UVA grant award collaborators: (top, l-r) Jennifer Lobo, PhD; Stephen Culp, MD, PhD; Tracey Krupski, MD; (bottom, l-r) Heman Shakeri, PhD; Guofen Yan, PhD; and Noah Schenkman, MD.
Decision-making can be difficult, but when it comes to cancer treatment, that difficulty can be multiplied enormously due to the many unknowns dealing with cancer. However, researchers from UVA, the University of California at San Francisco (UCSF), and the University of Wisconsin (UW) received a nearly $1.5 million grant award from the National Cancer Institute of the National Institutes of Health to build a decision-making model that can help physicians together with their patients make better decisions for kidney cancer treatment. The four-year project began on July 1, 2023 and is entitled, “Optimizing Treatment Decision Making for Patients with Localized Renal Mass”.
The main principal investigators are Jennifer Lobo, PhD (Public Health Sciences) and Stephen Culp, MD, PhD (Urology) from UVA. Other Co-Investigators from UVA are Guofen Yan, PhD (Public Health Sciences), Heman Shakeri, PhD (Data Science), Tracey Krupski, MD (Urology), and Noah Schenkman, MD (Urology). External collaborators are Maxwell Meng, MD (Urology, UCSF) and E. Jason Abel, MD (Urology, UW). According to Dr. Lobo, Contact-PI from UVA SOM’s Department of Public Health Sciences, “We are collecting EPIC electronic health record data from all three academic hospitals: UVA, UCSF, and UW. Collected data will be used to understand care patterns for kidney cancer patients and calibrate the decision-making model to help guide future treatment plans. We’re hopeful that future work can create a shared decision-making tool for patients, families, and providers.”
Each year in the US thousands of people are diagnosed with renal cell carcinoma, or kidney cancer, one of the 10 most common cancers in the US. Two thirds of kidney cancer cases consist of localized renal masses (LRMs) confined to the kidney. Treatment varies, especially since many of these masses may be benign or unlikely to metastasize. Another major aim when choosing the best treatment is preservation of renal function. While removing the entire kidney would prevent any chance of local recurrence, it would greatly reduce a patient’s kidney function, potentially leading to end stage renal disease. Doctors have four major options of treatment: observation over time (active surveillance), treatment of the mass with a needle from outside the patient’s body (ablation), surgery to remove only the mass and leave the rest of the kidney (partial nephrectomy), or surgery to remove the entire affected kidney (radical nephrectomy). However, few studies have focused on the general outcomes of treatment and the effect on quality of life, so decisions are still very difficult.
This new project will collect and analyze data on patients and their kidney cancer treatments from electronic health records at the three academic hospitals. The information on the patient will include the general health of the patient, kidney function, and details of the kidney mass. Other information collected will include any biopsy information collected prior to cancer treatment and which treatments patients choose. Then the researchers will use the Markov decision process model and the patient information to develop a set of rules for managing kidney cancer treatment.
Dr. Lobo added, “With this decision-making model doctors and their patients will identify treatment options based on the patient’s goals for quality of life and to minimize their treatment costs. Our work will enable patients and their doctors to participate in a shared decision-making process to make treatment decisions based on the projected outcomes that will be most beneficial to the patient.”
Congratulations to these UVA researchers and their colleagues on receiving this award to pursue such an important project to help physicians and their patients to enhance patients’ quality of life!