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?
Q22
A 35-year-old man presents to his primary care provider in Philadelphia with a skin rash on his right thigh. He reports that the rash appeared 3 days ago. He recently returned from a weeklong trip to his vacation home in central Pennsylvania. He denies pain, numbness, paresthesias, itchiness, or burning around the rash. He does not recall finding any ticks on his body. He otherwise feels well. His past medical history is notable for gout. He takes allopurinol. He is an avid hiker and spends 3 months out of the year hiking. He does not smoke and drinks alcohol socially. On exam, he has a bullseye-like circular erythematous rash on the anterolateral aspect of his right thigh. The doctor decides to perform a new serum test for Lyme disease that was trialed at the same hospital in Philadelphia, where it was shown to have a sensitivity of 91% and specificity of 94%. The prevalence of Lyme disease in the area is among the highest in the country. How would the sensitivity and specificity of this new test change if it were performed on a patient in Texas, an area with a very low prevalence of Lyme disease?
Q23
A research team is working on a new assay meant to increase the sensitivity of testing in cervical cancer. Current sensitivity is listed at 77%. If this research team's latest work culminates in the following results (listed in the table), has the sensitivity improved, and, if so, then by what percentage?
Research team's latest results:
| | Patients with cervical cancer | Patients without cervical cancer |
|--------------------------|-------------------------------|----------------------------------|
| Test is Positive (+) | 47 | 4 |
| Test is Negative (-) | 9 | 44 |
Q24
A group of neurologists develop a new blood test for Alzheimer's. They are optimistic about the test, as they have found that for any given patient, the test repeatedly produces very similar results. However, they find that the new test results are not necessarily consistent with the gold standard of diagnosis. How would this new test most accurately be described?
Q25
You conduct a medical research study to determine the screening efficacy of a novel serum marker for colon cancer. The study is divided into 2 subsets. In the first, there are 500 patients with colon cancer, of which 450 are found positive for the novel serum marker. In the second arm, there are 500 patients who do not have colon cancer, and only 10 are found positive for the novel serum marker. What is the overall sensitivity of this novel test?
Q26
You are developing a new diagnostic test to identify patients with disease X. Of 100 patients tested with the gold standard test, 10% tested positive. Of those that tested positive, the experimental test was positive for 90% of those patients. The specificity of the experimental test is 20%. What is the positive predictive value of this new test?
Q27
A medicine resident on her nephrology rotation notices that she has received more alerts of high serum potassium levels on her patients through the hospital electronic medical record despite her census not having changed. On inspection of the laboratory result reports, critical alert markers are seen for potassium values greater than 5.5 mEq/L 3 days ago, whereas the same alerts are seen for values > 5.0 mEq/L since yesterday. One of her patient's nurses asks if the patient should get an electrocardiogram. How has the potassium value reporting been affected?
Q28
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?
Q29
A group of investigators is evaluating the diagnostic properties of a new blood test that uses two serum biomarkers, dityrosine and Nε-carboxymethyl-lysine, for the clinical diagnosis of autism spectrum disorder (ASD) in children. The test is considered positive only if both markers are found in the serum. 50 children who have been diagnosed with ASD based on established clinical criteria and 50 children without the disorder undergo testing. The results show:
Diagnosis of ASD No diagnosis of ASD
Test positive 45 15
Test negative 5 35
Which of the following is the specificity of this new test?
Q30
A new real time-PCR test for the hepatitis C virus is approved for medical use. The manufacturer sets the threshold number of DNA copies required to achieve a positive result such that the sensitivity is 98% and the specificity is 80%. The tested population has a hepatitis C prevalence of 0.7%. Which of the following changes in the prevalence, incidence, or threshold concentration will increase the positive predictive value of the test, if the other two values are held constant?
Sensitivity/Specificity US Medical PG Practice Questions and MCQs
Question 21: 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
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+)**.
