Negative predictive value (NPV) US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Negative predictive value (NPV). These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Negative predictive value (NPV) US Medical PG Question 1: A group of investigators who are studying individuals infected with Trypanosoma cruzi is evaluating the ELISA absorbance cutoff value of serum samples for diagnosis of infection. The previous cutoff point is found to be too high, and the researchers decide to lower the threshold by 15%. Which of the following outcomes is most likely to result from this decision?
- A. Increased negative predictive value (Correct Answer)
- B. Unchanged true positive results
- C. Decreased sensitivity
- D. Increased specificity
- E. Increased positive predictive value
Negative predictive value (NPV) Explanation: ***Increased negative predictive value***
- Lowering the absorbance cutoff for the ELISA test makes it **easier to test positive**, which increases **sensitivity** (more true positives are detected, fewer false negatives occur).
- **Negative predictive value (NPV)** is the probability that a person who tests negative truly does not have the disease: NPV = TN / (TN + FN).
- When the cutoff is lowered, **fewer infected individuals will be missed** (false negatives decrease). This reduction in false negatives improves the NPV because there are fewer disease-positive individuals in the "test-negative" group.
- Therefore, a negative test result becomes **more reliable at ruling out infection**, increasing the NPV.
*Unchanged true positive results*
- Lowering the cutoff means that samples with lower absorbance values (previously below threshold) from truly infected individuals will now be classified as positive.
- This directly **increases the number of true positive results**, not keeps them unchanged.
- The whole purpose of lowering the threshold is to capture more infected cases.
*Decreased sensitivity*
- **Sensitivity** = TP / (TP + FN), the ability to correctly identify those with disease.
- Lowering the cutoff **increases sensitivity** by making it easier to test positive, thereby capturing more true positives and reducing false negatives.
- A lower threshold would never decrease sensitivity—it does the opposite.
*Increased specificity*
- **Specificity** = TN / (TN + FP), the ability to correctly identify those without disease.
- Lowering the cutoff causes some uninfected individuals to now test positive (false positives increase).
- This **decreases specificity**, not increases it, as fewer true negatives remain.
*Increased positive predictive value*
- **PPV** = TP / (TP + FP), the probability that a positive test indicates true disease.
- While lowering the cutoff increases true positives, it also **increases false positives more substantially**.
- The increased false positives dilute the proportion of true positives among all positive results, thereby **decreasing the PPV**.
Negative predictive value (NPV) US Medical PG Question 2: 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%
Negative predictive value (NPV) 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.
Negative predictive value (NPV) US Medical PG Question 3: A 27-year-old man interested in pre-exposure therapy for HIV (PrEP) is being evaluated to qualify for a PrEP study. In order to qualify, patients must be HIV- and hepatitis B- and C-negative. Any other sexually transmitted infections require treatment prior to initiation of PrEP. The medical history is positive for a prior syphilis infection and bipolar affective disorder, for which he takes lithium. On his next visit, the liver and renal enzymes are within normal ranges. HIV and hepatitis B and C tests are negative. Which of the following about the HIV test is true?
- A. It is a quantitative test used for screening purposes.
- B. It is a qualitative test used for screening purposes. (Correct Answer)
- C. A secondary reagent is needed to interpret the results.
- D. A known antigen binds directly to the patient's serum.
- E. An unknown antigen binds to the known serum.
Negative predictive value (NPV) Explanation: ***It is a qualitative test used for screening purposes.***
- **HIV screening tests** (e.g., 4th generation antibody/antigen combination assays) are typically **qualitative**, meaning they detect the presence or absence of HIV markers, not their exact amount.
- These tests are primarily used for broad **screening** of populations to identify potential cases of HIV infection.
*It is a quantitative test used for screening purposes.*
- **Quantitative tests** for HIV, such as viral load tests, measure the amount of virus in the blood and are typically used for monitoring disease progression or treatment effectiveness, not for initial screening.
- Screening tests are designed for high sensitivity to detect infection, even with low viral loads or early antibody responses, making a quantitative measurement less relevant for initial screening.
