A 52-year-old man visits his primary care physician to discuss screening for pancreatic ca… — USMLE Step 2 CK

A $52$ -year-old man visits his primary care physician to discuss screening for pancreatic cancer after a close friend was recently diagnosed with the disease. The patient has no family history of malignancy, is entirely asymptomatic, and has a normal physical examination. The prevalence of pancreatic cancer in his demographic is exceedingly low. The physician explains that a novel serum biomarker, Cancer Antigen X (CA-X), has recently been developed for clinical use. At the standard diagnostic cutoff of $35\text{ U/mL}$ , the test has a sensitivity of $98\%$ and a specificity of $90\%$ . The physician warns that if this test is applied to the general asymptomatic population, the vast majority of positive results would be false positives due to the low disease prevalence. To improve the test's utility for mass screening in low-risk populations, the manufacturer proposes a revised protocol that shifts the diagnostic cutoff to $70\text{ U/mL}$ .

Which of the following best describes the expected impact on the test's performance characteristics when adopting the $70\text{ U/mL}$ cutoff instead of the $35\text{ U/mL}$ cutoff?

It increases the positive predictive value primarily by decreasing the number of false positives, while concomitantly increasing the false-negative rate.Answer
B
It increases the positive predictive value primarily by increasing the number of true positives, while concomitantly decreasing the false-negative rate.
C
It decreases the positive predictive value primarily by decreasing the number of true positives, while concomitantly increasing the false-positive rate.
D
It increases the negative predictive value primarily by decreasing the number of false negatives, while concomitantly decreasing the false-positive rate.
E
It decreases the negative predictive value primarily by increasing the number of false positives, while concomitantly decreasing the true-positive rate.

Answer

It increases the positive predictive value primarily by decreasing the number of false positives, while concomitantly increasing the false-negative rate.

The correct option accurately identifies the dual effects of raising a diagnostic cutoff threshold. Shifting the cutoff from

35\text{ U/mL}

70\text{ U/mL}

means a patient must have a much higher level of the biomarker to test positive. Consequently, fewer healthy people will cross this threshold, which decreases the number of false positives (increasing specificity). Because the population prevalence is very low, eliminating false positives is the most powerful way to increase the Positive Predictive Value (PPV). However, this stricter threshold also means that some patients who actually have the disease will fail to reach the

70\text{ U/mL}

mark, leading to an increase in false negatives (decreasing sensitivity).

Step-by-Step Solution

Analyze the directional change of the threshold.

The cutoff is raised from

35\text{ U/mL}

70\text{ U/mL}

Establishing the direction of the cutoff shift is required to determine the effect on sensitivity and specificity.

Determine the impact of raising the threshold on basic test parameters.

Raising the cutoff requires a higher biomarker level for a positive test. This makes it harder to test positive, leading to fewer true positives (decreased sensitivity) and fewer false positives (increased specificity).

Test parameters are intrinsically linked to the cutoff point; raising it inherently trades sensitivity for specificity.

Evaluate the effect on the false-negative and false-positive rates.

Because sensitivity decreases, the false-negative rate (

1 - \text{sensitivity}

) increases. Because specificity increases, the false-positive rate (

1 - \text{specificity}

) decreases.

These rates are mathematically derived directly from sensitivity and specificity.

Relate these changes to predictive values in a low-prevalence population.

Positive Predictive Value (PPV) is

\frac{\text{True Positives}}{\text{True Positives} + \text{False Positives}}

. In a low-prevalence setting, the denominator is dominated by false positives. By drastically reducing false positives (increasing specificity), the denominator shrinks significantly, which increases the PPV despite a slight drop in true positives.

Predictive values depend on both the intrinsic test characteristics and the disease prevalence in the tested population.

Key Concept

Directional impact of diagnostic cutoff shifts on test performance metrics (Sensitivity, Specificity, PPV, NPV).

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