Data analytics are becoming increasingly important in the healthcare field, particularly in determining the best treatments for targeting certain illnesses.
Recently, three Tennessee researchers studied a small sample of patients with metastatic breast cancer to determine how their life expectancy was affected by the treatments they received—specifically when they had “discordant receptors,” where the primary tumor receptors differed from the metastatic tumor receptors. The researchers found that those who followed treatment plans based on their primary tumors survived for 48 months, compared to 8.4 months for those who followed treatment plans based on their metastatic tumors.
The study was conceived by T. Allen Pannell Jr., now at Lincoln Memorial University in Harrogate, when he was working on his dissertation in statistics at the University of Tennessee, Knoxville. His wife developed metastatic breast cancer with discordant receptors, living three years after her initial diagnosis and only six months after her cancer reoccurrence. Pannell wanted to investigate how a specific kind of treatment might have shortened her life.
Pannell was joined in his research efforts by Russell L. Zaretzki, associate professor of business analytics at UT’s Haslam College of Business, and Timothy J. Panella, an oncologist at UT Medical Center.
The researchers admit the sample size is statistically small—only 14 of 317 patient cases at the University of Tennessee Cancer Institute fit all criteria for the study. But they believe the results are clear: the status of the primary tumor should take precedence when developing the first-line treatment plan for a patient with newly diagnosed recurrent metastatic breast cancer.
“The Prognostic Impact of Determining Treatment Plans Based on Discordant Metatastic Tumor Receptors on Relapse” was published in the American Journal of Hematology/Oncology.