*A secondary reagent is needed to interpret the results.*
- While some complex immunoassays might involve multiple steps, modern **HIV screening tests** often use advanced technologies that directly yield results, making a separate secondary reagent for interpretation generally unnecessary.
- The results are typically indicated by a color change or a signal detected by an instrument, without requiring an additional interpretive reagent.
*A known antigen binds directly to the patient's serum.*
- **HIV antibody tests** detect **antibodies** produced by the patient's immune system in response to HIV infection.
- In such tests, **known HIV antigens** (from the test kit) bind to **HIV-specific antibodies present in the patient's serum**, not to serum components directly.
- This option is incorrect because it omits the critical role of antibodies as the target molecules being detected.
*An unknown antigen binds to the known serum.*
- This statement describes a different type of immunological assay where an unknown antigen is being identified using a known antibody, which is contrary to how **HIV screening tests** for infection are typically structured.
- **HIV screening tests** use known components (e.g., HIV antigens or antibodies) in the test kit to detect unknown components (e.g., HIV antibodies or viral antigens) in the patient's sample.
Negative predictive value (NPV) US Medical PG Question 4: A novel PET radiotracer is being evaluated for its ability to aid in the diagnosis of Alzheimer’s disease (AD). The study decides to use a sample size of 1,000 patients, and half of the patients enrolled have AD. In the group of patients with AD, 400 are found positive on the novel type of PET imaging examination. In the control group, 50 are found positive. What is the PPV of this novel exam?
- A. 400 / (400+50) (Correct Answer)
- B. 450 / (450 + 100)
- C. 400 / (400+100)
- D. 450 / (450 + 50)
- E. 400 / (400 + 150)
Negative predictive value (NPV) Explanation: ***400 / (400+50)***
- The **Positive Predictive Value (PPV)** is the probability that subjects with a positive test result actually have the disease. It's calculated as **True Positives / (True Positives + False Positives)**.
- In this scenario, **True Positives** are 400 (patients with AD who tested positive), and **False Positives** are 50 (control patients without AD who tested positive).
*450 / (450 + 100)*
- This calculation incorrectly includes **False Negatives** (450, total AD patients - true positives) in the numerator or denominator for PPV, and misidentifies other components.
- The formula for PPV specifically focuses on positive test results and the proportion of those that are truly disease-positive.
*400 / (400+100)*
- This option correctly identifies **True Positives** as 400 but incorrectly assumes **False Positives** are 100.
- The problem states that 50 control patients (without AD) tested positive, which are the false positives.
*450 / (450 + 50)*
- This formula incorrectly uses **450** as the number of **True Positives**, which represents the total number of patients with AD testing positive and negative (400 TP + 100 FN).
- PPV only considers those who tested positive in its numerator.
*400 / (400 + 150)*
- While 400 is correctly identified as **True Positives**, the **False Positives** are incorrectly stated as 150.
- The problem explicitly states that 50 control patients were found positive, making 50 the correct number for false positives.
Negative predictive value (NPV) US Medical PG Question 5: 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)
Negative predictive value (NPV) 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**.
Negative predictive value (NPV) US Medical PG Question 6: A survey was conducted in a US midwestern town in an effort to assess maternal mortality over the past year. The data from the survey are given in the table below:
Women of childbearing age 250,000
Maternal deaths 2,500
Number of live births 100, 000
Number of deaths of women of childbearing age 7,500
Maternal death is defined as the death of a woman while pregnant or within 42 days of termination of pregnancy from any cause related to or aggravated by, the pregnancy. Which of the following is the maternal mortality rate in this midwestern town?
- A. 1,000 per 100,000 live births
- B. 33 per 100,000 live births
- C. 3,000 per 100,000 live births
- D. 33,300 per 100,000 live births
- E. 2,500 per 100,000 live births (Correct Answer)
Negative predictive value (NPV) Explanation: ***2,500 per 100,000 live births***
- The maternal mortality rate is calculated as the number of **maternal deaths** per 100,000 **live births**. The given data directly provide these values.
- Calculation: (2,500 maternal deaths / 100,000 live births) × 100,000 = **2,500 per 100,000 live births**.
