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Difficulty: EasyDiagnostic Testing Performance

A clinical laboratory is validating a new quantitative blood assay for a tumor marker used to screen for a specific cancer. Initially, the test yields a high number of false-positive results, leading to patient anxiety and unnecessary invasive biopsies. To address this, the laboratory advisory committee decides to adjust the test's diagnostic threshold (cut-off value) so that a result is only considered 'positive' at a much higher serum concentration.

Assuming the underlying prevalence of the cancer in the screened population remains unchanged, which of the following statistical consequences is most likely to result directly from this threshold adjustment?

  1. Specificity of the test will increaseAnswer
  2. B
    Sensitivity of the test will increase
  3. C
    The false-positive rate will increase
  4. D
    The positive predictive value will decrease
  5. E
    The false-negative rate will decrease

Answer

Specificity of the test will increase
Diagnostic tests that use a continuous variable (like a serum biomarker concentration) require a defined cut-off point to distinguish between a 'positive' and 'negative' result. When this threshold is raised, the criteria to be diagnosed as positive become stricter. Consequently, fewer patients without the disease will accidentally cross the threshold, leading to a decrease in the false-positive rate. Because specificity is defined as the proportion of true negatives out of all individuals without the disease, a reduction in false positives directly translates to an increase in specificity. This adjustment always comes at a trade-off, as it simultaneously increases the false-negative rate and decreases sensitivity.

Step-by-Step Solution

1
Analyze the intervention applied to the diagnostic test.
The threshold (cut-off value) for a positive test is being raised to a higher serum concentration.
Understanding the direction of the cut-off shift is required to determine its impact on the underlying population curves (healthy vs. diseased).
2
Evaluate the effect of a raised threshold on healthy individuals (those without the disease).
Fewer healthy individuals will exceed the new, higher threshold. Therefore, false positives will decrease.
Specificity is the ability to correctly identify individuals without the disease [True Negatives / (True Negatives + False Positives)].
3
Correlate the decrease in false positives with the correct statistical parameter.
A decrease in false positives mathematically corresponds to an increase in true negatives, which increases the overall specificity of the test.
Sensitivity and specificity have an inverse relationship when cut-offs are adjusted; increasing the threshold favors specificity at the expense of sensitivity.

Key Concept

Adjusting diagnostic test cut-off thresholds
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Topics

Diagnostic Testing Performance

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