Addition of Radiotherapy to Immunotherapy: Effects on Outcome of Different Subgroups Using a Propensity Score Matching

Abstract

Immune checkpoint inhibition (ICI) has been established as successful modality in cancer treatment. Combination concepts are used to optimize treatment outcome, but may also induce higher toxicity rates than monotherapy. Several rationales support the combination of radiotherapy (RT) with ICI as radioimmunotherapy (RIT), but it is still unknown in which clinical situation RIT would be most beneficial. Therefore, we have conducted a retrospective matched-pair analysis of 201 patients with advanced-stage cancers and formed two groups treated with programmed cell death protein 1 (PD-1) inhibitors only (PD1i) or in combination with local RT (RIT) at our center between 2013 and 2017. We collected baseline characteristics, programmed death ligand 1 (PD-L1) status, mutational status, PD-1 inhibitor and RT treatment details, and side effects according to the Common Terminology Criteria for Adverse Events (CTCAE) v.5.0. Patients received pembrolizumab (n = 93) or nivolumab (n = 108), 153 with additional RT. For overall survival (OS) and progression-free survival (PFS), there was no significant difference between both groups. After propensity score matching (PSM), we analyzed 96 patients, 67 with additional and 29 without RT. We matched for different covariates that could have a possible influence on the treatment outcome. The RIT group displayed a trend towards a longer OS until the PD1i group reached a survival plateau. PD-L1-positive patients, smokers, patients with a BMI ≤ 25, and patients without malignant melanoma showed a longer OS when treated with RIT. Our data show that some subgroups may benefit more from RIT than others. Suitable biomarkers as well as the optimal timing and dosage must be established in order to achieve the best effect on cancer treatment outcome.

Keywords: PD-1/PD-L1; combination treatment; immune checkpoint inhibition; propensity score matching; radioimmunotherapy; radiotherapy; subgroups.

Figure A1

Kaplan–Meier survival curves for programmed death ligand 1 (PD-L1) expression. Kaplan–Meier survival curves comparing radioimmunotherapy (RIT) and immunotherapy alone (PD1i)—unmatched cohort. (A): PD-L1 expression < 1%, (B): PD-L1 expression ≥ 1%—< 50%, and (C): PD-L1 expression ≥ 50%. PD-L1 = programmed death ligand 1.

Figure A2

Kaplan–Meier survival curves for radiotherapy fractionation schemes. Kaplan–Meier survival curves comparing radioimmunotherapy (RIT) applied simultaneously (parallel) and sequentially (nonparallel)—unmatched cohort. (A): CFX = conventional fractionated radiotherapy and (B): SRS = stereotactic radiosurgery.

Figure 1

Z-differences before and after propensity score matching.

Figure 2

Kaplan–Meier survival curves comparing radioimmunotherapy (RIT) and immunotherapy alone (PD1i)—entire cohort. (A): OS = overall survival, (B): PFS = progression-free survival, and (C): OS differences in the programmed cell death 1 ligand 1 (PD-L1)-positive patient group.

Figure 3

Kaplan–Meier survival curves comparing radioimmunotherapy (RIT) and immunotherapy alone (PD1i)—matched cohort. (A): OS = overall survival, (B): OS differences in the PD-L1-positive patient group, (C): OS differences in smokers, (D): OS differences in nonsmokers, (E): OS differences in patients with a BMI ≤ 25, (F): OS differences in patients with a BMI > 25, (G): OS differences in the patient group with malignant melanoma, and (H): OS differences in the patient group without malignant melanoma.

Figure 3

Kaplan–Meier survival curves comparing radioimmunotherapy (RIT) and immunotherapy alone (PD1i)—matched cohort. (A): OS = overall survival, (B): OS differences in the PD-L1-positive patient group, (C): OS differences in smokers, (D): OS differences in nonsmokers, (E): OS differences in patients with a BMI ≤ 25, (F): OS differences in patients with a BMI > 25, (G): OS differences in the patient group with malignant melanoma, and (H): OS differences in the patient group without malignant melanoma.