Checkpoint Inhibitor Pneumonitis Research Articles

The relative risk of immune checkpoint inhibitor pneumonitis in advanced non-small- cell lung cancer: Meta-analyses of controlled clinical trials.

Immune checkpoint inhibitor pneumonitis (CIP) is a prevalent form of immunotherapy-induced pulmonary toxicity, ranking among the leading causes of mortality associated with immune checkpoint inhibitors (ICIs). Despite its significance, the risk stratification of CIP in advanced non-small cell lung cancer (NSCLC) remains uncertain. In this study, we conducted a comprehensive analysis, comparing various factors such as histological types, treatment regimens, PD-L1 expression levels, and EGFR/ALK negativity in advanced NSCLC. Our investigation extends to evaluating the relative risk of developing CIP based on previous treatment history. This analysis aims to provide valuable insights for the identification of specific patient subgroups at higher risk, facilitating more effective risk management and precision therapy approaches. PubMed, Embase, and Cochrane databases were systematically searched up to February 16, 2023. We conducted a screening of randomized controlled trials (RCTs) that compared ICI monotherapy or its combination with chemotherapy in advanced NSCLC. The trials were categorized based on histological type, treatment regimen, PD-L1 expression level, EGFR/ALK-negative status, and prior treatment history. Subsequently, the data were stratified into five subgroups, and the occurrences of all-grades (1-5) and high-grades (3-5) pneumonia events were extracted. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were then calculated for further analysis. Twenty-two RCTs, encompassing 13,725 patients with advanced NSCLC, were included in this analysis. Regardless of histology (OR = 2.47, 95% CI 1.41-4.33, P = 0.002; OR = 1.84, 95% CI 1.10-3.09, P = 0.02), treatment regimen (OR = 3.27, 95% CI 2.00-5.35, P < 0.00001; OR = 2.91, 95% CI 1.98-4.27, P < 0.00001), PD-L1 expression level (OR = 5.11, 95% CI 2.58-10.12, P < 0.00001; OR = 5.15, 95% CI 2.48-10.70, P < 0.0001), negative EGFR/ALK expression (OR = 4.32, 95% CI 2.22-8.41, P < 0.0001; OR = 3.6, 95% CI 1.56-8.28, P = 0.003), whether there is a history of treatment (OR = 3.27, 95% CI 2.00-5.35, P < 0.00001; OR = 2.74, 95% CI 1.75-4.29, P < 0.0001), ICI use was associated with a higher risk of all-grade (1-5) and high-grade (3-5) pneumonia compared to chemotherapy. Subgroup analysis revealed that the squamous group, the ICI vs. combination chemotherapy (CT) group, the PD-L1 > 50% group, and the previously untreated group had a higher risk of developing all-grade and grade 3-5 CIP (P < 0.05). In advanced NSCLC, ICI treatment was linked to an elevated risk of pneumonitis across all grades (1-5) as well as high-grade occurrences (3-5) compared to chemotherapy. Notably, individuals with squamous histology and high PD-L1 expression, along with those lacking a history of prior treatment, demonstrated a heightened susceptibility to developing immune-related pneumonitis of all grades (1-5) and high grades (3-5). These observations provide valuable insights for clinicians seeking to enhance the management of pulmonary toxicity associated with immunotherapy.

A retrospective study of combination therapy with glucocorticoids and pirfenidone for PD-1 inhibitor-related immune pneumonitis.

Immune checkpoint inhibitor pneumonitis (ICIP) is thought to be a self-limiting disease; however, an effective treatment option does not currently exist. This study aimed to determine the clinical efficacy of combination therapy with glucocorticoids and pirfenidone for ICIP related to programmed cell death protein-1 (PD-1) inhibitors. We conducted a retrospective analysis of 45 patients with advanced non-small cell lung cancer who developed ICIP following PD-1 inhibitor and albumin-bound paclitaxel or carboplatin treatment at our hospital. The PD-1 inhibitor was discontinued, and glucocorticoids were used alone or in combination with pirfenidone to treat ICIP. The relevant clinical data of these patients were collected and analyzed. Compared with the glucocorticoid alone group, the glucocorticoid-pirfenidone group showed significant improvement in forced vital capacity (FVC), carbon monoxide diffusing capacity [%], peripheral capillary oxygen saturation, and 6-minute walk distance (P < .05). There were benefits with respect to the St. George's Respiratory Questionnaire score and the recurrence rate of ICIP, but there was no significant difference between the 2 groups (P > .05). Adding pirfenidone to glucocorticoid treatment was shown to be safe and may be more beneficial than glucocorticoids alone for improving pulmonary interstitial lesions, reversing ICIP, and preventing its recurrence.

Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis

BackgroundPneumonitis is a well-described, potentially disabling, or fatal adverse effect associated with both immune checkpoint inhibitors (ICI) and thoracic radiotherapy. Accurate differentiation between checkpoint inhibitor pneumonitis (CIP) radiation pneumonitis (RP), and infective pneumonitis (IP) is crucial for swift, appropriate, and tailored management to achieve optimal patient outcomes. However, correct diagnosis is often challenging, owing to overlapping clinical presentations and radiological patterns. MethodsIn this multi-centre study of 455 patients, we used machine learning with radiomic features extracted from chest CT imaging to develop and validate five models to distinguish CIP and RP from COVID-19, non-COVID-19 infective pneumonitis, and each other. Model performance was compared to that of two radiologists. ResultsModels to distinguish RP from COVID-19, CIP from COVID-19 and CIP from non-COVID-19 IP out-performed radiologists (test set AUCs of 0.92 vs 0.8 and 0.8; 0.68 vs 0.43 and 0.4; 0.71 vs 0.55 and 0.63 respectively). Models to distinguish RP from non-COVID-19 IP and CIP from RP were not superior to radiologists but demonstrated modest performance, with test set AUCs of 0.81 and 0.8 respectively. The CIP vs RP model performed less well on patients with prior exposure to both ICI and radiotherapy (AUC 0.54), though the radiologists also had difficulty distinguishing this test cohort (AUC values 0.6 and 0.6). ConclusionOur results demonstrate the potential utility of such tools as a second or concurrent reader to support oncologists, radiologists, and chest physicians in cases of diagnostic uncertainty. Further research is required for patients with exposure to both ICI and thoracic radiotherapy.

Clinical features and prognostic analysis of checkpoint inhibitor pneumonitis in patients with non-small cell lung cancer

Objective: To describe the clinical characteristics of patients with non-small cell lung cancer (NSCLC) who developed checkpoint inhibitor pneumonitis (CIP) and to explore potential prognostic factors. Methods: NSCLC patients who were complicated with CIP after immune checkpoint inhibitors (ICIs) therapy in our institute were enrolled in this study from 1 July 2018 to 30 November 2022. Clinical data of NSCLC-CIP patients were collected, including clinical and radiological features and their outcomes. Results: Among the 70 enrolled NSCLC-CIP patients, there were 57 males (81%) and 13 females (19%). The mean age at the diagnosis of CIP was (65.2±6.3) years. There were 46 smokers (66%), 26 patients (37%) with emphysema, 19 patients (27%) with previous interstitial lung disease, and 26 patients (37%) with a history of thoracic radiation. The mean interval from the first application of checkpoint inhibitor to the onset of CIP was (122.7±106.9) days (range: 2-458 days). The main chest CT manifestations were coincided with non-specific interstitial pneumonia (NSIP) pattern and organizing pneumonia (OP) pattern. Most patients had grade 2 (21 cases) or grade 3 (34 cases) CIP. Seventeen patients had been concurrent with other immune-related adverse events such as rash, hepatitis, colitis, and thyroiditis. Half of the enrolled patients (36 patients/51%) had fever, and most patients had elevated C-reactive protein (52 patients/72%) and all patients had elevated erythrocyte sedimentation rate (70 patients/100%). Serum lactate dehydrogenase was elevated in 34 CIP patients. Prednisone≥1 mg·kg-1·d-1 (or equivalent) was the most commonly used initial treatment in CIP patients (50 patients/71.4%). Complications with pulmonary infections (OR=4.44, P=0.03), use of anti-fungal drugs (OR=5.10, P=0.03) or therapeutic dose of sulfamethoxazole (OR=4.86, P=0.04), longer duration of prednisone≥1 mg·kg-1·d-1 (or equivalent) (Z=-2.33, P=0.02) were probable potential risk factors for poor prognosis. Conclusions: Older males with smoking history might be predisposed to develop NSCLC-CIPs after ICIs therapy. NSIP pattern and OP pattern were common chest CT manifestations. Complications with pulmonary infections (especially fungal infection or Pneumocystis jirovecii pneumonia), longer duration, longer duration of high-dose corticosteroids were likely potential risk factors for poor prognosis.