Question 22: A 35-year-old man presents to his primary care provider in Philadelphia with a skin rash on his right thigh. He reports that the rash appeared 3 days ago. He recently returned from a weeklong trip to his vacation home in central Pennsylvania. He denies pain, numbness, paresthesias, itchiness, or burning around the rash. He does not recall finding any ticks on his body. He otherwise feels well. His past medical history is notable for gout. He takes allopurinol. He is an avid hiker and spends 3 months out of the year hiking. He does not smoke and drinks alcohol socially. On exam, he has a bullseye-like circular erythematous rash on the anterolateral aspect of his right thigh. The doctor decides to perform a new serum test for Lyme disease that was trialed at the same hospital in Philadelphia, where it was shown to have a sensitivity of 91% and specificity of 94%. The prevalence of Lyme disease in the area is among the highest in the country. How would the sensitivity and specificity of this new test change if it were performed on a patient in Texas, an area with a very low prevalence of Lyme disease?
A. Both sensitivity and specificity will decrease.
B. Sensitivity will decrease, and specificity will increase.
C. Both sensitivity and specificity will increase.
D. Sensitivity and specificity will remain the same. (Correct Answer)
E. Sensitivity will increase, and specificity will decrease.
Explanation: ***Sensitivity and specificity will remain the same.***
- **Sensitivity** and **specificity** are **intrinsic properties** of a diagnostic test that describe its ability to correctly identify diseased and non-diseased individuals, respectively, independent of **disease prevalence**.
- While **predictive values (positive and negative predictive values)** are influenced by the **prevalence** of a disease in a given population, sensitivity and specificity are not. They reflect the test's performance characteristics regardless of how common the disease is in the population being tested.
*Both sensitivity and specificity will decrease.*
- This statement is incorrect because the **prevalence** of a disease does not alter the inherent ability of a test to correctly identify individuals with or without the disease; hence, sensitivity and specificity remain constant.
- A change in prevalence would affect the **positive and negative predictive values**, not the test's fundamental sensitivity and specificity.
*Sensitivity will decrease, and specificity will increase.*
- This is incorrect because sensitivity and specificity are fixed characteristics of the test itself, determined during its validation.
- The **prevalence** of the disease in a different population (e.g., Texas vs. Pennsylvania) does not change these intrinsic measures of test performance.
*Both sensitivity and specificity will increase.*
- This statement is incorrect as sensitivity and specificity are **independent** of **disease prevalence**. Better performance (higher sensitivity and specificity) would require a different, improved test, not merely testing in a different population.
- The **inherent accuracy** of the test does not spontaneously improve or worsen based on where it is applied.
*Sensitivity will increase, and specificity will decrease.*
- This is incorrect because, as explained, **sensitivity** and **specificity** are inherent qualities of the test and are not influenced by the **prevalence** of the disease within a population.
- Changes in prevalence affect the **likelihood of false positives and false negatives** when interpreting results, but not the test's fundamental ability to detect disease (sensitivity) or absence of disease (specificity).
Question 23: A research team is working on a new assay meant to increase the sensitivity of testing in cervical cancer. Current sensitivity is listed at 77%. If this research team's latest work culminates in the following results (listed in the table), has the sensitivity improved, and, if so, then by what percentage?
Research team's latest results:
| | Patients with cervical cancer | Patients without cervical cancer |
|--------------------------|-------------------------------|----------------------------------|
| Test is Positive (+) | 47 | 4 |
| Test is Negative (-) | 9 | 44 |
A. No, the research team has seen a decrease in sensitivity according to the new results listed.
B. No, the research team has not seen any improvement in sensitivity according to the new results listed.
C. Yes, the research team has seen an improvement in sensitivity of almost 7% according to the new results listed. (Correct Answer)
D. Yes, the research team has seen an improvement in sensitivity of more than 10% according to the new results listed.
E. Yes, the research team has seen an improvement in sensitivity of less than 2% according to new results listed; this improvement is negligible and should be improved upon for significant contribution to the field.
Explanation: ***Yes, the research team has seen an improvement in sensitivity of almost 7% according to the new results listed.***
- **Sensitivity** is calculated as **True Positives / (True Positives + False Negatives)**. From the table: True Positives = 47, False Negatives = 9.
- New sensitivity = 47 / (47 + 9) = 47 / 56 $\approx$ **83.9%**. Compared to the current sensitivity of 77%, this is an improvement of 83.9% - 77% = **6.9%**, which is almost 7%.
*No, the research team has not seen any improvement in sensitivity according to the new results listed.*
- The new sensitivity calculated is **83.9%**, which is indeed higher than the current sensitivity of **77%**.
