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The diagnostic performance of CA-125 for the detection of ovarian cancer in women from different ethnic groups: a cohort study of English primary care data

  • Melissa Barlow*
  • , Liz Down
  • , Luke Mounce
  • , Garth Funston
  • , Samuel W D Merriel
  • , Jessica C Watson
  • , Gary A Abel
  • , Lucy Kirkland
  • , Tanimola Martins
  • , Sarah Bailey
  • *Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

5 Citations (Scopus)

Abstract

Background
CA-125 testing is a recommended first line investigation for women presenting with possible symptoms of ovarian cancer in English primary care, to help determine whether further investigation for ovarian cancer is needed. It is currently not known how well the CA-125 test performs in ovarian cancer detection for patients from different ethnic groups.

Methods
A retrospective cohort study utilising English primary care data linked to the national cancer registry was undertaken. Women aged ≥ 40 years with a CA-125 test between 2010 and 2017 were included. Logistic regression predicted one-year ovarian cancer incidence by ethnicity, adjusting for age, deprivation status, and comorbidity score. The estimated incidence of ovarian cancer by CA-125 level was modelled for each ethnic group using restricted cubic splines.

Results
The diagnostic performance of CA-125 differed for women from different ethnicities. In an unadjusted analysis, predicted CA-125 levels for Asian and Black women were higher than White women at corresponding probabilities of ovarian cancer. The higher PPVs for White women compared to Asian or Black women were eliminated by inclusion of covariates.

Conclusion
The introduction of ethnicity-specific thresholds may increase the specificity and PPVs of CA-125 in ovarian cancer detection at the expense of sensitivity, particularly for Asian and Black women. As such, we cannot recommend the use of ethnicity-specific thresholds for CA-125.
Original languageEnglish
Article number173
JournalJournal of Ovarian Research
Volume17
DOIs
Publication statusPublished - 26 Aug 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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