Skip to main content
. Author manuscript; available in PMC: 2023 Aug 2.
Published in final edited form as: Cancer Epidemiol Biomarkers Prev. 2022 Aug 2;31(8):1517–1520. doi: 10.1158/1055-9965.EPI-22-0232

Table 1.

Screening accuracy classification based on observed screening results, observed cancer diagnoses during accuracy assessment interval, and true cancer status at screening

Screening test result Cancer diagnosed during accuracy assessment interval No cancer diagnosed during accuracy assessment interval
Positive Cancer is truly present: Correct true positives (cTP) Cancer is truly absent: Correct False Positive (cFP)
and and
Cancer is truly absent: Incorrect true positives (iTP) (should be false positives) Cancer is truly present: Incorrect False Positive (iFP) (should be true positives)
Misclassifying false positives as true positives:
  • increases estimated sensitivity by inflating its numerator

  • increases estimated specificity by deflating its denominator

Misclassifying true positives as false positives:
  • decreases estimated sensitivity by deflating its numerator

  • decreases estimated specificity by inflating its denominator

Negative Cancer is truly present: Correct False Negative (cFN) Cancer is truly absent: Correct True Negative (cTN)
and and
Cancer is truly absent: Incorrect False Negative (iFN) (should be true negatives) Cancer is truly present: Incorrect True Negative (iTN) (should be false negatives)
Misclassifying true negatives as false negatives:
  • decreases estimated sensitivity by inflating its denominator

  • decreases estimated specificity by deflating its numerator

Misclassifying false negatives as true negatives:
  • increases estimated sensitivity by deflating its denominator

  • increases estimated specificity by inflating its numerator

cTP=correct true positive, cTN=correct true negative, cFP=correct false positive, cFN=correct false negative, iTP=incorrect true positive, iTN=incorrect true negative, iFP=incorrect false positive, iFN=incorrect false negative