- This option incorrectly states there is no improvement, as a clear increase of nearly 7% is observed.
*No, the research team has seen a decrease in sensitivity according to the new results listed.*
- The calculated new sensitivity of **83.9%** is higher than the original 77%, indicating an **increase**, not a decrease.
- This statement is factually incorrect based on the provided data.
*Yes, the research team has seen an improvement in sensitivity of more than 10% according to the new results listed.*
- The improvement is approximately **6.9%** (83.9% - 77%), which is less than 10%.
- This option overstates the degree of improvement observed.
*Yes, the research team has seen an improvement in sensitivity of less than 2% according to new results listed; this improvement is negligible and should be improved upon for significant contribution to the field.*
- The calculated improvement is approximately **6.9%**, not less than 2%.
- While clinical significance can be debated, the mathematical calculation of improvement is not accurately reflected by "less than 2%".
Question 24: A group of neurologists develop a new blood test for Alzheimer's. They are optimistic about the test, as they have found that for any given patient, the test repeatedly produces very similar results. However, they find that the new test results are not necessarily consistent with the gold standard of diagnosis. How would this new test most accurately be described?
A. Valid and reliable
B. Reliable (Correct Answer)
C. Valid
D. Biased
E. Neither valid nor reliable
Explanation: ***Reliable***
- The test produces **similar results repeatedly** upon repeated measures, indicating high **reliability** or **precision**.
- Reliability refers to the **consistency** of a measure, even if it is not accurate.
*Valid and reliable*
- While the test is **reliable**, it is explicitly stated that the results are **not consistent with the gold standard**, meaning it lacks **validity**.
- A test must be both **consistent** (reliable) and **accurate** (valid) to be described as valid and reliable.
*Valid*
- **Validity** refers to the **accuracy** of a test, or how well it measures what it is supposed to measure.
- The test is explicitly stated to **not be consistent with the gold standard**, indicating a lack of agreement with the true measure of Alzheimer's.
*Biased*
- **Bias** refers to a **systematic error** in measurement that can lead to consistently high or low results compared to the true value.
- While the test might be biased due to its lack of consistency with the gold standard, "biased" is not the most accurate single descriptor of its measurement properties given the information provided.
*Neither valid nor reliable*
- The test is described as producing **very similar results repeatedly**, which directly indicates it has **high reliability**.
- Therefore, stating it is neither valid nor reliable is incorrect, as it possesses reliability.
Question 25: You conduct a medical research study to determine the screening efficacy of a novel serum marker for colon cancer. The study is divided into 2 subsets. In the first, there are 500 patients with colon cancer, of which 450 are found positive for the novel serum marker. In the second arm, there are 500 patients who do not have colon cancer, and only 10 are found positive for the novel serum marker. What is the overall sensitivity of this novel test?
A. 450 / (450 + 10)
B. 490 / (10 + 490)
C. 490 / (50 + 490)
D. 450 / (450 + 50) (Correct Answer)
E. 490 / (450 + 490)
Explanation: ***450 / (450 + 50)***
- **Sensitivity** is defined as the proportion of actual positive cases that are correctly identified by the test.
- In this study, there are **500 patients with colon cancer** (actual positives), and **450 of them tested positive** for the marker, while **50 tested negative** (500 - 450 = 50). Therefore, sensitivity = 450 / (450 + 50) = 450/500 = 0.9 or 90%.
*450 / (450 + 10)*
- This formula represents **Positive Predictive Value (PPV)**, which is the probability that a person with a positive test result actually has the disease.
- It incorrectly uses the total number of **test positives** in the denominator (450 true positives + 10 false positives) instead of the total number of diseased individuals, which is needed for sensitivity.
*490 / (10 + 490)*
- This is actually the correct formula for **specificity**, not sensitivity.
- Specificity = TN / (FP + TN) = 490 / (10 + 490) = 490/500 = 0.98 or 98%, which measures the proportion of actual negative cases correctly identified.
- The question asks for sensitivity, not specificity.
*490 / (50 + 490)*
- This formula incorrectly mixes **true negatives (490)** with **false negatives (50)** in an attempt to calculate specificity.
