Prevalence threshold of screening tests in obstetrics and gynecology.

Abstract

OBJECTIVE\nWe define the prevalence threshold as the prevalence level below which a test s positive predictive value (PPV) declines most sharply relative to disease prevalence - and thus the rate of false positive results/false discovery rate increases most rapidly. The objective of this study is to determine the prevalence threshold of various screening tests used in obstetrics and gynecology among low-risk women in modern clinical practice.\n\n\nMETHODS\nWe searched Medline, EMBASE, Google Scholar, Scopus, ISI Web of Science, Cochrane database, and PubMed to obtain the sensitivity and specificity estimates for the following screening tests: 50\u2009g-oral glucose tolerance test (GDM-50\u2009g), non-invasive prenatal testing (NIPT), combined first trimester screening (FTS), vagino-rectal swab for group B streptococcus (GBS) in pregnancy, cervical cytology (Pap) and HPV testing, mammography and manual breast exam, urinary PCR and cervical-vaginal swab testing for gonorrhoea and chlamydia as well as AMH for the diagnosis of PCOS. We used these estimates to calculate disease-specific prevalence thresholds, comparing them to the actual estimates of disease prevalence.\n\n\nRESULTS\nThe prevalence thresholds and average estimates of disease prevalence (shown in brackets) are as follows: GDM-50\u2009g 31 % (6%), NIPT 7% (0.2 %), combined FTS 19.5 % (0.2 %), GBS swab 18 % (15-45 %), Pap 21 % (0.2 %), HPV 27 % (0.2 %), mammography 25 % (12.5 %), breast exam 25 % (12.5 %), gonorrhoea -chlamydia 6-13 % (4.2-4.7 %), AMH for PCOS 32 % (10 %).\n\n\nCONCLUSION\nThe prevalence thresholds of various screening tests used in obstetrics and gynecology are well above the estimated disease prevalence. This implies that when undertaking population-level screening a significant proportion of positive screening tests obtained are likely false-positives. Attempts at individualizing pre-test probability when undertaking population-level screening are needed in order to best interpret the results of screening tests.