Pneumonitis In Patients Research Articles

Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease

Objectives: We aimed to develop imaging biomarkers to predict radiation pneumonitis (RP) in non-small cell lung cancer (NSCLC) patients undergoing thoracic radiotherapy. We hypothesized that measuring morphometric complexity in the lung using simulation computed tomography may provide objective imaging biomarkers for lung parenchyma integrity, potentially forecasting the risk of RP. Materials and Methods: A retrospective study was performed on medical records of 175 patients diagnosed with NSCLC who had received thoracic radiotherapy. Three indices were utilized to measure the morphometric complexity of the lung parenchyma: box-counting fractal dimension, lacunarity, and minimum spanning tree (MST) fractal dimension. Patients were dichotomized into two groups at median values. Cox proportional hazard models were constructed to estimate the hazard ratios for grade ≥ 2 or grade ≥ 3 RP. Results and Conclusions: We found significant associations between lung parenchymal morphometric complexity and RP incidence. In univariate Cox-proportional hazard analysis, patients with a lower MST fractal dimension had a significantly higher hazard ratio of 2.296 (95% CI: 1.348–3.910) for grade ≥ 2 RP. When adjusted for age, sex, smoking status, category of the underlying lung disease, category of radiotherapy technique, clinical stage, histology, and DLCO, patients with a lower MST fractal dimension showed a significantly higher hazard ratio of 3.292 (95% CI: 1.722–6.294) for grade ≥ 2 RP and 7.952 (95% CI: 1.722 36.733) for grade ≥ 3 RP than those with a higher MST fractal dimension. Patients with lower lacunarity exhibited a significantly lower hazard ratio of 0.091 (95% CI: 0.015–0.573) for grade ≥ 3 RP in the adjusted model. We speculated that the lung tissue integrity is captured by morphometric complexity measures, particularly by the MST fractal dimension. We suggest the MST fractal dimension as an imaging biomarker for predicting the occurrence of symptomatic RP after thoracic radiotherapy.

Real-world analysis of the incidence and risk factors of pneumonitis in non-small cell lung cancer patients treated with combined thoracic radiotherapy and immunotherapy

Abstract Objectives Combining radiotherapy with immune checkpoint inhibitor (ICI) treatment has emerged as an important therapeutic regimen. However, this combined treatment may increase the risk of pneumonitis. The aim of this study is to analyze the incidence and risk factors for pneumonitis in non-small cell lung cancer (NSCLC) patients receiving combined thoracic radiotherapy and ICI (RT + ICI) treatment in the real-world clinical setting, offering a reference and guidance for clinical physicians. Methods This study identified 447 patients with pathologically confirmed NSCLC at West China Hospital of Sichuan University from 2016 to 2021. Clinical characteristics, treatment regimens, immune-related adverse events (irAEs), and hematological data were collected and analyzed. Results Patients receiving combined RT + ICI treatment had a higher risk of developing pneumonitis than those receiving ICI treatment alone (26.9 vs. 6.7 %, p<0.001). The multivariate logistic analysis identified the following independent risk factors for pneumonitis in patients undergoing combined RT + ICI treatment: history of lung disease (p=0.032), first-line ICI treatment (p=0.001), anti-PD-L1 instead of anti-PD-1 treatment (p=0.035), and the development of immunotherapy-related thyroid dysfunction (p=0.019). The independent risk factors were incorporated into a nomogram to predict the incidence of pneumonitis. The area under the receiver operating characteristic curve is 0.727, suggesting an acceptable predictive efficacy. Conclusions Compared to ICI monotherapy, NSCLC patients receiving the combination of thoracic radiotherapy and ICI treatment are at higher risk of developing pneumonitis. The nomogram holds promise for facilitating the risk assessment and early identification of pneumonitis in NSCLC patients receiving combined RT + ICI treatment.

