Inflammatory Markers Can Help Predict Treatment Response in Patients With Metastatic Renal Cell Carcinoma

A new study published in JAMA Oncology presents a notable advancement in predicting the effectiveness of treatment for metastatic renal cell carcinoma. The study led by Dr. Niklas Klümper, a resident at the Department of Urology and Pediatric Urology at the University Hospital Bonn (UKB) and a working group leader at the Institute for Experimental Oncology (IEO), along with Dr. Jonas Saal, a resident at the Medical Clinic III for Oncology, Hematology, Immune-Oncology, and Rheumatology of the UKB, achieved this by incorporating the level of inflammation evaluated using two simple blood parameters, in addition to the conventional imaging-based approach.

Metastatic renal cell carcinoma, the most prevalent type of kidney cancer, is typically treated with a combination of immunotherapies as the primary approach. The purpose of these treatments is to stimulate the patient's immune system, enabling it to identify and combat cancerous cells. As a result of their high efficacy, these initial therapies currently achieve disease management in more than 80% of individuals diagnosed with metastatic renal cell carcinoma.

Limitations of imaging

Accurate prediction of treatment response is crucial for effective patient care. Unfortunately, in routine clinical practice, the evaluation of treatment response often relies solely on imaging, typically computed tomography (CT), which provides an imprecise estimation of tumor volume. However, relying solely on tumor volume assessment is insufficient to accurately determine which patients will derive long-term benefits from immunotherapy. To optimize and guide therapy more effectively, it is essential to incorporate additional markers that can predict future disease progression. These complementary markers are necessary to enhance the precision of treatment prediction and ensure optimal patient management.

Improvement of the therapy response in the blood

Dr. Klümper and his research team demonstrated that by examining two commonly found and affordable inflammatory markers in the blood, namely C-reactive protein (CRP) and albumin, it is now possible to significantly enhance the accuracy of predicting treatment response in patients with metastatic renal cell carcinoma. This improvement is particularly noteworthy in the subgroup of patients where the disease is under control during the initial follow-up period, which accounts for over 80% of cases. As a result, the authors strongly recommend incorporating both radiologic imaging and supplementary analysis of inflammation levels into the monitoring process for patients with metastatic renal cell carcinoma in the future.

Dr. Klümper stated that this innovative method for improving therapy monitoring and predicting treatment response relies on a fusion of imaging techniques and evaluating inflammation levels using two easily obtainable blood parameters: CRP and albumin. These parameters are integrated into the well-established modified Glasgow Prognosis Score (mGPS). The research findings are based on patient groups involved in two distinct randomized trials concentrating on metastatic renal cell carcinoma. The outcomes strongly endorse the prompt adoption of the mGPS as a prognostic tool for foreseeing outcomes in individuals with a diagnosis of metastatic renal cell carcinoma.

The mGPS scoring system is established by attributing a single point to patients with an increased serum CRP concentration (> 10 mg/L), and an additional point is assigned only to those with elevated CRP if their serum albumin level is below 35 g/L. Based on these criteria, patients are classified into three risk categories: low risk (0 points), intermediate risk (1 point), and high risk (2 points).

Dr. Saal emphasized that both blood parameters, CRP and albumin, are easily accessible and cost-effective to measure. As a result, they can be readily incorporated into clinical practice worldwide, enhancing the monitoring of cancer patients' therapy. By improving the ability to predict treatment failure, these parameters can help identify patients who would potentially benefit from a therapy change or intensification. Dr. Saal also stressed the need for further studies to explore and expand upon this concept.