Risk factors for immune checkpoint inhibitor-related pneumonitis in non-small cell lung cancer

Abstract

Background: Immune checkpoint inhibitors (ICIs) have led to dramatic improvements in survival a subset of patients with non-small cell lung cancer (NSCLC); however, they have been shown to cause life-threatening toxicity such as immune checkpoint inhibitor-related pneumonitis (CIP). Our previous studies have shown that chronic obstructive pulmonary disease (COPD) and circulating cytokines are associated with clinical outcomes in NSCLC patients receiving ICIs. However, the relationship between these factors and the development of CIP is unclear. In this study, we retrospectively assessed NSCLC patients receiving ICIs to identify CIP risk factors.

Methods: This retrospective cohort study reviewed medical records of NSCLC patients receiving ICIs targeting programmed cell death 1 (PD-1) or its ligand PD-L1 between March 2017 and December 2020 at Zhongshan Hospital Fudan University. CIP was diagnosed by the treating investigator. Clinical characteristics and baseline plasma cytokines were collected. Logistic regression was used to compare clinical characteristics and circulating cytokine levels between patients with and without CIP to identify CIP risk factors.

Results: Of 164 NSCLC patients who received ICIs, CIP developed in 20 cases (12.2%). The presence of COPD [odds ratio (OR), 7.194; 95% confidence interval (CI): 1.130 to 45.798; P=0.037] and PD-L1 expression of ≥50% (OR, 7.184; 95% CI: 1.154 to 44.721; P=0.035) were independently associated with a higher incidence of CIP, whereas a higher baseline level of interleukin-8 (IL-8) was associated with a lower incidence of CIP (OR, 0.758; 95% CI: 0.587 to 0.978; P=0.033). The independent risk factors from final multivariate analysis were incorporated into a nomogram to predict the incidence of CIP. The nomogram model receiver operating characteristic (ROC) curve had a good predictive accuracy of 0.883 (95% CI: 0.806 to 0.959).

Conclusions: Increased risk of CIP independently associated with history of COPD, tumor PD-L1 expression ≥50%, and low baseline IL-8 level. The nomogram may hold promise for CIP risk assessment in the administration of ICIs.

Keywords: Immune checkpoint inhibitor (ICI); immune checkpoint inhibitor-related pneumonitis (CIP); non-small cell lung cancer (NSCLC); risk factor.

Figure 1

Time from initiation of ICIs therapy to date of CIP event stratified by grade, with median and interquartile range shown. ICI, immune checkpoint inhibitor; CIP, immune checkpoint inhibitor-related pneumonitis.

Figure 2

Bar graphs showing the clinical and radiographic features of CIP. (A) Relative frequency of CTCAE pneumonitis severity grade; (B) relative frequency of CIP radiographic patterns; (C) the number of clinical symptoms in COPD patients at the time of CIP diagnosis; (D) the number of clinical symptoms in non-COPD patients at the time of CIP diagnosis. CIP, immune checkpoint inhibitor-related pneumonitis; CTCAE, Common Terminology Criteria for Adverse Events; COPD, chronic obstructive pulmonary disease; COP, cryptogenic organizing pneumonitis; GGO, ground-glass opacity; NOS, not otherwise specified.

Figure 3

Risk factors of CIP. (A) The optimal cutoff value of IL-8 was 9 pg/mL by ROC curve analysis with AUC =0.744; (B) risk factors of CIP developing in the multivariate logistic regression analysis model with forest plots. ROC curve, receiver operating characteristic curve; AUC, area under curve; OR, odds ratio; CI, confidence interval; CIP, immune checkpoint inhibitor-related pneumonitis; COPD, chronic obstructive pulmonary disease; PD-L1, programmed cell death-ligand 1; IL, interleukin.

Figure 4

Nomogram was constructed with COPD, PD-L1 expression, and the baseline IL-8 level for predicting the occurrence of CIP in NSCLC patients. The first line is a reference line for reading scoring points for each prediction parameter. The points are added together and marked on the Total points line. The figure on this line indicates the predicted risk that the patient will experience CIP. COPD, chronic obstructive pulmonary disease; PD-L1, programmed cell death-ligand 1; IL, interleukin; CIP, immune checkpoint inhibitor-related pneumonitis.

Figure 5

Validation of the nomogram model. (A) ROC curve analyses the nomogram model for predicting the occurrence of CIP. The AUC is 0.883; (B) calibration curves for predicting the occurrence of CIP. The diagonal line is the reference line, indicating the probability of an ideal nomogram. ROC curve, receiver operating characteristic curve; AUC, area under curve; CIP, immune checkpoint inhibitor-related pneumonitis.