Germline Human Leukocyte Antigen Status is Associated With Immunotherapy-Induced Pneumonitis and Treatment Response in Patients With Non–Small Cell Lung Carcinoma With High Programmed Death-Ligand 1 Expression

IntroductionThe germline human leukocyte antigen (HLA) status has been found to be associated with immunotherapy outcomes in patients with NSCLC, but its correlation to immunotherapy-induced pneumonitis and prognostic impact in the Asian population remains largely unknown. MethodsWe evaluated the HLA genotype of the germline and available tumor samples in 42 patients with programmed death-ligand 1 expression of 50% or higher undergoing pembrolizumab immunotherapy. The HLA allele expression was correlated with tumor response, disease survival, and the occurrence of pneumonitis. ResultsIt was observed that the germline HLA-C homozygosity and HLA-DRB1∗13 expression were related to a worse progression-free survival and treatment response. Importantly, all patients (7/7 patients) who developed pneumonitis in our cohort expressed the HLA-DPB1∗02 allele, and the incidence of pneumonitis was 31.8% (7/22 patients) in patients expressing this allele compared with 0% (0/20 patients) in those without this allele (p = 0.009). Investigation of the tumor samples from 15 patients revealed some degree of HLA loss in the HLA class I loci in 40% (6/15) of patients, and no significant difference in tumor mutation burden was found among patients with different treatment responses. ConclusionTaken together, this study evaluated the impact of HLA status in both germline and tumor samples in patients with NSCLC with high programmed death-ligand 1 expression, and the high incidence of immunotherapy-induced pneumonitis in patients expressing the HLA-DPB1∗02 allele may suggest a routine HLA typing and closer monitoring in this patient subset.

Predictive Value of Simulated CT Radiomics Combined with Ipsilateral Lung Dosimetry Parameters for Radiation Pneumonitis in Patients with Esophageal Cancer: A Machine Learning-Based Retrospective Study.

To explore how non-surgical esophageal cancer patients can identify high-risk factors for radiation-induced pneumonitis after receiving radiotherapy. We retrospectively included 228 esophageal cancer patients who were unable to undergo surgical treatment but received radiotherapy for the first time. By retrospective analysis and identifying potential risk factors for symptomatic radiation-induced pneumonitis (ie ≥grade 2), as well as delineating the affected lung as an area of interest on localized CT and extracting radiomics features, along with extracting dosimetric parameters from the affected lung area. After feature screening, patients were randomly divided into training and testing sets in a 7-to-3 ratio, and a prediction model was established using machine learning algorithms. Finally, the receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to validate the predictive performance of the model. A total of 54 cases of symptomatic radiation pneumonitis occurred in this study, with a total incidence rate of 23.68%. The results of multivariate analysis showed that the occurrence of symptomatic radiation pneumonitis was significantly correlated with the mean lung dose (MLD), esophageal PTVD90, esophageal PTVV50, V5, V10, V15, and V20 in patients. The machine learning prediction model constructed based on candidate prediction variables has a prediction performance interval between 0.751 (95% CI: 0.700-0.802) and 0.891 (95% CI: 0.840-0.942) in the training and validation sets, respectively. Among them, the RFM algorithm has the best prediction performance for radiation-induced pneumonitis, with 0.891 (95% CI: 0.840-0.942) and 0.887 (95% CI: 0.836-0.938) in the training and validation sets, respectively. The combination of localization CT radiomics features and diseased lung dosimetry parameters has good predictive value for radiation-induced pneumonitis in esophageal cancer patients after radiotherapy. Especially, the radiation-induced pneumonitis prediction model constructed using RF algorithm can be more effectively used to guide clinical decision-making in esophageal cancer patients.

High-Resolution CT Patterns of Anti-PD1 Checkpoint Inhibitor-Related Pneumonitis in Patients With Lung Cancer.

Lung cancer has the highest morbidity and mortality in the world, and immunotherapies have been developed for this disease in recent years. However, activation of the immune system can cause immune-related adverse events (irAEs), and checkpoint inhibitor-related pneumonitis (CIP), can be the most severe and fatal. But few reports have systematically examined the spectrum of imaging findings of this condition. Therefore, the objective of this paper is to investigate the high-resolution computed tomography (HRCT) characteristics of CIP in patients with lung cancer. To investigate the HRCT characteristics of CIP in patients with lung cancer. HRCT patterns in 41 lung cancer patients who developed CIP after treatment with immune checkpoint inhibitors were retrospectively characterized by interstitial lung disease classification, and their severity was graded. Specific HRCT characteristics related to CIP were identified. There are 4 types of immunotherapy-induce pneumonitis patterns (organizing pneumonia OP 19 cases, nonspecific interstitial pneumonia NSIP 8 cases, acute interstitial pneumonia AIP 7 cases, 7 cases of undetermined type) and image grade (13 cases of grade 1, 17 cases of grade 2, 11 cases of grade 3, 0 cases of grade 4) were identified. Spatial distribution characteristics of these lesions were noted (17 cases predominantly distributed in tumor-containing lobes, 6 cases predominantly distributed in non-tumor-containing lobes, and no specific predilection in 18 cases). Specific CT imaging features found in CIP included, in the order of prevalence, the following: ground glass opacities (38 cases), subpleural/vertical line (37 cases), interstitial thickening around the bronchovascular bundles (36 cases), reticulation (34 cases), fine reticular shadow (31 cases), consolidation (31 cases), small cystic shadow (24 cases, may not having honeycombing), small nodules (17 cases), bronchiectasis (15 cases), honeycombing (11 cases), mosaic sign (11 cases), and pleural effusion (18 cases). HRCT of CIP predominantly manifests as ground glass opacities, reticulation, subpleural/vertical line, interstitial thickening around the bronchovascular bundle, and consolidation.