Quantification of preexisting lung ground glass opacities on CT for predicting checkpoint inhibitor pneumonitis in advanced non-small cell lung cancer patients

BackgroundImmune checkpoint inhibitors (ICIs) can lead to life-threatening pneumonitis, and pre-existing interstitial lung abnormalities (ILAs) are a risk factor for checkpoint inhibitor pneumonitis (CIP). However, the subjective assessment of ILA and the lack of standardized methods restrict its clinical utility as a predictive factor. This study aims to identify non-small cell lung cancer (NSCLC) patients at high risk of CIP using quantitative imaging.MethodsThis cohort study involved 206 cases in the training set and 111 cases in the validation set. It included locally advanced or metastatic NSCLC patients who underwent ICI therapy. A deep learning algorithm labeled the interstitial lesions and computed their volume. Two predictive models were developed to predict the probability of grade ≥ 2 CIP or severe CIP (grade ≥ 3). Cox proportional hazard models were employed to analyze predictors of progression-free survival (PFS).ResultsIn a training cohort of 206 patients, 21.4% experienced CIP. Two models were developed to predict the probability of CIP based on different predictors. Model 1 utilized age, histology, and preexisting ground glass opacity (GGO) percentage of the whole lung to predict grade ≥ 2 CIP, while Model 2 used histology and GGO percentage in the right lower lung to predict grade ≥ 3 CIP. These models were validated, and their accuracy was assessed. In another exploratory analysis, the presence of GGOs involving more than one lobe on pretreatment CT scans was identified as a risk factor for progression-free survival.ConclusionsThe assessment of GGO volume and distribution on pre-treatment CT scans could assist in monitoring and manage the risk of CIP in NSCLC patients receiving ICI therapy.Clinical relevance statementThis study’s quantitative imaging and computational analysis can help identify NSCLC patients at high risk of CIP, allowing for better risk management and potentially improved outcomes in those receivingICI treatment.

Pulmonary toxicity of immune checkpoint immunotherapy.

Cancer remains a leading cause of mortality on a global scale. Lung cancer, specifically non-small cell lung cancer (NSCLC), is a prominent contributor to this burden. The management of NSCLC has advanced substantially in recent years, with immunotherapeutic agents, such as immune checkpoint inhibitors (ICIs), leading to improved patient outcomes. Although generally well tolerated, the administration of ICIs can result in unique side effects known as immune-related adverse events (irAEs). The occurrence of irAEs involving the lungs, specifically checkpoint inhibitor pneumonitis (CIP), can have a profound effect on both future therapy options and overall survival. Despite CIP being one of the more common serious irAEs, limited treatment options are currently available, in part due to a lack of understanding of the underlying mechanisms involved in its development. In this Review, we aim to provide an overview of the epidemiology and clinical characteristics of CIP, followed by an examination of the emerging literature on the pathobiology of this condition.

Immune checkpoint inhibitors in patients with lung cancer having chronic interstitial pneumonia.

In interstitial pneumonia (IP)-associated lung cancer, immune checkpoint inhibitor pneumonitis (ICIP) is common with immune checkpoint inhibitor (ICI) treatment. The purpose of the present study was to clarify the safety and efficacy of ICI treatment for patients with lung cancer with IP. This multicentre retrospective observational study was conducted from June 2016 to December 2020 in patients with primary lung cancer with IP who received ICI treatment. A total of 200 patients (median age 70 years; male/female, 176/24) were enrolled from 27 institutions. ICIP occurred in 61 patients (30.5%), pneumonitis grades 3-5 in 32 patients (15.5%) and death in nine patients (4.5%). The common computed tomography pattern of ICIP was organising pneumonia in 29 patients (47.5%). Subsequently, diffuse alveolar damage (DAD) pattern was observed in 19 patients (31.1%) who had a significantly worse prognosis than those with a non-DAD pattern (median progression-free survival (PFS) 115 days versus 226 days, p=0.042; median overall survival (OS) 334 days versus 1316 days, p<0.001). Immune-related adverse events (irAEs) occurred in approximately 50% of patients. Patients with irAEs (n=100) had a better prognosis than those without irAEs (n=100) (median PFS 200 days versus 77 days, p<0.001; median OS 597 days versus 390 days p=0.0074). The objective response rate and disease control rate were 41.3% and 68.5%, respectively. Although ICI treatment was effective for patients with lung cancer with IP, ICIP developed in approximately 30% of patients. Patients with irAEs had a significantly better PFS and OS than those without irAEs.

