(May 5, 2015) Data from a large clinical trial shows that a personalized method for interpreting blood tests identifies more ovarian cancer cases than a generalized approach. The results from the study will be published in the Journal of Clinical Oncology.
Using an algorithm to analyze changes in the level of CA-125 (a protein in blood that can be elevated in the presence of ovarian cancer) over time was better at predicting ovarian cancer, compared to waiting until the protein level reached a general “cut-off” point, researchers found.
This new method detected invasive epithelial ovarian cancer in 86 percent of the women, which is significantly better than the results of previous screening trials. While the results are promising, the study’s lead author, Dr. Usha Menon of University College London, said it’s too soon to use the new screening method in general practice.
“It looks like we picked up cancers in more people earlier,” said Dr. Menon. “Now the next question is, did we save these women’s lives by picking them up earlier?”
The researchers began the new study with data from the UK Collaborative Trial of Ovarian Cancer Screening (or UKCTOCS) — this largest ever ovarian cancer screening trial involved 202,638 women over the age of 50. For 46,237 women, researchers tested their blood once a year for CA-125 levels and then used a computer algorithm to interpret their risk of ovarian cancer based on her age, her original levels of CA-125, and the changes in her level.
Read more here (Reuters Health).