CT-based different regions of interest radiomics analysis for acute radiation pneumonitis in patients with locally advanced NSCLC after chemoradiotherapy

PurposeTo establish a radiomics model using radiomics features from different region of interests (ROI) based on dosimetry-related regions in enhanced computed tomography (CT) simulated images to predict radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC). MethodsOur retrospective study was conducted based on a cohort of 236 NSCLC patients (59 of them with RP≥2) who were treated in 2 institutions and divided into the primary cohort (n = 182,46 of them with RP≥2) and external validation cohort (n = 54,13 of them with RP≥2). Radiomic features extracted from three ROIs were defined as the whole lung (WL), the dose volume histogram (DVH) of the lung V20 (V20_Lung) and the DVH of the V30 of lung minus the planning target volume (PTV) (V30 Lung-PTV). A total of 107 radiomics features were extracted from each ROIs. The U test, correlation coefficient and least absolute shrinkage and selection operator (LASSO) were performed for features selection. Six models based on different classification algorithms were developed to select the best radiomics model (R model).In addition, we built a dosimetry model then combined it with the best R model to create a mixed model (R+D model) The receiver operating characteristic (ROC) curve was delineated to assess the predictive efficacy of the models. Decision curve analysis could benefit from the model proposals through the assessment of clinical utility. ResultsAmong the three ROIs, the best R model constructed from the LightGBM algorithm demonstrated the strongest discriminative ability in the ROI of V30 Lung-PTV. The corresponding area under the curve (AUC) value was 0.930 (95 % confidence interval (CI): 0.829–0.941). The D model, R model and R+D model achieved AUC values of 0.798 (95 %CI: 0.732–0.865), 0.930 (95 %CI: 0.829–0.941) and 0.940 (95 %CI: 0.906–0.974) in primary cohort, and in external validation cohort, the AUC values were 0.793 (95 %CI:0.637–0.949), 0.887 (95 %CI:0.810–0.993), 0.951 (95CI%:0.891–1.000). Decision curve demonstrate that R+D model could benefit for patients through the assessment of clinical utility. ConclusionThe radiomics model was able to predict the acute RP more effectively in comparison with the traditional dosimetry model. Especially the radiomics model based on the V30 Lung-PTV region was able to achieve a higher accuracy when compared to the other regions.

ViTR-SP: A CT-based vision transformer model for prediction of pneumonitis in patients with non-small cell lung cancer who received thoracic radiotherapy and immunotherapy.

e20034 Background: The combination of thoracic radiotherapy (TRT) and immunotherapy accompanied by the accumulation of pulmonary toxicity. This study aimed to construct a deep radiomics model based on sequential computed tomography (CT) images for radioimmune-associated pneumonitis prediction in non-small cell lung cancer (NSCLC) patients treated with TRT and immune checkpoint inhibitors (ICIs). Methods: Three models were constructed based on a vision transformer (ViT) network using sequential chest CT images, tumor-mask and lung-mask as inputs, respectively. NSCLC patients treated with TRT and ICIs at Shandong Cancer Hospital and Qilu Hospital were included for model training and external validation, respectively. The image-level model was trained based on ViT to identify predictive images, and the image-level probability distribution were performed. Then, a ViT-Recursive Neural Network (ViT-RNN) model framework was constructed at the patient-level to integrate the image-level information to derive the final prediction, which was evaluated in an independent validation cohort. Results: A total of 230 NSCLC patients from Shandong Cancer Hospital were randomly assigned in a 7:3 ratio for model training and validation, respectively. Another 42 patients from Qilu Hospital were used as an independent external validation cohort. The ViT-RNN model for symptomatic pneumonitis (ViTR-SP) based on sequential CT images achieved better area under curve (AUC), sensitivity, and specificity of 0.725, 0.750, and 0.886 than lung-mask based model (0.575, 0.625, and 0.705) and tumor-mask based model (0.658, 0.667, and 0.773) in the internal validation set. In the external validation set, the proposed model achieved the AUC, sensitivity, and specificity of 0.654, 0.818, 0.727, while the lung-mask and tumor-mask based models had the AUC, sensitivity, and specificity of 0.540, 0.545, 0.677, and 0.630, 0.545, 0.742, respectively. The performance of the model was improved after integrating clinical features, with internal and external validation AUC of 0.782 and 0.672, respectively. Conclusions: In conclusion, the clinical combined ViTR-SP neural network risk prediction model based on sequential chest CT images can be used for predicting the risk of developing radioimmune-associated pneumonitis in NSCLC patients.

