New Research: Using Mathematics to Treat Ovarian Cancer
The need for new research
New research into the diagnosis and treatment of ovarian cancer has been sorely needed. Early term diagnostic issues and low survival rates in the latter stages of the disease have been crying out for a response. The results of the Alber-Stark study are encouraging; fresh eyes and a new perspective of combined team approach have reinforced this need and uncovered a possible solution to enhance treatment.
To understand how the new findings would work, it’s necessary to first talk of some basic details about ovarian cancer.
A major challenge with diagnosing ovarian cancer is the absence of definitive symptoms, even in its later stages. Back pain, fatigue, vague stomach pain, bloating, and urinary frequency and/or urgency are some of the most common symptoms. As the symptoms are rather general, the condition is difficult to diagnose.
The original suspicion of ovarian cancer is often triggered when a pelvic mass is discovered during an internal gynecological exam. Unfortunately, about 70% of women are already in advanced Stage IV ovarian cancer when diagnosed. The five-year survival rate for Stage IV is 17%.
While there is no established preventive course for ovarian cancer, such as immunization, for example, the Alber-Stark team has developed an encouraging hypothesis for the treatment of ovarian cancer. If their continued research outcomes remain favorable, ovarian cancer survival rates could be greatly improved.
