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Zorluk: OrtaDiagnostic Testing Performance

An armed forces medical induction center is initiating a screening protocol for latent tuberculosis infection among incoming personnel. The protocol utilizes a highly standardized interferon-gamma release assay. Epidemiological surveillance indicates that the true prevalence of latent tuberculosis in this incoming cohort of 5,0005,000 recruits is exactly 4%4\%. The laboratory parameters for this specific assay demonstrate a sensitivity of 90%90\% and a specificity of 98%98\%.

If a recruit from this cohort receives a positive result on this assay, what is the probability that the individual actually has a latent tuberculosis infection? (Enter the value as a percentage rounded to the nearest whole number).

Cevap: 65 %

Cevap

65
The question asks for the probability that a patient with a positive test result actually has the disease, which is the definition of Positive Predictive Value (PPV). To calculate PPV, one must account for the prevalence of the disease in the specific cohort being tested. Using a 2x2 contingency table for the population of 5,0005,000 recruits, a prevalence of 4%4\% equates to 200200 individuals with latent tuberculosis and 4,8004,800 healthy individuals. Given a sensitivity of 90%90\%, the assay will correctly identify 180180 of the 200200 diseased individuals (True Positives). Given a specificity of 98%98\%, the false positive rate is 2%2\%; therefore, the assay will incorrectly flag 9696 of the 4,8004,800 healthy individuals (False Positives). The total number of positive test results is the sum of True Positives and False Positives (180+96=276180 + 96 = 276). The PPV is the ratio of True Positives to Total Positives (180/276180 / 276), which equals 0.65210.6521. Converted to a percentage and rounded to the nearest whole number, the correct probability is 65%65\%.

Adım Adım Çözüm

1
Determine the true disease status distribution in the cohort.
200 recruits have latent TB; 4,800 do not.
Pre-test probability (prevalence) is required to establish the baseline numbers of true positive and true negative candidates in the population.
2
Calculate the number of True Positives.
180 True Positives.
Sensitivity (90%90\%) dictates the proportion of the 200 diseased individuals who will correctly test positive (200×0.90200 \times 0.90).
3
Calculate the number of False Positives.
96 False Positives.
Specificity is 98%98\%, meaning the false positive rate is 2%2\%. Applying this false positive rate to the 4,800 healthy individuals (4,800×0.024,800 \times 0.02) yields 96.
4
Calculate the Positive Predictive Value (PPV).
65.2%, rounded to 65%.
PPV is the ratio of True Positives to all positive test results: 180/(180+96)=180/276=0.6521180 / (180 + 96) = 180 / 276 = 0.6521.

Anahtar Kavram

Positive Predictive Value (PPV) depends heavily on the disease prevalence in the tested population, in addition to the test's sensitivity and specificity.
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