Disease-free survival estimates for ovarian cancer improve over time

April 4, 2014 by Allison Hydzik

The probability of staying disease-free improves dramatically for ovarian cancer patients who already have been disease-free for a period of time, and time elapsed since remission should be taken into account when making follow-up care decisions, according to a study led by researchers at the University of Pittsburgh Cancer Institute (UPCI), a partner with UPMC CancerCenter.

A patient's prognosis traditionally is determined when they are diagnosed with a disease or when they become disease-free. However, for patients who already have survived or been disease-free for a number of years, these estimates may no longer be accurate because prognosis usually improves over time. Determining a prognosis that takes into account time elapsed since remission may be a more accurate benchmark. This measure is known as conditional disease-free .

"Having more accurate information about the risk of recurrence will allow patients and clinicians to make better informed decisions regarding follow-up care after cancer treatment. It also may lead to patients having a better quality of life because a more accurate diagnosis can ease their fears about the cancer coming back," said Brenda Diergaarde, Ph.D., a UPCI researcher who will present the findings Wednesday at the American Association for Cancer Research (AACR) Annual Meeting 2014.

In the study, researchers estimated disease-free survival and conditional disease-free survival for 404 patients who had achieved remission and whose information was collected as part of the Hormones and Ovarian Cancer Prediction (HOPE) case-control study. The researchers found disease-free survival estimates for ovarian improved dramatically over time, in particular among those with poorer initial prognoses. At time of remission, the probability of staying disease-free for three more years was 48 percent. This increased to 98 percent for patients who had remained disease-free for five years after .

Explore further: Biomarkers predict time to ovarian cancer recurrence

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