*1,000 per 100,000 live births*
- This value is incorrect as it does not align with the provided numbers for maternal deaths and live births in the calculation.
- It might result from a miscalculation or using incorrect numerator/denominator values from the dataset.
*33 per 100,000 live births*
- This value is significantly lower than the correct rate and suggests a substantial error in calculation or an incorrect understanding of how the maternal mortality rate is derived.
- It could potentially result from dividing the number of live births by maternal deaths, which is the inverse of the correct formula.
*3,000 per 100,000 live births*
- This option is close to the correct answer but slightly higher, indicating a possible calculation error, for instance, including non-maternal deaths or other causes of deaths in the numerator.
- The definition of maternal death is specific to pregnancy-related or aggravated causes, so extraneous deaths would inflate the rate.
*33,300 per 100,000 live births*
- This figure results from incorrectly calculating the proportion of maternal deaths among all deaths of women of childbearing age: (2,500 / 7,500) × 100,000 = 33,333.
- This is a conceptual error as the maternal mortality rate should use live births as the denominator, not total deaths of women of childbearing age.
Negative predictive value (NPV) US Medical PG Question 7: In a randomized controlled trial studying a new treatment, the primary endpoint (mortality) occurred in 14.4% of the treatment group and 16.7% of the control group. Which of the following represents the number of patients needed to treat to save one life, based on the primary endpoint?
- A. 1/(0.144 - 0.167)
- B. 1/(0.167 - 0.144) (Correct Answer)
- C. 1/(0.300 - 0.267)
- D. 1/(0.267 - 0.300)
- E. 1/(0.136 - 0.118)
Negative predictive value (NPV) Explanation: ***1/(0.167 - 0.144)***
- The **Number Needed to Treat (NNT)** is calculated as **1 / Absolute Risk Reduction (ARR)**.
- The **Absolute Risk Reduction (ARR)** is the difference between the event rate in the control group (16.7%) and the event rate in the treatment group (14.4%), which is **0.167 - 0.144**.
*1/(0.144 - 0.167)*
- This calculation represents 1 divided by the **Absolute Risk Increase**, which would be relevant if the treatment increased mortality.
- The **NNT should always be a positive value**, indicating the number of patients to treat to prevent one adverse event.
*1/(0.300 - 0.267)*
- This option uses arbitrary numbers (0.300 and 0.267) that do not correspond to the given **mortality rates** in the problem.
- It does not reflect the correct calculation for **absolute risk reduction** based on the provided data.
*1/(0.267 - 0.300)*
- This option also uses arbitrary numbers not derived from the problem's data, and it would result in a **negative value** for the denominator.
- The difference between event rates of 0.267 and 0.300 is not present in the given information for this study.
*1/(0.136 - 0.118)*
- This calculation uses arbitrary numbers (0.136 and 0.118) that are not consistent with the reported **mortality rates** of 14.4% and 16.7%.
- These values do not represent the **Absolute Risk Reduction** required for calculating NNT in this specific scenario.
Negative predictive value (NPV) US Medical PG Question 8: A 50-year-old male presents to his primary care physician for a routine check-up. He reports that he is doing well overall without any bothersome symptoms. His past medical history is significant only for hypertension, which has been well controlled with losartan. Vital signs are as follows: T 37.0 C, HR 80, BP 128/76, RR 14, SpO2 99%. Physical examination does not reveal any concerning abnormalities. The physician recommends a fecal occult blood test at this visit to screen for the presence of any blood in the patient's stool that might be suggestive of an underlying colorectal cancer. Which of the following best describes this method of disease prevention?
- A. Primary prevention
- B. Primordial prevention
- C. Secondary prevention (Correct Answer)
- D. Tertiary prevention
- E. Quaternary prevention
Negative predictive value (NPV) Explanation: ***Secondary prevention***
- **Secondary prevention** involves **early detection** of a disease or health problem in apparently healthy individuals. Screening tests, such as the fecal occult blood test used to detect colorectal cancer before symptoms arise, are prime examples of secondary prevention.
- The goal is to identify and address the disease in its early stages, allowing for timely intervention and potentially improving outcomes.
