Pneumonitis after immune checkpoint inhibitor therapies in patients with acute myeloid leukemia: A retrospective cohort study

Practice Changes in Checkpoint Inhibitor-Induced Immune-Related Adverse Event Management at a Tertiary Care Center

Understanding of immune-related adverse events (irAEs) has evolved rapidly, and management guidelines are continually updated. We explored temporal changes in checkpoint inhibitor-induced irAE management at a tertiary cancer care center to identify areas for improvement. We conducted a single-center retrospective study of patients who developed a gastrointestinal, pulmonary, renal, or cardiac irAE between July and 1 October in 2019 or 2021. We collected patient demographic and clinical information up to 1 year after toxicity. Endoscopic evaluation and specialty follow-up after discharge for patients with gastrointestinal irAEs declined between the 2019 and 2021 periods. Symptom duration and steroid taper attempts also declined. For pulmonary irAEs, rates of specialty consultation, hospital admission and readmission, and mortality improved in 2021 compared with 2019. Follow-up rates after hospital discharge were consistently low (<50%) in both periods. For cardiac irAEs, consultation with a cardiologist was frequent and prompt in both periods. Outpatient treatment and earlier specialty consultation improved outcomes with gastrointestinal irAEs. Our study exploring irAE practice changes over time identified areas to improve management; specifically, timely specialty consultation was associated with better outcomes for gastrointestinal irAEs. These findings can help improve the quality of management algorithms at our institution and may inform policies in other institutions.

Pulmonary Immune-Related Adverse Events of PD-1 Versus PD-L1 Checkpoint Inhibitors: A Retrospective Review of Pharmacovigilance

Introduction

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapeutics. However, immune-related adverse events (irAEs) increase morbidity and mortality and thereby limit therapeutic utility. The real-world incidence of the entire spectrum of pulmonary irAEs has not been systematically described. The objective of this study is to assess the risk of developing pulmonary irAEs (pneumonitis, pleural events [i.e., effusion and pleurisy], exacerbations of airway disease [i.e., bronchitis and bronchiectasis], and sarcoidosis) with exposure to five commonly used ICIs: nivolumab, pembrolizumab, durvalumab, avelumab, and atezolizumab.

Methods

We conducted a retrospective review of the Food and Drug Administration Adverse Events Reporting System (FAERS) pharmacovigilance database. We collected data from 2012 to 2021 to assess the risk of pulmonary irAEs and performed a disproportionality analysis using Open-Vigil, a software package used for analysis of pharmacovigilance data, to calculate reporting odds ratios (RORs). We used 95% CIs to evaluate the precision of RORs. An ROR greater than 1 and the upper limit of the 95% CI indicated statistical significance.

Results

A total of 17,273,403 events were reported in FAERS between 2012 and 2021. Of these, 88,099 (0.5%) were attributed to the PD-1 (programmed cell death protein 1) inhibitors and 21,905 (0.1%) to PD-L1 (programmed death ligand 1) inhibitors of interest. The most common indication for using the ICIs of interest was lung cancer: a total of 2832 (46.70%) for the PD-1 inhibitors and 1311 (70.9%) for the PD-L1 inhibitors. In the anti-PD-1 group, 2342 (38.6%) patients were hospitalized, and 1962 (32.4%) patients died from the lung adverse event. In the PD-L1 group, 744 (40.3%) patients were hospitalized, and 520 (28.1%) patients died from the event. Nivolumab resulted in the highest statistically significant risk (ROR, 10.5; 95% CI, 10.1-10.9) for pneumonitis. Avelumab had a lesser risk for pneumonitis (ROR, 0.2; 95% CI, 0.2-0.3). The risk for pleural events was highest with nivolumab (ROR, 3.6; 95% CI, 3.4-3.9), followed by pembrolizumab (ROR, 1.8; 95% CI; 1.6-2.0) (p < 0.001), with the lowest risks from durvalumab, atezolizumab, and avelumab. For ICI-related sarcoidosis, the risk was most significant with pembrolizumab (ROR, 3.6; 95% CI, 2.8-4.7), followed by nivolumab (ROR, 2.5; 95% CI, 1.9-3.5) (p < 0.001). The RORs for all five ICIs were less than 1 for exacerbations of airway diseases as compared with other drugs.