- The correct specificity formula should use false positives (10), not false negatives (50), in the denominator: 490 / (10 + 490).
*490 / (450 + 490)*
- This calculation incorrectly combines **true negatives (490)** and **true positives (450)** in the denominator, which does not correspond to any standard epidemiological measure.
- Neither sensitivity nor specificity uses both true positives and true negatives in the denominator.
Question 26: You are developing a new diagnostic test to identify patients with disease X. Of 100 patients tested with the gold standard test, 10% tested positive. Of those that tested positive, the experimental test was positive for 90% of those patients. The specificity of the experimental test is 20%. What is the positive predictive value of this new test?
A. 10%
B. 90%
C. 95%
D. 11% (Correct Answer)
E. 20%
Explanation: ***11%***
- The positive predictive value (PPV) is calculated as **true positives / (true positives + false positives)**.
- From 100 patients, 10 have disease (prevalence 10%). With 90% sensitivity, the test correctly identifies **9 true positives** (90% of 10).
- Of 90 patients without disease, specificity of 20% means 20% are correctly identified as negative (18 true negatives), so **72 false positives** = 90 × (1 - 0.20).
- Therefore, PPV = 9 / (9 + 72) = 9/81 = **11.1% ≈ 11%**.
*10%*
- This value represents the **prevalence** of the disease in the population, not the positive predictive value of the test.
- Prevalence is the proportion of individuals who have the disease (10 out of 100 patients).
*90%*
- This figure represents the **sensitivity** of the test, which is the percentage of true positives correctly identified by the experimental test.
- Sensitivity = true positives / (true positives + false negatives) = 9/10 = 90%.
*95%*
- This value is not directly derivable from the given data and does not represent any standard test characteristic in this context.
- It would imply a much higher PPV than what can be calculated given the low specificity of 20%.
*20%*
- This is the stated **specificity** of the test, which measures the proportion of true negatives correctly identified.
- Specificity = true negatives / (true negatives + false positives) = 18/90 = 20%.
Question 27: A medicine resident on her nephrology rotation notices that she has received more alerts of high serum potassium levels on her patients through the hospital electronic medical record despite her census not having changed. On inspection of the laboratory result reports, critical alert markers are seen for potassium values greater than 5.5 mEq/L 3 days ago, whereas the same alerts are seen for values > 5.0 mEq/L since yesterday. One of her patient's nurses asks if the patient should get an electrocardiogram. How has the potassium value reporting been affected?
A. Sensitivity increased and specificity increased
B. Sensitivity decreased and specificity increased
C. Sensitivity increased and specificity unchanged
D. Sensitivity decreased and specificity decreased
E. Sensitivity increased and specificity decreased (Correct Answer)
Explanation: ***Sensitivity increased and specificity decreased***
- Lowering the alert threshold from **>5.5 mEq/L** to **>5.0 mEq/L** means more true positives (patients with actual hyperkalemia) will be identified, thus **increasing sensitivity**.
- However, this also means more false positives (patients without clinically significant hyperkalemia triggering an alert) will occur, thereby **decreasing specificity**.
*Sensitivity increased and specificity increased*
- This option would imply that the test is better at identifying both true positives and true negatives, which is not the case when only the threshold is changed.
- While sensitivity increases by lowering the threshold, specificity invariably decreases, as more benign cases are flagged.
*Sensitivity decreased and specificity increased*
- This scenario would occur if the threshold were raised (e.g., from >5.0 mEq/L to >5.5 mEq/L), which would miss more true cases but reduce false alarms.
- The alert range change described (from >5.5 to >5.0) directly opposes this outcome.
*Sensitivity decreased and specificity decreased*
- This would indicate a significant worsening of the test's ability to correctly identify both cases and non-cases, which is not directly supported by merely adjusting a threshold.
- While specificity does decrease, sensitivity increases, making this option incorrect.
*Sensitivity increased and specificity unchanged*
- Changing the threshold will impact both sensitivity and specificity, making it impossible for specificity to remain unchanged if sensitivity increases.
- A threshold adjustment always involves a trade-off between sensitivity and specificity; improving one typically impacts the other.
Question 28: 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
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.
