Accuracy of diagnostic algorithms for suspected or elevated risk of ovarian cancer

Background

To substantially improve the overall prognosis of ovarian cancer, the accepted paradigm is: improved and safe pre-operative diagnostics.There is currently no single diagnostic method that has sufficiently high sensitivity/specificity to make an accurate and risk-free pre-operative diagnosis.

Today in Sweden the initial diagnostic method used for suspected disease (unclear symptoms or incidental findings) is algorithm-based. The algorithms are based on a combination of several diagnostic modalities (usually ultrasound, biochemical tumor markers) with different accuracy, which together with a simple clinical assessment (usually current endocrine status) form their basis.

The algorithms have not undergone any formalized evaluation in a Swedish context. The latest major systematic review from Cochrane was published in 2022. The review has an almost 5-year-old end date for literature search, and the risk population (including BRCA 1/2 gene mutations) was not included in the study.

Aim

Overall aim of the evaluation is to evaluate the accuracy of different diagnostic algorithms for suspected or elevated risk of ovarian cancer.

Sub-objectives of the evaluation:
a) to evaluate whether there is sufficient and acceptable accuracy of a diagnostic algorithm for the diagnosis?
b) which of the diagnostic algorithms studied has the highest accuracy?