Conclusion

Using a pharmacovigilance database, we found an increased risk of multiple pulmonary irAEs after ICI therapy, particularly with PD-1 inhibitors. Further work is needed to investigate the incidence of pulmonary irAEs other than pneumonitis.

Pneumonitis After Concurrent Chemoradiation and Immune Checkpoint Inhibition in Patients with Locally Advanced Non-small Cell Lung Cancer

AIMS

Pneumonitis is a common and potentially deadly complication of combined chemoradiation and immune checkpoint inhibition (CRT-ICI) in patients with locally advanced non-small cell lung cancer (LA-NSCLC). In this study we sought to identify the risk factors for pneumonitis with CRT-ICI therapy in LA-NSCLC cases and determine its impact on survival.

MATERIALS AND METHODS

We conducted a retrospective chart review of 140 patients with LA-NSCLC who underwent curative-intent CRT-ICI with durvalumab between 2018 and 2021. Pneumonitis was diagnosed by a multidisciplinary team of clinical experts. We used multivariable cause-specific hazard models to identify risk factors associated with grade ≥2 pneumonitis. We constructed multivariable Cox proportional hazard models to investigate the impact of pneumonitis on all-cause mortality.

RESULTS

The median age of the cohort was 67 years; most patients were current or former smokers (86%). The cumulative incidence of grade ≥2 pneumonitis was 23%. Among survivors, 25/28 patients had persistent parenchymal scarring. In multivariable analyses, the mean lung dose (hazard ratio 1.14 per Gy, 95% confidence interval 1.03-1.25) and interstitial lung disease (hazard ratio 3.8, 95% confidence interval 1.3-11.0) increased the risk for pneumonitis. In adjusted models, grade ≥2 pneumonitis (hazard ratio 2.5, 95% confidence interval 1.0-6.2, P = 0.049) and high-grade (≥3) pneumonitis (hazard ratio 8.3, 95% confidence interval 3.0-23.0, P < 0.001) were associated with higher all-cause mortality.

CONCLUSIONS

Risk factors for pneumonitis in LA-NSCLC patients undergoing CRT-ICI include the mean radiation dose to the lung and pre-treatment interstitial lung disease. Although most cases are not fatal, pneumonitis in this setting is associated with markedly increased mortality.

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

Background

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.

Materials and methods

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.

Results

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%).

Conclusion

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.

Common methodological pitfalls in ICI pneumonitis risk prediction studies

Background

Pneumonitis is one of the most common adverse events induced by the use of immune checkpoint inhibitors (ICI), accounting for a 20% of all ICI-associated deaths. Despite numerous efforts to identify risk factors and develop predictive models, there is no clinically deployed risk prediction model for patient risk stratification or for guiding subsequent monitoring. We believe this is due to systemic suboptimal approaches in study designs and methodologies in the literature. The nature and prevalence of different methodological approaches has not been thoroughly examined in prior systematic reviews.

Methods

The PubMed, medRxiv and bioRxiv databases were used to identify studies that aimed at risk factor discovery and/or risk prediction model development for ICI-induced pneumonitis (ICI pneumonitis). Studies were then analysed to identify common methodological pitfalls and their contribution to the risk of bias, assessed using the QUIPS and PROBAST tools.

Results

There were 51 manuscripts eligible for the review, with Japan-based studies over-represented, being nearly half (24/51) of all papers considered. Only 2/51 studies had a low risk of bias overall. Common bias-inducing practices included unclear diagnostic method or potential misdiagnosis, lack of multiple testing correction, the use of univariate analysis for selecting features for multivariable analysis, discretization of continuous variables, and inappropriate handling of missing values. Results from the risk model development studies were also likely to have been overoptimistic due to lack of holdout sets.

