Establishment and validation of nomogram for predicting immuno checkpoint inhibitor related pneumonia

Risk factors for severe immune-related pneumonitis after nivolumab plus ipilimumab therapy for non-small cell lung cancer

BACKGROUND

The efficacy of anti-CTLA-4 antibody (ipilimumab) plus anti-programmed cell death 1 antibody (nivolumab) in treating advanced non-small cell lung cancer (NSCLC) is impeded by an elevated risk of severe immune-related adverse events. However, our understanding of associations among pre-existing fibrosis, emphysematous changes, and objective indicators as predictive factors is limited for severe pneumonitis in NSCLC patients receiving this combination therapy. Thus, we retrospectively investigated these associations, including overall tumor burden, before treatment initiation in the Japanese population.

METHODS

We focused on patients (n = 76) with pre-existing interstitial lung disease (ILD) to identify predictors of severe pneumonitis. Variables included age, sex, smoking status, programmed cell death ligand 1 expression, overall tumor burden, chest computed tomography-confirmed fibrosis, serum markers, and respiratory function test results.

RESULTS

Severe pneumonitis was more frequent in patients with squamous cell carcinoma, fibrosis, low diffusing capacity for carbon monoxide (%DLCO), and high surfactant protein D (SP-D) level. Notably, squamous cell carcinoma, baseline %DLCO, and SP-D level were significant risk factors. Our findings revealed the nonsignificance of tumor burden (≥85 mm) in predicting severe pneumonitis, emphasizing the importance of pre-existing ILD. Conversely, in cases without pre-existing fibrosis, severe pneumonitis was not associated with %DLCO or SP-D level (93.2% vs. 91.9%, and 63.3 vs. 40.9 ng/mL, respectively) and was more common in patients with a large overall tumor burden (97.5 vs. 70.0 mm).

CONCLUSION

Vigilant monitoring and early intervention are crucial for patients with squamous cell carcinoma, high SP-D level, or low %DLCO undergoing ipilimumab plus nivolumab therapy.

Immune checkpoint inhibitor-related pneumonitis: research advances in prediction and management

The advent of immune-checkpoint inhibitors (ICIs) has revolutionized the treatment of malignant solid tumors in the last decade, producing lasting benefits in a subset of patients. However, unattended excessive immune responses may lead to immune-related adverse events (irAEs). IrAEs can manifest in different organs within the body, with pulmonary toxicity commonly referred to as immune checkpoint inhibitor-related pneumonitis (CIP). The CIP incidence remains high and is anticipated to rise further as the therapeutic indications for ICIs expand to encompass a wider range of malignancies. The diagnosis and treatment of CIP is difficult due to the large individual differences in its pathogenesis and severity, and severe CIP often leads to a poor prognosis for patients. This review summarizes the current state of clinical research on the incidence, risk factors, predictive biomarkers, diagnosis, and treatment for CIP, and we address future directions for the prevention and accurate prediction of CIP.

Distinguishing immune checkpoint inhibitor-related pneumonitis from radiation pneumonitis by CT radiomics features in non-small cell lung cancer

PURPOSE

To develop a CT-based model to classify pneumonitis etiology in patients with non-small cell lung cancer(NSCLC) after radiotherapy(RT) and Immune checkpoint inhibitors(ICIs).

METHODS

We retrospectively identified 130 NSCLC patients who developed pneumonitis after receipt of ICIs only (n = 50), thoracic RT only (n = 50) (ICIs only + thoracic RT only, the training cohort, n = 100), and RT + ICIs (the test cohort, n = 30). Clinical and CT radiomics features were described and compared between different groups. We constructed a random forest (RF) classifier and a linear discriminant analysis (LDA) classifier by CT radiomics to discern pneumonitis etiology.

RESULTS

The patients in RT + ICIs group have more high grade (grade 3-4) pneumonitis compared to patients in ICIs only or RT only group (p < 0.05). Pneumonitis after the combined therapy was not a simple superposition mode of RT-related pneumonitis(RP) and ICI-related pneumonitis(CIP), resulting in the distinct characteristics of both RT and ICIs-related pneumonitis. The RF classifier showed favorable discrimination between RP and CIP with an area under the receiver operating curve (AUC) of 0.859 (95 %CI: 0.788-0.929) in the training cohort and 0.851 (95 % CI: 0.700-1) in the test cohort. The LDA classifier achieved an AUC of 0.881 (95 %CI: 0.815-0.947) in the training cohort and 0.842 (95 %CI: 0.686-0.997) in the test cohort. Our analysis revealed four principal CT-based features shared across both models:original_glrlm_LongRunLowGrayLevelEmphasis, wavelet-HLL_firstorder_Median, wavelet-LLL_ngtdm_Busyness， and wavelet-LLL_glcm_JointAverage.

CONCLUSION

CT radiomics-based classifiers could provide a noninvasive method to identify the predominant etiology in NSCLC patients who developed pneumonitis after RT alone, ICIs alone or RT + ICIs.

Nintedanib in an elderly non-small-cell lung cancer patient with severe steroid-refractory checkpoint inhibitor-related pneumonitis: A case report and literature review

Immune checkpoint inhibitors tremendously improve cancer prognosis; however, severe-grade immune-related adverse events may cause premature death. Current recommendations for checkpoint inhibitor-related pneumonitis (CIP) treatment are mainly about immunosuppressive therapy, and anti-fibrotic agents are also needed, especially for patients with poor response to corticosteroids and a longer pneumonitis course. This is because fibrotic changes play an important role in the pathological evolution of CIP. Here, we report a case demonstrating that nintedanib is a promising candidate drug for CIP management or prevention, as it has potent anti-fibrotic efficacy and a safety profile. Moreover, nintedanib could partially inhibit tumor growth in patients with non-small-cell lung cancer, and its efficacy can be improved in combination with other anti-tumor therapies.