Radiation therapy for augmenting the efficacy of immunotherapy in advanced non-small cell lung cancer: a case-controlled study

Assessing Potential Factors Influencing the Efficacy of Immune Checkpoint Inhibitors with Radiation in Advanced Non-Small-Cell Lung Cancer Patients: A Systematic Review and Meta-Analysis

Objective

Recent evidence suggests that combining radiotherapy (RT) with immune checkpoint inhibitors (ICIs) may result in better outcomes. In this study, we assessed the efficacy and safety of ICI plus radiation versus ICI alone and explored potential factors affecting its efficacy in advanced non-small-cell lung cancer (NSCLC) patients.

Methods

The databases including PubMed and Embase were searched to retrieve eligible studies comparing the efficacy and safety outcomes in advanced NSCLC patients after ICIs ± RT treatments. We performed subgroup analyses to identify potential prognostic factors from radiation details and study types. The odds ratio (OR) of objective response rate (ORR) and disease control rate (DCR), hazard ratio (HR) of progression-free survival (PFS) and overall survival (OS), and risk ratio (RR) of adverse events were used to represent the outcome effects.

Results

26 eligible studies with 14192 cases were included. The results showed that the ORR (OR = 0.63, 95% CI: 0.42, 0.93; p = 0.02) and DCR (OR = 0.55, 95% CI: 0.36, 0.82; p < 0.01) of RT + ICIs groups were significantly higher than those of the ICIs alone group. The median PFS and OS for ICIs versus RT + ICIs were 2.2 versus 4.4 months and 9.0 versus 13.4 months, respectively. Patients in the ICIs plus RT group had a significantly better PFS (HR = 0.72, 95% CI: 0.64, 0.81; p < 0.01) and OS (HR = 0.74, 95% CI: 0.65, 0.83; p < 0.01) when compared to those in the ICIs group. In terms of adverse events, the risk of pneumonia was not significantly increased in patients treated with both ICIs and RT when compared to ICIs group alone (risk ratio = 0.89; 95% CI: 0.55, 1.44; p = 0.63). The correlation analysis found that PFS was significantly correlated with OS (p = 0.02). The subgroup analysis results showed that significant improvements in OS were observed in non-palliative RT group (HR = 0.29, 95% CI: 0.13, 0.65; p < 0.01) and extracranial RT group (HR = 0.70, 95% CI: 0.59, 0.83; p < 0.01). RT type could also be a prognostic factor associated with the OS (for conventional RT: HR = 0.68 and p = 0.22; for stereotactic body radiation therapy: HR = 0.77 and p < 0.01). However, concerning RT timing, the results showed a similar trend in reducing mortality risk (for previous RT: HR = 0.64 and p = 0.21; for concurrent RT: HR = 0.35 and p = 0.16).

Conclusion

RT plus ICIs is associated with improved survival for advanced NSCLC patients, especially for those with non-palliative RT. Further clinical trials are needed to validate its effect on survival outcomes.

A Mathematical Modeling Approach for Targeted Radionuclide and Chimeric Antigen Receptor T Cell Combination Therapy

Simple Summary

Targeted radionuclide therapy (TRT) and immunotherapy, an example being chimeric antigen receptor T cells (CAR-Ts), represent two potent means of eradicating systemic cancers. Although each one as a monotherapy might have a limited effect, the potency can be increased with a combination of the two therapies. The complications involved in the dosing and scheduling of these therapies make the mathematical modeling of these therapies a suitable solution for designing combination treatment approaches. Here, we investigate a mathematical model for TRT and CAR-T cell combination therapies. Through an analysis of the mathematical model, we find that the tumor proliferation rate is the most important factor affecting the scheduling of TRT and CAR-T cell treatments with faster proliferating tumors requiring a shorter interval between the two therapies.

Abstract

Targeted radionuclide therapy (TRT) has recently seen a surge in popularity with the use of radionuclides conjugated to small molecules and antibodies. Similarly, immunotherapy also has shown promising results, an example being chimeric antigen receptor T cell (CAR-T) therapy in hematologic malignancies. Moreover, TRT and CAR-T therapies possess unique features that require special consideration when determining how to dose as well as the timing and sequence of combination treatments including the distribution of the TRT dose in the body, the decay rate of the radionuclide, and the proliferation and persistence of the CAR-T cells. These characteristics complicate the additive or synergistic effects of combination therapies and warrant a mathematical treatment that includes these dynamics in relation to the proliferation and clearance rates of the target tumor cells. Here, we combine two previously published mathematical models to explore the effects of dose, timing, and sequencing of TRT and CAR-T cell-based therapies in a multiple myeloma setting. We find that, for a fixed TRT and CAR-T cell dose, the tumor proliferation rate is the most important parameter in determining the best timing of TRT and CAR-T therapies.