Conclusions

Studies with low risk of bias in their methodology are lacking in the existing literature. High-quality risk factor identification and risk model development studies are urgently required by the community to give the best chance of them progressing into a clinically deployable risk prediction model. Recommendations and alternative approaches for reducing the risk of bias were also discussed to guide future studies.

Characterization of immunomodulatory factors and cells in bronchoalveolar lavage fluid for immune checkpoint inhibitor-related pneumonitis

As immune checkpoint inhibitors (ICIs) are widely used, a series of immune-related adverse events (irAEs) have been reported, including immune checkpoint inhibitor-related pneumonitis (ICI-pneumonitis). The incidence of ICI-pneumonitis is higher in reality than in clinical trials. The diagnosis is challenging, mainly based on clinical and imaging features, and requires the exclusion of other causes. The data on the biological mechanisms of ICI-pneumonitis are scarce, resulting in little knowledge of the best treatment for ICI-pneumonitis. Bronchoalveolar lavage (BAL) may be helpful to identify the biological differences or find predictive biomarkers, and may in turn help to develop phenotype-specific targeted drugs to treat ICI-pneumonitis. Herein, we outline the characterization of immunomodulatory factors and cells in bronchoalveolar lavage fluid for ICI-pneumonitis. Through careful sorting and literature review, we find crosstalk between pathogenic Th17/Th1 cells (i.e., Th17.1) and pro-inflammatory monocytes, and activation of Th17(/Th1)/IL-17A (/IFN-γ) pathways may play a key role in the pathogenesis of ICI-pneumonitis. Disruption of the interaction between pathogenic Th17/Th1 cells and pro-inflammatory monocytes (such as, anti-IL-23) may be a potential treatment for ICI-pneumonitis. We first describe the possible pathophysiological mechanisms of ICI-pneumonitis, hoping to contribute to the optimization of diagnosis and treatment, as well as provide readers with research inspiration.

Safety, Outcomes, and T-Cell Characteristics in Patients with Relapsed or Refractory MDS or CMML Treated with Atezolizumab in Combination with Guadecitabine

PURPOSE

We hypothesized that resistance to hypomethylating agents (HMA) among patients with myelodysplastic syndrome (MDS) and chronic myelomonocytic leukemia (CMML) would be overcome by combining a programmed death-ligand 1 antibody with an HMA.

PATIENTS AND METHODS

We conducted a Phase I/II, multicenter clinical trial for patients with MDS not achieving an International Working Group response after at least 4 cycles of an HMA ("refractory") or progressing after a response ("relapsed") with 3+ or higher risk MDS by the revised International Prognostic Scoring System (IPSS-R) and CMML-1 or -2. Phase I consisted of a 3+3 dose-escalation design beginning with guadecitabine at 30 mg/m2 and escalating to 60 mg/m2 Days 1 to 5 with fixed-dose atezolizumab: 840 mg intravenously Days 8 and 22 of a 28-day cycle. Primary endpoints were safety and tolerability; secondary endpoints were overall response rate (ORR) and survival.

RESULTS

Thirty-three patients, median age 73 (range 54-85), were treated. Thirty patients had MDS and 3 had CMML, with 30% relapsed and 70% refractory. No dose-limiting toxicities were observed in Phase I. There were 3 (9%) deaths in ≤ 30 days. Five patients (16%) came off study for drug-related toxicity. Immune-related adverse events (IRAE) occurred in 12 (36%) patients (4 grade 3, 3 grade 2, and 5 grade1). ORR was 33% [95% confidence interval (CI), 19%-52%] with 2 complete remission (CR), 3 hematologic improvement, 5 marrow CR, and 1 partial remission. Median overall survival was 15.1 (95% CI, 8.5-25.3) months.

CONCLUSIONS

Guadecitabine with atezolizumab has modest efficacy with manageable IRAEs and typical cytopenia-related safety concerns for patients with relapsed or refractory MDS and CMML.