Prognostic models for immunotherapy of lung and urology cancers

Giuseppe Luigi Banna

Consultant Medical Oncologist, Portsmouth Hospitals NHS Trust, Portsmouth, PO6 3LY, United Kingdom

Inflammation is a hallmark of cancer. Numerous cell types and cytokines act as inflammatory mediators promoting tumour cell proliferation and progression, suppressing the immune response by altering the tumour microenvironment. Elements of full blood count may serve as a proxy of a deranged pro-inflammatory response, prognosticators and predictive factors for immune checkpoint inhibitors (ICIs).

Baseline neutrophils-to-lymphocytes ratio (NLR) and systemic immune-inflammatory index (SII, i.e., NLR x platelets) have been validated as prognosticators for ICIs in different tumour types, particularly thoracic cancer, like non-small cell lung cancer (NSCLC) and mesothelioma, renal and urothelial cancers. They can improve the accuracy of tumour type-specific contemporary prognostic models to inform patients about their prognosis, drive cost-effective treatments, identify early immune-related adverse events (irAEs) and for clinical trial stratification. Early changes in neutrophils and NLR are dynamic prognostic factors.

As for their advantages, they are relatively inexpensive and available on a routine basis. Disadvantages are required cut-offs, their non-necessarily predictive role and the need to combine with other tumour type-specific factors

Examples of prognostic models based on peripheral blood-derived inflammatory indexes we developed are LIPS-3 for real-world patients with high PD-L1 NSCLC approaching ICIs; NLR/PDL1 combination which is prognostic and predictive of the response to ICIs in NSCLC; ETOP-MRS prognostic score in the second-line treatment of mesothelioma; Meet-URO prognostic model for risk stratification of patients with metastatic renal cell cancer; and the ITACA score for metastatic urothelial cancer receiving ICIs.