The Clinical Analysis of Checkpoint Inhibitor Pneumonitis with Different Severities in Lung Cancer Patients: A Retrospective Study.

Immune-related adverse events (irAEs) of immunotherapy would lead to the temporary or permanent discontinuation of immune checkpoint inhibitors (ICIs). Among them, checkpoint inhibitor pneumonitis (CIP) is a potentially life-threatening irAE. This study aimed to identify the differences between patients with low-grade CIPs (grades 1-2) and high-grade CIPs (grades 3-5) and to explore the prognostic factors. We retrospectively reviewed the medical records of 916 lung cancer patients who were treated with ICIs. Patients with CIPs were identified after multidisciplinary discussion, and their clinical, laboratory, radiological, and follow-up data were analyzed. Among the 74 enrolled CIP patients, there were 31 low-grade CIPs and 43 high-grade CIPs. Compared with low-grade CIP patients, patients with high-grade CIPs were older (65.8 years vs. 61.5 years) and had lower serum albumin (35.2 g/L vs. 37.9 g/L), higher D-dimer (5.1 mg/L vs. 1.7 mg/L), and more pulmonary infectious diseases (32.6% vs. 6.5%) during follow-up. In addition, complication with pulmonary infectious diseases, management with intravenous immunoglobulin, tocilizumab, and longer duration of large dosage corticosteroids might be associated with worse outcomes for patients with CIPs. This study highlights potential risk factors for high-grade CIP and poor prognosis among lung cancer patients who were treated with anti-cancer ICIs.

Durvalumab-Associated Pneumonitis in Patients with Locally Advanced Non-Small Cell Lung Cancer: A Real-World Population Study.

The PACIFIC trial led to a new standard of care for patients with locally advanced lung cancer, but real-world practice has demonstrated that immune checkpoint inhibitor (ICI) pneumonitis can lead to significant clinical complications. This study aimed to examine the clinical predictors, outcomes, and healthcare utilization data in patients who received consolidation durvalumab. Using the Alberta Immunotherapy Database, NSCLC patients who received durvalumab in Alberta, Canada, from January 2018 to December 2021 were retrospectively evaluated. We examined incidence and predictive values of severe pneumonitis, with overall survival (OS) and time-to-treatment failure (TTF) using exploratory multivariate analyses. Of 189 patients, 91% were ECOG 0-1 and 85% had a partial response from chemoradiation prior to durvalumab. Median TTF and OS were not reached; 1-year OS was 82%. An amount of 26% developed any grade of pneumonitis; 9% had ≥grade 3 pneumonitis. Male gender and a pre-existing autoimmune condition were associated with severe pneumonitis. V20 was associated with any grade of pneumonitis. Pneumonitis development was found to be an independent risk factor for worse OS (p = 0.038) and TTF (p = 0.007). Our results suggest clinical and dosimetric predictive factors of durvalumab-associated pneumonitis. These results affirm the importance of careful patient selection for safe completion of consolidation durvalumab in real-world LA-NSCLC population.

435MO Initial strategy of corticosteroids-immunosuppressant treatment and the consequent clinical outcome among non-small cell lung cancer patients with severe checkpoint inhibitor pneumonitis: A real-world study

435MO Initial strategy of corticosteroids-immunosuppressant treatment and the consequent clinical outcome among non-small cell lung cancer patients with severe checkpoint inhibitor pneumonitis: A real-world study

Association Between Pretreatment Chest Imaging and Immune Checkpoint Inhibitor Pneumonitis Among Patients With Lung Cancer.

