An emergency department utilizes a quantitative plasma D-dimer assay to assist in ruling o… — USMLE Step 2 CK

An emergency department utilizes a quantitative plasma D-dimer assay to assist in ruling out pulmonary embolism in low-risk patients. The standard cutoff for a positive result is $500 \text{ ng/mL}$ . In an effort to reduce the number of unnecessary computed tomography pulmonary angiograms, the department protocol is modified to use an age-adjusted cutoff, effectively raising the positivity threshold to $1000 \text{ ng/mL}$ for patients over the age of 80. Assuming the disease prevalence remains constant, which of the following best describes the expected impact of this protocol change on the diagnostic characteristics of the D-dimer test in this patient population?

A
Increased sensitivity and decreased positive predictive value
B
Decreased sensitivity and increased negative predictive value
Increased specificity and decreased negative predictive valueAnswer
D
Increased specificity and increased negative predictive value
E
Decreased specificity and increased positive predictive value

Answer

Increased specificity and decreased negative predictive value

Raising the D-dimer cutoff threshold from

500 \text{ ng/mL}

1000 \text{ ng/mL}

requires a higher biomarker concentration for a test to be flagged as positive. This modification ensures that fewer disease-free patients will incorrectly test positive (reducing false positives), which directly increases the test's specificity. Conversely, because the threshold is higher, some patients with an actual pulmonary embolism who have a D-dimer level between

500

and

1000 \text{ ng/mL}

will now be misclassified as healthy (increasing false negatives). This rise in false-negative results reduces the reliability of a negative test, meaning the negative predictive value (NPV) decreases.

Step-by-Step Solution

Analyze the effect of raising the cutoff threshold on the total number of positive and negative results.

A higher threshold requires a higher biomarker concentration for the test to be considered positive. Therefore, fewer patients will test positive (both true positives and false positives decrease), and more patients will test negative (both true negatives and false negatives increase).

Understanding how the threshold shifts patient categorization is the required first step before calculating diagnostic parameters.

Determine the subsequent impact on sensitivity and specificity.

Because true positives decrease and false negatives increase, sensitivity (the ability to detect the disease) decreases. Because true negatives increase and false positives decrease, specificity (the ability to correctly identify those without the disease) increases.

Sensitivity is calculated as

\frac{\text{TP}}{\text{TP} + \text{FN}}

and specificity as

\frac{\text{TN}}{\text{TN} + \text{FP}}

Determine the impact on predictive values based on the changes in false positives and false negatives.

The positive predictive value (PPV) increases because the proportion of false positives drops. The negative predictive value (NPV) decreases because the number of false negatives rises, meaning a negative test is now less reassuring.

Predictive values depend heavily on the rates of false positives and false negatives within the tested population.

Key Concept

Raising the diagnostic cutoff threshold of a test makes the test more stringent, which increases its specificity and positive predictive value (PPV) while decreasing its sensitivity and negative predictive value (NPV).

Estimated Time:1m 30s

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