Development and validation of nomograms for predicting efficacy and toxicity in cancer patients treated with immune checkpoint inhibitors

Worldwide, cancer incidence and mortality are growing rapidly, with 18.1 million new cancer cases and 9.6 million deaths from cancer predicted in 2018. Advanced cancers are difficult to treat. Immune checkpoint inhibitors that target programmed cell death 1(PD-1) or its ligand 1 (PD-L1) monoclonal antibodies, such as nivolumab, pembrolizumab, atezolizumab and durvalumab are increasingly used for the treatment of several cancers (e.g. lung cancer and bladder cancer). The clinical outcomes of a minority of cancer patients have improved substantially after the US Food and Drug Administration (FDA) approval of immune checkpoint inhibitors for cancer treatments. However, a substantial proportion of patients do not respond to immune checkpoint inhibitors, while they can be associated with a range of potentially life-threatening immune-related adverse events (irAEs). The beneficial role of immunotherapy with the clinical relevance of clinical factors and biological factors in cancer patients remain inconclusive.

We aim to develop clinical tools that can predict immunotherapy response/toxicity in metastatic non-small cell lung cancer patients and metastatic urothelial bladder cancer patients, respectively. The conducted nomogram model may support new immune checkpoint inhibitor therapy development, trial design, and personalized treatment in clinical practice.

Pooled post hoc analyses of individual participant data from a series of clinical trials on atezolizumab will be conducted. Examples of predictors to be explored include patient characteristics, laboratory and clinical factors, biomarkers, co-morbidities and concomitant medications. Furthermore, we intend to validate the prediction performance of conducted nomogram model by a separate cohort.

Recently, our research team has published an article titled “A nomogram for predicting survival and retroperitoneal lymph node dissection treatment in patients with resected testicular germ cell tumors” in Journal of Surgical Oncology [1]. This nomogram model can be used for response prediction and mechanistic optimization of cancer treatments in individual patients.

References
[1]Y. Wu, J.P. Meyers, G. Shi, Z. Jin, J. Xia, Y. Gu, Q. Qian, Y. Hong, A nomogram for predicting survival and retroperitoneal lymph node dissection treatment in patients with resected testicular germ cell tumors. J Surg Oncol 120 (2019) 508-517.