by A new risk model developed by researchers at the University of Eastern Finland and Kuopio University Hospital can help identify cancer patients who are most likely to benefit from treatment with immune checkpoint inhibitors (ICIs). ICIs are antibodies that sensitize the body’s immune system to detect and destroy tumors, but their effectiveness varies among patients. The risk model, published in BMC Cancer, uses six inflammation-related laboratory parameters to classify patients into low-risk and high-risk groups.
Senior Researcher Aino Rönkä explains that with a risk model that predicts treatment outcomes, treatment can be better targeted at patients who are more likely to benefit from ICIs. The study cohort consisted of patients receiving ICIs for metastatic cancers at Kuopio University Hospital Cancer Center. The researchers assigned a risk score of 0-6 to patients based on elevated values of neutrophils, platelets, C-reactive protein (CRP), lactate dehydrogenase, erythrocyte sedimentation rate, and the presence of anemia.
Patients were then classified into two groups: those with a risk score of 0-3 in the low-risk group with a good prognosis, and those with a risk score of 4-6 in the high-risk group with a poor prognosis. The study found that 53.9% of patients in the low-risk group responded to ICIs, while the response rate in the high-risk group was 30.3%. The median overall survival was 27.3 months in the low-risk group and 10 months in the high-risk group. The risk model was effective in all common cancer types studied, including lung cancer, melanoma, and renal cell carcinoma.
The risk scoring developed in this study is based on routine blood work, making it a practical predictive model that can easily be integrated into the treatment assessment of cancer patients. By targeting ICIs to patients who are most likely to benefit, the efficacy, safety, and cost-effectiveness of treatment can be improved. However, the researchers emphasize that further validation of the model is needed in a prospective, multi-center setting.
In conclusion, a risk model based on inflammation-related laboratory parameters has been developed by researchers to help identify metastatic cancer patients who may benefit from treatment with immune checkpoint inhibitors. This model can improve treatment outcomes by better targeting ICIs to patients who are more likely to respond to them. Although the model shows promise, further validation is necessary to establish its efficacy in a larger and more diverse patient population.
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1. Source: Coherent Market Insights, Public sources, Desk research
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