Question 29: A group of investigators is evaluating the diagnostic properties of a new blood test that uses two serum biomarkers, dityrosine and Nε-carboxymethyl-lysine, for the clinical diagnosis of autism spectrum disorder (ASD) in children. The test is considered positive only if both markers are found in the serum. 50 children who have been diagnosed with ASD based on established clinical criteria and 50 children without the disorder undergo testing. The results show:
Diagnosis of ASD No diagnosis of ASD
Test positive 45 15
Test negative 5 35
Which of the following is the specificity of this new test?
A. 10%
B. 88%
C. 70% (Correct Answer)
D. 90%
E. 30%
Explanation: ***70%***
- **Specificity** measures the proportion of **true negatives** among all actual negatives. It is calculated as True Negatives / (True Negatives + False Positives).
- In this study, there are 35 true negatives (children without ASD who tested negative) and 15 false positives (children without ASD who tested positive). Therefore, Specificity = 35 / (35 + 15) = 35 / 50 = **0.70 or 70%**.
*10%*
- This value is not directly interpretable as a standard diagnostic property from the given data.
- It might represent a calculation error or a misinterpretation of a different metric.
*88%*
- This value does not correspond to any standard diagnostic test property calculated from the given 2x2 table.
- It might result from a calculation error or confusion between different metrics (e.g., an incorrect attempt at calculating positive predictive value or sensitivity).
- The actual **positive predictive value** would be 45 / (45 + 15) = 45/60 = **75%**, not 88%.
*90%*
- This value represents the **sensitivity** of the test, calculated as True Positives / (True Positives + False Negatives) = 45 / (45 + 5) = 45/50 = 0.90 or 90%.
- Sensitivity measures the ability of the test to correctly identify those with the disease, not those without it.
*30%*
- This value represents the proportion of **false positives** among all actual negatives (False Positives / (True Negatives + False Positives) = 15 / (35 + 15) = 15/50 = 0.30 or 30%).
- This is **1 - specificity**, not specificity itself.
Question 30: A new real time-PCR test for the hepatitis C virus is approved for medical use. The manufacturer sets the threshold number of DNA copies required to achieve a positive result such that the sensitivity is 98% and the specificity is 80%. The tested population has a hepatitis C prevalence of 0.7%. Which of the following changes in the prevalence, incidence, or threshold concentration will increase the positive predictive value of the test, if the other two values are held constant?
A. A decrease in incidence
B. A decrease in prevalence
C. An increase in prevalence (Correct Answer)
D. Lowering the threshold concentration required for a positive test.
E. An increase in incidence
Explanation: ***An increase in prevalence***
- An increase in **prevalence** directly leads to an increase in the **positive predictive value (PPV)** as it means there are more true positives in the tested population relative to false positives.
- PPV is calculated as (True Positives) / (True Positives + False Positives), and a higher prevalence increases the likelihood that a positive test result genuinely indicates the presence of the disease.
*A decrease in incidence*
- **Incidence** refers to the rate of new cases, while **prevalence** is the total proportion of individuals with the disease at a given time.
- The PPV formula depends directly on **prevalence**, not incidence. Since the question specifies that other values are held constant, a change in incidence alone (with prevalence held constant) would have *no direct effect* on PPV.
*A decrease in prevalence*
- A **decrease in prevalence** would lead to a lower likelihood of a positive test result being a true positive, thus *decreasing* the **positive predictive value (PPV)**.
- With fewer true cases in the population, a higher proportion of positive results would be false positives, negatively impacting the PPV.
*Lowering the threshold concentration required for a positive test*
- **Lowering the threshold concentration** for a positive test would increase the test's **sensitivity** (detecting more true positives) but *decrease* its **specificity** (leading to more false positives).
- A decrease in specificity, especially in a low-prevalence setting (0.7%), would significantly increase the number of false positives, thereby *decreasing* the **positive predictive value (PPV)**.
*An increase in incidence*
- **Incidence** measures the rate of new cases over time, while the PPV formula depends directly on **prevalence** (the proportion with disease at a given time).
- Since the question specifies that other values are held constant, an increase in incidence with prevalence held constant would have *no direct effect* on PPV. Incidence only affects PPV indirectly through its eventual impact on prevalence, but this pathway is blocked by the constraint.