Immune checkpoint inhibitors (ICIs) are a first-line and perioperative treatment for lung cancer. Pneumonitis is a potentially life-threatening complication of ICI treatment in 2% to 5% of patients; however, risk factors for developing ICI pneumonitis (ICI-p) remain undefined. We conducted a retrospective cohort study of consecutive patients with lung cancer who received at least one dose of ICI from 2015 through 2020 at The Ohio State University. Pneumonitis cases were documented by the treating oncologist and retrospectively evaluated for agreement between an oncologist and a pulmonologist. Patient demographic and clinical characteristics were recorded and summarized between those with and without pneumonitis for the overall cohort. Univariate and multivariable survival analyses using the Fine-Gray competing risk model were used to examine the associations. A total of 471 patients with lung cancer were included, of which 402 had non-small cell lung cancer and 69 had small cell lung cancer; 39 (8%) patients in the overall cohort developed ICI-p. Preexisting interstitial abnormalities and prior chest radiation were both significantly associated with ICI-p on univariate analysis (hazard ratio [HR], 8.91; 95% CI, 4.69-16.92; P<.001; and HR, 2.81; 95% CI, 1.50-5.28; P=.001). On multivariable analyses, interstitial abnormalities remained a strong independent risk factor for ICI-p when controlling for chest radiation and type of immunotherapy (HR, 9.77; 95% CI, 5.17-18.46; P<.001). Among patients with ICI-p (n=39), those with severe (grade 3-5) pneumonitis had worse overall survival compared with those with mild (grade 1 or 2) pneumonitis (P=.001). Abnormal pulmonary function test results at both 12 and 18 months prior to ICI initiation were not significantly associated with ICI-p. Preexisting interstitial abnormalities on chest CT and prior chest radiation are independent risk factors that are strongly associated with ICI-p in patients with lung cancer. These findings highlight a potential need for closer observation for ICI-p among patients with these risk factors.

P2.07-08 Checkpoint Inhibitor Pneumonitis Model for NSCLC based onPreexistingLung Ground Glass Opacities: Development and Validation

P2.07-08 Checkpoint Inhibitor Pneumonitis Model for NSCLC based onPreexistingLung Ground Glass Opacities: Development and Validation

195P Identification of biomarkers associated with checkpoint inhibitor pneumonitis based on serum proteomic approach and construction of an online interactive visual prediction model

195P Identification of biomarkers associated with checkpoint inhibitor pneumonitis based on serum proteomic approach and construction of an online interactive visual prediction model

Heterogenous lung inflammation CT patterns distinguish pneumonia and immune checkpoint inhibitor pneumonitis and complement blood biomarkers in acute myeloid leukemia: proof of concept.

Immune checkpoint inhibitors (ICI) may cause pneumonitis, resulting in potentially fatal lung inflammation. However, distinguishing pneumonitis from pneumonia is time-consuming and challenging. To fill this gap, we build an image-based tool, and further evaluate it clinically alongside relevant blood biomarkers. We studied CT images from 97 patients with pneumonia and 29 patients with pneumonitis from acute myeloid leukemia treated with ICIs. We developed a CT-derived signature using a habitat imaging algorithm, whereby infected lungs are segregated into clusters ("habitats"). We validated the model and compared it with a clinical-blood model to determine whether imaging can add diagnostic value. Habitat imaging revealed intrinsic lung inflammation patterns by identifying 5 distinct subregions, correlating to lung parenchyma, consolidation, heterogenous ground-glass opacity (GGO), and GGO-consolidation transition. Consequently, our proposed habitat model (accuracy of 79%, sensitivity of 48%, and specificity of 88%) outperformed the clinical-blood model (accuracy of 68%, sensitivity of 14%, and specificity of 85%) for classifying pneumonia versus pneumonitis. Integrating imaging and blood achieved the optimal performance (accuracy of 81%, sensitivity of 52% and specificity of 90%). Using this imaging-blood composite model, the post-test probability for detecting pneumonitis increased from 23% to 61%, significantly (p = 1.5E - 9) higher than the clinical and blood model (post-test probability of 22%). Habitat imaging represents a step forward in the image-based detection of pneumonia and pneumonitis, which can complement known blood biomarkers. Further work is needed to validate and fine tune this imaging-blood composite model and further improve its sensitivity to detect pneumonitis.

Anti‑PD‑1/PD‑L1 and anti‑CTLA‑4 associated checkpoint inhibitor pneumonitis in non‑small cell lung cancer: Occurrence, pathogenesis and risk factors (Review).

