Relationship with false positive/negative rates US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Relationship with false positive/negative rates. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Relationship with false positive/negative rates 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)
Relationship with false positive/negative rates 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.
Relationship with false positive/negative rates US Medical PG Question 2: An at-home recreational drug screening test kit is currently being developed. They consult you for assistance with determining an ideal cut-off point for the level of the serum marker in the test kit. This cut-off point will determine what level of serum marker is associated with a positive or negative test, with serum marker levels greater than the cut-off point indicative of a positive test and vice-versa. The cut-off level is initially set at 4 mg/uL, which is associated with a sensitivity of 92% and a specificity of 97%. How will the sensitivity and specificity of the test change if the cut-off level is raised to 6 mg/uL?
- A. Sensitivity decreases, specificity decreases
- B. Sensitivity decreases, specificity may increase or decrease
- C. Sensitivity decreases, specificity increases (Correct Answer)
- D. Sensitivity increases, specificity increases
- E. Sensitivity increases, specificity decreases
Relationship with false positive/negative rates Explanation: ***Sensitivity decreases, specificity increases***
- Raising the cut-off level means that the test will now require a **higher concentration of the serum marker** to be considered positive. This makes it harder for true positives to be identified (more false negatives), thus **decreasing sensitivity**.
- Conversely, a higher cut-off makes it less likely for healthy individuals (true negatives) to mistakenly test positive (fewer false positives), leading to an **increase in specificity**.
*Sensitivity decreases, specificity decreases*
- This option is incorrect because **raising the cut-off point** typically has opposing effects on sensitivity and specificity, not a decrease in both.
- A decrease in both would suggest a poorly designed or random change, which is not the expected outcome of systematically adjusting a threshold.
*Sensitivity decreases, specificity may increase or decrease*
- While it's true that real-world scenarios can be complex, for a single, direct change to a cut-off point, the relationship between sensitivity and specificity is generally inverse for a given test.
- The uncertainty implied by "may increase or decrease" does not fully capture the predictable inverse relationship that occurs when adjusting a diagnostic threshold.
*Sensitivity increases, specificity increases*
- **Increasing sensitivity** and **increasing specificity** simultaneously is only achievable by improving the diagnostic test itself (e.g., using a better marker), not by simply adjusting a fixed cut-off point.
- Adjusting a cut-off almost always involves a **trade-off** between these two metrics.
*Sensitivity increases, specificity decreases*
- This would occur if the cut-off level were **lowered**, not raised.
- A lower cut-off would detect more true positives (increased sensitivity) but would also incorrectly classify more healthy individuals as positive (decreased specificity).
Relationship with false positive/negative rates US Medical PG Question 3: A mother presents to the family physician with her 16-year-old son. She explains, "There's something wrong with him doc. His grades are getting worse, he's cutting class, he's gaining weight, and his eyes are often bloodshot." Upon interviewing the patient apart from his mother, he seems withdrawn and angry at times when probed about his social history. The patient denies abuse and sexual history. What initial test should be sent to rule out the most likely culprit of this patient's behavior?
- A. Complete blood count
- B. Sexually transmitted infection (STI) testing
- C. Blood culture
- D. Urine toxicology screen (Correct Answer)
- E. Slit lamp examination
Relationship with false positive/negative rates Explanation: ***Urine toxicology screen***
- The patient's presentation with **declining grades**, **cutting class**, **weight gain**, **bloodshot eyes**, and **irritability** are classic signs of **substance abuse** in an adolescent.
- A **urine toxicology screen** is the most appropriate initial test to detect common illicit substances, especially given the clear signs pointing towards drug use.
*Slit lamp examination*
- This test is used to examine the **anterior segment of the eye**, including the conjunctiva, cornea, iris, and lens.
- While the patient has **bloodshot eyes**, this specific test would be more relevant for ruling out ocular infections or injuries, not for diagnosing the underlying cause of systemic behavioral changes.
*Complete blood count*
- A **complete blood count (CBC)** measures different components of the blood, such as red blood cells, white blood cells, and platelets.
- A CBC is a general health indicator and while it can detect infections or anemia, it is not specific or sensitive enough to identify the cause of the behavioral changes described.