*Primary prevention*
- **Primary prevention** aims to **prevent a disease from occurring** in the first place by reducing risk factors or increasing protective factors. Examples include vaccinations, promoting healthy diets, and regular exercise.
- In this scenario, the individual is already being screened for a potential disease, not taking measures to prevent its initial development.
*Primordial prevention*
- **Primordial prevention** focuses on **preventing the development of risk factors** themselves at a societal level. This often involves public policy and environmental changes to promote healthier lifestyles.
- It targets broad determinants of health before specific risk factors emerge in individuals, which is distinct from an individual screening test.
*Tertiary prevention*
- **Tertiary prevention** occurs **after a disease has been diagnosed** and aims to prevent progression, reduce complications, improve quality of life, and restore function. Examples include rehabilitation after a stroke or chemotherapy for cancer.
- The patient in the scenario is asymptomatic and undergoing screening, not managing an existing, diagnosed condition.
*Quaternary prevention*
- **Quaternary prevention** aims to **protect patients from medical interventions** that are likely to cause more harm than good, or to mitigate the consequences of unnecessary or excessive medical care. It focuses on identifying and avoiding overmedicalization.
- The fecal occult blood test is a standard screening tool in this context, not an intervention designed to counter the negative effects of over-treatment.
Negative predictive value (NPV) US Medical PG Question 9: A 5-year-old boy presents to your office with his mother. The boy has been complaining of a sore throat and headache for the past 2 days. His mother states that he had a fever of 39.3°C (102.7°F) and had difficulty eating. On examination, the patient has cervical lymphadenopathy and erythematous tonsils with exudates. A streptococcal rapid antigen detection test is negative. Which of the following is the most likely causative agent?
- A. A gram-negative, pleomorphic, obligate intracellular bacteria
- B. An enveloped, single-stranded, negative sense RNA virus
- C. A gram-positive, beta-hemolytic cocci in chains
- D. An enveloped, double-stranded DNA virus (Correct Answer)
- E. A naked, double-stranded DNA virus
Negative predictive value (NPV) Explanation: ***An enveloped, double-stranded DNA virus***
- This description refers to **Epstein-Barr virus (EBV)**, which is a common cause of **infectious mononucleosis** in children and adolescents.
- Symptoms like **sore throat**, **fever**, **fatigue**, **cervical lymphadenopathy**, and **erythematous tonsils with exudates** are classic for mononucleosis; a negative strep test helps rule out bacterial pharyngitis.
*A gram-negative, pleomorphic, obligate intracellular bacteria*
- This describes organisms like **Chlamydia** or **Rickettsia**, which typically cause different sets of symptoms, such as sexually transmitted infections or tick-borne diseases.
- These are **not common causes of pharyngitis** with exudates and cervical lymphadenopathy in children.
*An enveloped, single-stranded, negative sense RNA virus*
- This describes viruses such as **influenza virus** or **respiratory syncytial virus (RSV)**.
- While these can cause pharyngitis, the overall clinical picture, particularly the prominent **lymphadenopathy** and **exudative tonsillitis** in the presence of a negative strep test, is less typical for these viruses compared to EBV.
*A gram-positive, beta-hemolytic cocci in chains*
- This describes **Group A Streptococcus (GAS)**, which is the causative agent of **streptococcal pharyngitis (strep throat)**.
- Although the symptoms are consistent with strep throat, the information states that the **rapid antigen detection test for streptococcus was negative**, making this diagnosis highly unlikely.
*A naked, double-stranded DNA virus*
- This describes viruses such as **adenoviruses** or **human papillomaviruses**.
- While adenoviruses can cause pharyngitis, the detailed clinical presentation of **prominent exudative tonsillitis** and **cervical lymphadenopathy** in the context of a negative strep test points more strongly to infectious mononucleosis caused by EBV.
Negative predictive value (NPV) US Medical PG Question 10: 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)
Negative predictive value (NPV) 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.
More Negative predictive value (NPV) US Medical PG questions available in the OnCourse app. Practice MCQs, flashcards, and get detailed explanations.
