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Difficulty: MediumDiagnostic Testing Performance

A large regional healthcare system is evaluating a newly developed stool DNA panel for colorectal cancer screening. In clinical validation trials conducted at a specialized high-risk genetics clinic, where the prevalence of colorectal cancer is 15%15\%, the test demonstrated a sensitivity of 92%92\% and a specificity of 95%95\%. The healthcare system's administration now plans to deploy this stool DNA panel as a primary screening tool for average-risk adults in the general community, where the prevalence of colorectal cancer is approximately 0.6%0.6\%. Assuming the intrinsic test characteristics remain constant, which of the following is the most accurate statement regarding the community-wide deployment of this test?

  1. The majority of patients who test positive in the general community will not actually have the diseaseAnswer
  2. B
    The negative predictive value of the test will decrease compared to its performance in the high-risk clinic
  3. C
    The intrinsic proportion of healthy individuals who incorrectly test positive will increase
  4. D
    Patients with a positive test result should undergo a confirmatory test with higher sensitivity
  5. E
    The test should be avoided for primary screening because its false-negative rate will rise unacceptably

Answer

The majority of patients who test positive in the general community will not actually have the disease.
Positive predictive value (PPV) is highly dependent on disease prevalence. When a test is moved from a high-prevalence setting (15%15\%) to a low-prevalence setting (0.6%0.6\%), the PPV drops significantly. In the general community, for every 1,0001,000 patients screened, only about 66 actually have the disease, yielding approximately 55 or 66 true positive results (6×0.926 \times 0.92). Meanwhile, out of the 994994 healthy patients, a 5%5\% false-positive rate (100%−95%100\% - 95\% specificity) will generate approximately 5050 false positives (994×0.05994 \times 0.05). Because the 5050 false positives vastly outnumber the 55 or 66 true positives, the vast majority of positive test results in this community setting will not actually have the disease (a PPV of roughly 10%10\%).

Step-by-Step Solution

1
Recall how disease prevalence affects diagnostic testing parameters.
Sensitivity and specificity are intrinsic properties of a test and do not change with prevalence. However, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) are highly dependent on prevalence. As prevalence drops, PPV drops and NPV rises.
Establishing the mathematical relationship between pre-test probability (prevalence) and post-test probability.
2
Calculate the expected number of true positives in a hypothetical community population of 1,000 patients.
With a prevalence of 0.6%0.6\%, there are 66 true disease cases in 1,0001,000 people (1,000×0.0061,000 \times 0.006). With 92%92\% sensitivity, the test correctly identifies 5.525.52 true positives (6×0.926 \times 0.92).
To determine the numerator for the Positive Predictive Value calculation.
3
Calculate the expected number of false positives in the same community population.
There are 994994 healthy individuals (1,000−61,000 - 6). The false-positive rate is 5%5\% (100%−95%100\% - 95\% specificity). The test will produce 49.749.7 false positives (994×0.05994 \times 0.05).
To determine the denominator for the Positive Predictive Value calculation.
4
Evaluate the clinical implication of the calculated values.
Comparing true positives ( 5.5~5.5) to false positives ( 49.7~49.7), the PPV is approximately 10%10\% (5.5/55.25.5 / 55.2). Therefore, nearly 90%90\% of all positive results in this population will be false positives.
To identify the correct statement regarding community deployment from the given options.

Key Concept

The relationship between disease prevalence and predictive values (PPV and NPV).
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Topics

Diagnostic Testing Performance

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