*Sexually transmitted infection (STI) testing*
- Although the patient denies sexual history, all adolescents presenting with certain risk factors or symptoms may warrant STI testing in a broader health assessment.
- However, in this scenario, the primary cluster of symptoms (poor grades, cutting class, bloodshot eyes, irritability) points more directly to substance abuse than to an STI.
*Blood culture*
- A **blood culture** is used to detect the presence of bacteria or other microorganisms in the bloodstream, indicating a systemic infection (sepsis).
- The patient's symptoms are not indicative of an acute bacterial bloodstream infection, and a blood culture would not be the initial test for the presented behavioral changes.
Relationship with false positive/negative rates US Medical PG Question 4: A rapid diagnostic test has been developed amid a major avian influenza outbreak in Asia. The outbreak has reached epidemic levels with a very high attack rate. Epidemiologists are hoping to use the rapid diagnostic test to identify all exposed individuals and curb the rapid spread of disease by isolating patients with any evidence of exposure to the virus. The epidemiologists compared rapid diagnostic test results to seropositivity of viral antigen via PCR in 200 patients. The findings are represented in the following table:
Test result PCR-confirmed avian influenza No avian influenza
Positive rapid diagnostic test 95 2
Negative rapid diagnostic test 5 98
Which of the following characteristics of the rapid diagnostic test would be most useful for curbing the spread of the virus via containment?
- A. Positive predictive value of 95/97
- B. Specificity of 98/100
- C. Sensitivity of 95/100 (Correct Answer)
- D. Negative predictive value of 98/103
- E. Accuracy of 193/200
Relationship with false positive/negative rates Explanation: ***Sensitivity of 95/100***
- In an epidemic with a **high attack rate** and the goal of **identifying all exposed individuals** to prevent spread, a test with **high sensitivity** is crucial.
- **Sensitivity** measures the proportion of true positives that are correctly identified (95/100 = 95%), meaning it correctly identifies those *with* the disease, thus minimizing **false negatives** and ensuring all infected individuals are isolated.
- When the primary objective is containment and preventing disease spread, missing even a few infected individuals (false negatives) could perpetuate the epidemic.
*Positive predictive value of 95/97*
- **Positive predictive value (PPV)** indicates the probability that a positive test result truly reflects the presence of the disease (95/97 = 97.9%).
- While important for confirming disease in individuals, it's less critical than sensitivity for the primary goal of **identifying all exposed individuals** in an epidemic to prevent further spread.
*Specificity of 98/100*
- **Specificity** measures the proportion of true negatives that are correctly identified (98/100 = 98%), meaning it correctly identifies those *without* the disease.
- In this scenario, while important to avoid unnecessary isolation, high specificity is secondary to high sensitivity when the main objective is to **curb rapid disease spread by finding all infected individuals**.
*Negative predictive value of 98/103*
- **Negative predictive value (NPV)** indicates the probability that a negative test result truly reflects the absence of the disease (98/103 = 95.1%).
- While valuable for ruling out disease, high NPV is not the most critical characteristic when the primary goal is to **identify all infected individuals** to contain an epidemic.
*Accuracy of 193/200*
- **Accuracy** represents the overall proportion of correct results, both positive and negative (193/200 = 96.5%).
- While accuracy provides an overall measure of test performance, it doesn't specifically address the critical need to **minimize false negatives** in a containment scenario where missing infected individuals is the primary concern.
Relationship with false positive/negative rates 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)
Relationship with false positive/negative rates 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**.
Relationship with false positive/negative rates US Medical PG Question 6: During an evaluation of a new diagnostic imaging modality for detecting salivary gland tumors, 90 patients tested positive out of the 100 patients who tested positive with the gold standard test. A total of 80 individuals tested negative with the new test out of the 100 individuals who tested negative with the gold standard test. What is the positive likelihood ratio for this test?
- A. 80/90
- B. 90/100
- C. 90/20 (Correct Answer)
- D. 90/110
- E. 10/80
Relationship with false positive/negative rates Explanation: ***90/20***
- The **positive likelihood ratio (LR+)** is calculated as **sensitivity / (1 - specificity)**. To calculate this, we first need to determine the values for true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN).
