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Devyanshi Dixit: Why Is Ovarian Cancer Still So Difficult to Detect Early?

Devyanshi Dixit/LinkedIn

Sep 2, 2026, 16:35

Devyanshi Dixit: Why Is Ovarian Cancer Still So Difficult to Detect Early?

Devyanshi Dixit, Program Manager at CLS Event and Publication and Conference Manager at the 12th Global Summit on Gynecology, shared on LinkedIn:

”Why Is Ovarian Cancer Still So Difficult to Detect Early?

Ovarian cancer is often called a ‘silent’ cancer.

The bigger problem is that its early symptoms can be subtle, common, and easily mistaken for everyday conditions.

And by the time persistent symptoms raise concern, the disease may already be more advanced.

What Makes Early Detection So Difficult?

Symptoms can be vague

Bloating, pelvic or abdominal discomfort, feeling full quickly, urinary changes, or changes in bowel habits can have many causes.

There is no reliable routine screening test for average – risk women

Unlike cervical cancer, there is currently no established population-wide screening strategy proven to reduce ovarian cancer mortality.

Imaging has limitations

Ultrasound can identify ovarian abnormalities, but distinguishing benign findings from early cancer can be challenging.

Biomarkers aren’t the complete answer – yet

Markers such as CA-125 can support evaluation in appropriate clinical settings, but they are not specific enough to serve as a standalone screening test for the general population.

Cancer isn’t one disease

Ovarian cancers are biologically diverse. Different molecular pathways can behave very differently, making one universal detection strategy difficult.

Where Is Research Heading?

The next generation of detection may combine:

Genomic and molecular biomarkers
Liquid biopsy and circulating tumor DNA
Artificial intelligence and predictive analytics
Multi-marker blood tests
Advanced imaging and image analysis
Individualized risk prediction

At the 12th Global Summit on Gynecology, Fertility and Women’s Health (GFW 2026), experts will explore emerging advances in gynecologic oncology, precision medicine, molecular diagnostics, AI, and women’s healthcare.