400 + 0) (Correct Answer)
- B. 700 / (700 + 300)
- C. 400 / (400 + 300)
- D. 700 / (700 + 0)
- E. 700 / (400 + 400)
Positive predictive value (PPV) Explanation: ***400 / (400 + 0) = 1.0 or 100%***
- The **positive predictive value (PPV)** is calculated as **True Positives / (True Positives + False Positives)**.
- In this scenario, **True Positives (TP)** are the 400 patients with NHL who tested positive, and **False Positives (FP)** are 0, as no control patients tested positive.
- This gives a PPV of 400/400 = **1.0 or 100%**, indicating that all patients who tested positive actually had the disease.
*700 / (700 + 300)*
- This calculation does not align with the formula for PPV based on the given data.
- The denominator `(700+300)` suggests an incorrect combination of various patient groups.
*400 / (400 + 300)*
- The denominator `(400+300)` incorrectly includes 300, which is the number of **False Negatives** (patients with NHL who tested negative), not False Positives.
- PPV focuses on the proportion of true positives among all positive tests, not all diseased individuals.
*700 / (700 + 0)*
- This calculation incorrectly uses the total number of patients with NHL (700) as the numerator, rather than the number of positive test results in that group.
- The numerator should be the **True Positives** (400), not the total number of diseased individuals.
*700 / (400 + 400)*
- This calculation uses incorrect values for both the numerator and denominator, not corresponding to the PPV formula.
- The numerator 700 represents the total number of patients with the disease, not those who tested positive, and the denominator incorrectly sums up values that don't represent the proper PPV calculation.
Positive predictive value (PPV) US Medical PG Question 9: A population is studied for risk factors associated with testicular cancer. Alcohol exposure, smoking, dietary factors, social support, and environmental exposure are all assessed. The researchers are interested in the incidence and prevalence of the disease in addition to other outcomes. Which pair of studies would best assess the 1. incidence and 2. prevalence?
- A. 1. Prospective cohort study 2. Cross sectional study (Correct Answer)
- B. 1. Prospective cohort study 2. Retrospective cohort study
- C. 1. Cross sectional study 2. Retrospective cohort study
- D. 1. Case-control study 2. Prospective cohort study
- E. 1. Clinical trial 2. Cross sectional study
Positive predictive value (PPV) Explanation: ***1. Prospective cohort study 2. Cross sectional study***
- A **prospective cohort study** is ideal for measuring **incidence** (new cases over time) because it follows a group of individuals forward in time to observe who develops the disease.
- A **cross-sectional study** is suitable for measuring **prevalence** (existing cases at a specific point in time) as it surveys a population at one moment to determine the proportion with the disease.
*1. Prospective cohort study 2. Retrospective cohort study*
- A **retrospective cohort study** assesses past exposures and outcomes and can measure incidence, but it is not the primary choice for prevalence.
- While a prospective cohort study is appropriate for incidence, a retrospective cohort study is less suited for determining current prevalence.
*1. Cross sectional study 2. Retrospective cohort study*
- A **cross-sectional study** measures prevalence, not incidence, as it captures disease status at a single point in time.
- A **retrospective cohort study** looks back in time to identify past exposures and subsequent outcomes, which is not the best method for current prevalence.
*1. Case-control study 2. Prospective cohort study*
- A **case-control study** compares exposures between individuals with a disease (cases) and those without (controls) and is best for studying rare diseases and estimating odds ratios, not incidence or prevalence directly.
- A **prospective cohort study** is suitable for incidence, but a case-control study is not for incidence or prevalence.
*1. Clinical trial 2. Cross sectional study*
- A **clinical trial** is an experimental study designed to test the efficacy of interventions and is not primarily used to measure disease incidence or prevalence in a general population.
- While a cross-sectional study is appropriate for prevalence, a clinical trial is not designed for incidence measurement.
Positive predictive value (PPV) US Medical PG Question 10: Many large clinics have noticed that the prevalence of primary biliary cholangitis (PBC) has increased significantly over the past 20 years. An epidemiologist is working to identify possible reasons for this. After analyzing a series of nationwide health surveillance databases, the epidemiologist finds that the incidence of PBC has remained stable over the past 20 years. Which of the following is the most plausible explanation for the increased prevalence of PBC?
- A. Improved quality of care for PBC (Correct Answer)
- B. Increased availability of diagnostic testing for PBC
- C. Increased exposure to environmental risk factors for PBC
- D. Increased awareness of PBC among clinicians
- E. Increased average age of the population at risk for PBC
Positive predictive value (PPV) Explanation: ***Improved quality of care for PBC***
- This leads to a **longer survival time** for patients with PBC. When incidence remains stable but patients live longer, the cumulative number of living cases (prevalence) naturally increases.
- An increase in prevalence with stable incidence is a classic indicator of **improved patient survival** due to better management or treatment.
*Increased availability of diagnostic testing for PBC*
- This would primarily impact the **incidence** of PBC by detecting more cases that were previously undiagnosed. The question states that the incidence has remained stable.
- While improved diagnostics might initially increase *reported* incidence, if the true incidence is stable, it wouldn't explain a sustained rise in prevalence without a corresponding change in incidence or survival.
*Increased exposure to environmental risk factors for PBC*
- This would directly lead to an **increase in the incidence** of PBC, as more people would be developing the disease.
- Since the incidence is stable, an increase in environmental risk factors is not the most plausible explanation for increased prevalence.
*Increased awareness of PBC among clinicians*
- Similar to increased diagnostic testing, increased awareness would likely lead to the diagnosis of more new cases, thus **increasing the incidence** of PBC.
- A stable incidence despite increased awareness means that the actual rate of new cases developing the disease has not changed, ruling this out as the primary cause of increased prevalence.
*Increased average age of the population at risk for PBC*
- An aging population could potentially increase the incidence of age-related diseases. However, if the **incidence has remained stable**, it implies that even with an older population, the rate of new diagnoses has not increased.
- While age is a risk factor for PBC, an increase in prevalence without a change in incidence suggests a factor influencing the duration of the disease rather than its onset.
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