Immune checkpoint inhibitors (ICIs) play a significant anti‑tumor role in the management of non‑small cell lung cancer. The most broadly used ICIs are anti‑programmed death 1 (PD‑1), anti‑programmed cell death‑ligand 1, and anti‑cytotoxic T lymphocyte‑associated antigen‑4 monoclonal antibody. Compared with traditional chemotherapy, ICIs have the advantages of greater efficiency and more specific targeting. However, the resulting immune‑related adverse events limit the clinical application of ICIs, especially checkpoint inhibitor pneumonitis (CIP). CIP chiefly occurs within 6 months of administration of ICIs. Excessive activation and amplification of cytotoxic T lymphocytes, helper T cells, downregulation of regulatory T cells, and over‑secretion of pro‑inflammatory cytokines are the dominant mechanisms underlying the pathophysiology of CIP. The dysregulation of innate immune cells, such as an increase in inflammatory monocytes, dendritic cells, neutrophils and M1 polarization of macrophages, an increase in IL‑10 and IL‑35, and a decrease in eosinophils, may underlie CIP. Although contested, several factors may accelerate CIP, such as a history of previous respiratory disease, radiotherapy, chemotherapy, administration of epidermal growth factor receptor tyrosine kinase inhibitors, PD‑1 blockers, first‑line application of ICIs, and combined immunotherapy. Interestingly, first‑line ICIs plus chemotherapy may reduce CIP. Steroid hormones remain the primary treatment strategy against grade ≥2 CIP, although cytokine blockers are promising therapeutic agents. Herein, the current research on CIP occurrence, clinical and radiological characteristics, pathogenesis, risk factors, and management is summarized to further expand our understanding, clarify the prognosis, and guide treatment.

Deciphering pathogenic cellular module at single-cell resolution in checkpoint inhibitor-related pneumonitis

Checkpoint inhibitor pneumonitis (CIP) is the most common fatal immune-related adverse event; however, its pathophysiology remains largely unknown. Comprehensively dissecting the key cellular players and molecular pathways associated with CIP pathobiology is critical for precision diagnosis and develop novel therapy strategy of CIP. Herein, we performed a comprehensive single-cell transcriptome analysis to dissect the complexity of the immunological response in the bronchoalveolar lavage fluid (BALF) microenvironment. CIP was characterized by a dramatic accumulation of CXCL13+ T cells and hyperinflammatory CXCL9+ monocytes. T-cell receptor (TCR) analysis revealed that CXCL13+ T cells exhibited hyperexpanded- TCR clonotypes, and pseudotime analysis revealed a potential differentiation trajectory from naïve to cytotoxic effector status. Monocyte trajectories showed that LAMP3+ DCs derived from CXCL9+ monocytes possessed the potential to migrate from tumors to the BALF, whereas the differentiation trajectory to anti-inflammatory macrophages was blocked. Intercellular crosstalk analysis revealed the signaling pathways such as CXCL9/10/11-CXCR3, FASLG-FAS, and IFNGR1/2-IFNG were activated in CIP+ samples. We also proposed a novel immune signature with high diagnostic power to distinguish CIP+ from CIP− samples (AUC = 0.755). Our data highlighted key cellular players, signatures, and interactions involved in CIP pathogenesis.

Establish a whole-process comprehensive surveillance management mode for immune checkpoint inhibitor pneumonitis

The application of immune checkpoint inhibitors (ICIs) has shown impressive anti-tumor efficacy across multiple malignant tumors, leading to the prolonged survival period of tumor patients. However, immune-related adverse events should not be ignored. Checkpoint inhibitor pneumonitis (CIP) is a pulmonary adverse event that can occur in malignant tumor patients after receiving ICIs treatment. The incidence of CIP has been reported to range from 2.7% to 20.0% in clinical trials and real-world research. Furthermore, some patients might suffer from serious or fatal CIP, and the prognosis of such patients will be poor. Early detection, diagnosis and treatment may improve the prognosis of these patients. The establishment of a whole-process CIP comprehensive surveillance management mode covering the health care system and patients during ICIs treatment might be helpful to improve the early diagnosis and treatment capacity of CIP, which is a key measure to improve the prognosis of these patients.

Abnormalities on baseline chest imaging are risk factors for immune checkpoint inhibitor associated pneumonitis