- Given that 90 out of 100 actual positive patients tested positive, **TP = 90** and **FN = 100 - 90 = 10**. Also, 80 out of 100 actual negative patients tested negative, so **TN = 80** and **FP = 100 - 80 = 20**.
- **Sensitivity** is the true positive rate (TP / (TP + FN)) = 90 / (90 + 10) = 90 / 100.
- **Specificity** is the true negative rate (TN / (TN + FP)) = 80 / (80 + 20) = 80 / 100.
- Therefore, LR+ = (90/100) / (1 - 80/100) = (90/100) / (20/100) = **90/20**.
*80/90*
- This option incorrectly represents the components for the likelihood ratio. It seems to misinterpret the **true negative** count and the **true positive** count.
- It does not follow the formula for LR+ which is **sensitivity / (1 - specificity)**.
*90/100*
- This value represents the **sensitivity** of the test, which is the proportion of true positives among all actual positives.
- It does not incorporate the **false positive rate** (1 - specificity) in the denominator required for the positive likelihood ratio.
*90/110*
- This option incorrectly combines different values, possibly by confusing the denominator for sensitivity or specificity calculations.
- It does not correspond to the formula for the **positive likelihood ratio**.
*10/80*
- This value seems to relate to the inverse of the **false negative rate** (10/100) or misrepresents the relationship between false negatives and true negatives.
- It is not correctly structured to represent the **positive likelihood ratio (LR+)**.
Relationship with false positive/negative rates US Medical PG Question 7: A 40-year-old woman presents with a ‘tingling’ feeling in the toes of both feet that started 5 days ago. She says that the feeling varies in intensity but has been there ever since she recovered from a stomach flu last week. Over the last 2 days, the tingling sensation has started to spread up her legs. She also reports feeling weak in the legs for the past 2 days. Her past medical history is unremarkable, and she currently takes no medications. Which of the following diagnostic tests would most likely be abnormal in this patient?
- A. Noncontrast CT of the head
- B. Serum hemoglobin concentration
- C. Nerve conduction studies (Correct Answer)
- D. Serum calcium concentration
- E. Transthoracic echocardiography
Relationship with false positive/negative rates Explanation: ***Nerve conduction studies***
- The patient's ascending **motor weakness** and **sensory paresthesias** following a gastrointestinal infection are classic symptoms of **Guillain-Barré Syndrome (GBS)**, which is characterized by **demyelination** of peripheral nerves.
- **Nerve conduction studies** would reveal **markedly slowed conduction velocities**, **conduction block**, and **prolonged distal latencies**, indicating the demyelinating neuropathy characteristic of GBS.
*Noncontrast CT of the head*
- This test is primarily used to evaluate **acute neurological deficits** suggestive of stroke, hemorrhage, or mass lesions within the brain.
- The patient's symptoms are consistent with a **peripheral neuropathy** and do not suggest a central nervous system pathology.
*Serum hemoglobin concentration*
- This measures the concentration of **hemoglobin in the blood** and is used to diagnose **anemia**.
- While anemia can cause fatigue, it does not typically cause the **ascending paralysis** and **paresthesias** described, nor is it directly related to a recent stomach flu in this manner.
*Serum calcium concentration*
- This measures the level of **calcium in the blood**, which is important for muscle and nerve function.
- While extreme imbalances can cause neurological symptoms, there is no direct indication or typical association between the patient's symptoms and a primary calcium disorder.
*Transthoracic echocardiography*
- This imaging test evaluates the **structure and function of the heart**.
- The patient's symptoms are neurological and do not suggest a primary cardiac etiology or complication that would warrant an echocardiogram.
Relationship with false positive/negative rates US Medical PG Question 8: A 1-minute-old newborn is being examined by the pediatric nurse. The nurse auscultates the heart and determines that the heart rate is 89/min. The respirations are spontaneous and regular. The chest and abdomen are both pink while the tips of the fingers and toes are blue. When the newborn’s foot is slapped the face grimaces and he cries loud and strong. When the arms are extended by the nurse they flex back quickly. What is this patient’s Apgar score?