BackgroundChronic lung disease is a proposed risk factor for immune checkpoint inhibitor pneumonitis (ICI-pneumonitis); however, data is sparse regarding the impact of pre-existing lung disease and baseline chest imaging abnormalities on the risk of developing ICI-pneumonitis. MethodsWe conducted a retrospective cohort study of patients with ICI treatment for cancer from 2015 to 2019. ICI-pneumonitis was determined by the treating physician with corroboration via an independent physician review and exclusion of alternative etiologies. Controls were patients treated with ICI without a diagnosis of ICI-pneumonitis. Fisher's exact tests, Student's t-tests, and logistic regression were used for statistical analysis. ResultsWe analyzed 45 cases of ICI-pneumonitis and 135 controls. Patients with abnormal baseline chest CT imaging (emphysema; bronchiectasis; reticular, ground glass and/or consolidative opacities) had increased risk for ICI-pneumonitis (OR 3.41, 95%CI: 1.68–6.87, p = 0.001). Patients with gastroesophageal reflux disease (GERD) (OR 3.83, 95%CI: 1.90–7.70, p = < 0.0001) also had increased risk for ICI-pneumonitis. On multivariable logistic regression, patients with abnormal baseline chest imaging and/or GERD remained at increased risk for ICI-pneumonitis. Eighteen percent of all patients (32/180) had abnormal baseline chest CT consistent with chronic lung disease without a documented diagnosis. ConclusionPatients with baseline chest CT abnormalities and GERD were at increased risk for developing ICI-pneumonitis. The large proportion of patients with baseline radiographic abnormalities without a clinical diagnosis of chronic lung disease highlights the importance of multidisciplinary evaluation prior to ICI initiation.

Radiomics to predict checkpoint inhibitor pneumonitis based on chest CT scans in patients with advanced cancer.

e20550 Background: Checkpoint inhibitor pneumonitis (CIP) is a concerning immune-related adverse event responsible for treatment discontinuation, hospitalization, with acknowledged possible fatal cases. The aim of our study was to assess the potential role of machine learning models, combining pre-treatment CT lung radiomic features with clinical data, to predict the risk of developing CIP. Methods: A cohort of 116 patients with different type advanced malignancies (81% lung cancer, 14% melanoma, 8% other solid tumors) treated with immune checkpoint inhibitors (ICIs) were retrospectively enrolled in this study and divided into a CIP (n = 35) and a control group (n = 81). Each patients had a chest CT scan at baseline and associated clinical covariates. Lungs and lobes were segmented semi-automatically on pre-treatment CT scans. We extracted radiomics features and selected them by the Minimum Redundancy Maximum Relevance (mRMR) method. Clinical-only, radiomics-only, and clinical-radiomics models (both lung- and lobe-based) were built using generalized linear (GLM) and random forest (RF) models to predict the occurrence of CIP. A nested 5-fold cross-validation scheme was used in the training, validation and test sets. Model performances were assessed in terms of Area under the Curve (AUC). Results: The most accurate clinical (RF) and the best radiomic (lobe-based GLM) models achieved AUCs of 0.72 (95%CI:0.51-0.92) and 0.71 (95%CI:0.58-0.84) on the test set, respectively. No statistically significant differences have been found between lung- and lobe-based radiomic models. The RF model combining lung-based radiomic and clinical features showed the best performances overall with an AUC of 0.75 (95%CI:0.62-0.88) on the test set. Conclusions: CT-based lung radiomic, and clinical models alone show moderate to good performances at identifying patients at risk of developing CIP. Nevertheless, we demonstrated the added value of machine learning models built combining clinical and radiomic features to better stratify the risk of developing CIP in patients with advanced malignancies treated with ICIs.

Analysis of cytokines in bronchoalveolar lavage fluid in patients with checkpoint inhibitor pneumonitis and pulmonary infection: A case-control study.

The discovery of immune checkpoint inhibitors (ICIs) is a breakthrough in the field of cancer therapy. However, ICIs may cause immune-related adverse reactions, including checkpoint inhibitor-related pneumonitis (CIP). The aim of this study was to investigate cytokines in bronchoalveolar lavage fluid (BALF) of patients with CIP compared with patients with pulmonary infection and patients with cancer. We retrospectively analyzed 34 cytokine levels and T cell subsets in BALF supernatant samples from ICI-treated patients with CIP (n = 13), pulmonary infection (n = 10), and progressive cancer (n = 12). Cytokine levels and T cell subsets were compared among the three groups of patients. We observed significantly higher levels of IFN-γ-induced protein 10(IP-10) (p = 0.002), and percentage of CD3 + CD8 + T cells (p = 0.020) in BALF of patients with CIP compared with the other two groups. However, we found significantly lower levels of interleukin-21 (p = 0.008) in BALF of patients with progressive disease compared with the other two groups. Cytokine profile and character of cell subsets in BALF was helpful for the differential diagnosis of CIP. IP-10 may play an important role in pathophysiology for CIP and also be a potential therapeutic target.