- A. 5
- B. 10
- C. 8 (Correct Answer)
- D. 6
- E. 9
Relationship with false positive/negative rates Explanation: ***8***
- The Apgar score is calculated by assigning 0, 1, or 2 points to five criteria: **Appearance**, **Pulse**, **Grimace (reflex irritability)**, **Activity (muscle tone)**, and **Respiration**.
- This newborn scores 1 point for **Appearance** (pink body, blue extremities/acrocyanosis), 1 point for **Pulse** (89/min, which is below 100), 2 points for **Grimace** (cries loud and strong), 2 points for **Activity** (arms flex back quickly), and 2 points for **Respiration** (spontaneous and regular), totaling **8**.
*5*
- An Apgar score of 5 would indicate a more compromised state, with lower scores in multiple categories.
- This newborn demonstrates strong respiratory effort, vigorous cry, and active muscle tone, all inconsistent with a score of 5.
*10*
- A perfect score of 10 is rare and would require the newborn to have a **pink appearance throughout** (including extremities), a heart rate over 100 bpm, strong cry, active movement, and vigorous breathing.
- This newborn has two findings preventing a score of 10: **acrocyanosis** (blue extremities) and **heart rate of 89/min** (below 100).
*6*
- An Apgar score of 6 would imply more significant compromise, such as weak respiratory effort, minimal response to stimulation, or poor muscle tone.
- This newborn's strong cry, vigorous grimace response, and quick flexion indicate better performance than a score of 6.
*9*
- A score of 9 would mean only one parameter scores 1 point, with all others scoring 2 points.
- This newborn has **two parameters scoring 1 point**: **Appearance** (acrocyanosis) and **Pulse** (89/min, below 100), making the maximum possible score 8, not 9.
Relationship with false positive/negative rates US Medical PG Question 9: 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)
Relationship with false positive/negative rates 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.
Relationship with false positive/negative rates US Medical PG Question 10: You are tasked with analyzing the negative predictive value of an experimental serum marker for ovarian cancer. You choose to enroll 2,000 patients across multiple clinical sites, including both 1,000 patients with ovarian cancer and 1,000 age-matched controls. From the disease and control subgroups, 700 and 100 are found positive for this novel serum marker, respectively. Which of the following represents the NPV for this test?
- A. 700 / (700 + 300)
- B. 700 / (300 + 900)
- C. 700 / (700 + 100)
- D. 900 / (900 + 100)
- E. 900 / (900 + 300) (Correct Answer)
Relationship with false positive/negative rates Explanation: ***900 / (900 + 300)***
- The **Negative Predictive Value (NPV)** is the probability that a person with a **negative test result** does not have the disease. It is calculated as **true negatives (TN)** divided by the sum of true negatives and **false negatives (FN)**, i.e., TN / (TN + FN).
- In this scenario: there are 1,000 ovarian cancer patients, and 700 tested positive, meaning **300 tested negative (false negatives)**. There are 1,000 controls, and 100 tested positive, meaning **900 tested negative (true negatives)**. Therefore, NPV = 900 / (900 + 300).
*700 / (700 + 300)*
- This calculation represents the sensitivity of the test, which is the proportion of true positives among all individuals with the disease (700 true positives / 1000 diseased individuals).
- It does not account for the true negatives or false positives, which are crucial for determining predictive values.
*700 / (300 + 900)*
- This formula mixes elements and does not correspond to a standard measure of test validity.
- The numerator (700) is the number of true positives, and the denominator incorrectly combines false negatives (300) and true negatives (900).
*700 / (700 + 100)*
- This calculation represents the **Positive Predictive Value (PPV)**, which is the probability that a person with a **positive test result** actually has the disease (700 true positives / (700 true positives + 100 false positives)).
- It does not assess the negative predictive power of the test.
*900 / (900 + 100)*
- This calculation represents the **specificity** of the test, which is the proportion of true negatives among all individuals without the disease (900 true negatives / 1000 controls).
- While this involves true negatives, it does not account for false negatives, which are essential for calculating NPV.
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