Association of human leukocyte antigen (HLA) status with immune checkpoint inhibitor (ICI) pneumonitis in patients with non-small cell lung cancer (NSCLC).

8620 Background: Pneumonitis is a potentially serious complication occurring in 5-20% of lung cancer patients receiving ICI. The genetic risk factors for ICI pneumonitis are unclear. Given the association between HLA genetic variants and autoimmune diseases, we hypothesized that certain HLA genetic variants are associated with risk of ICI pneumonitis. Methods: Patients with advanced EGFR/ ALK wild type, PD-L1 tumor proportion score ≥50% NSCLC who received ICI were enrolled from year 2019 to 2022. Germline HLA typing was performed on buccal swab specimens using the Alltype Fastplex assay. Clinicopathological characteristics, treatment courses and survival outcomes were retrospectively collated. The primary endpoint was the correlation of common HLA variants (present in >30% of subjects) to the risk of ICI pneumonitis. Results: 42 patients (all Chinese, 36 male, 33 current/former smokers) were enrolled. Median age was 71 years old (range 51-91). 34, 6, 1 and 1 patients had adenocarcinoma, NSCLC not otherwise specified, squamous cell carcinoma and large cell neuroendocrine carcinoma respectively. Majority (33/42, 79%) received pembrolizumab monotherapy while 9 (21%) patients received pembrolizumab plus chemotherapy. Median follow up time was 27.8 months. At data cutoff, 28 (67%) patients received ICI for more than 1 year and 10 (24%) patients stopped ICI after completion of 2-year course of treatment. Seven (17%) patients developed pneumonitis, of which 3 were grade 2 and 4 were grade 3 in severity. Median time to development of pneumonitis was 6.9 months (range 0.3-25.2). Demographic characteristics were similar between patients who did or did not experience pneumonitis. In the entire cohort, twenty-two (52%) patients harbored the class II DPB1*02 allele. This allele was significantly associated with development of ICI pneumonitis. All 7 patients who had ICI pneumonitis harbored the DPB1*02 allele. The incidence of pneumonitis in patients harboring the DPB1*02 allele was 32% compared to 0% in those without this allele (p=0.009). Patients who experienced pneumonitis had worse survival rates than those without (p=0.03), but expression of DPB1*02 allele was not associated with inferior survival outcomes. Conclusions: Our results suggested that expression of DPB1*02 allele may be associated with development of ICI pneumonitis. A larger case-control study is ongoing to validate this association. [Table: see text]

In-hospital outcomes and mortality of drug-induced pneumonitis and radiation pneumonitis in patients with thoracic cancer.

12042 Background: Pneumonitis is one of the challenging adverse events in thoracic oncology patients undergoing cancer therapy. The cancer treatments, including targeted agents, systemic chemotherapy, immune-checkpoint inhibitors, and radiation therapy have recently advanced, however, the data on incidence of drug-induced and radiation pneumonitis (DP and RP) and their association with in-hospital outcomes is limited. Methods: Data from the National Inpatient Sample Database from 2016 to 2019 were analyzed. Adult patients with primary lung cancer were included and categorized into three groups: (1). Patients without pneumonitis, (2). Patients with DP, (3). Patients with RP. Outcomes included in-hospital mortality, intensive care unit (ICU) admission, and hospital length of stay (LOS). Data were extracted using ICD-10 codes. Results: Our analysis included 1,631,940 hospitalized primary lung cancer patients (based on a weighted sample). Among all, 4,515 patients had DP, and 16,905 patients had RP. Overall, 69.3% had smoking history, however, no significant difference between DP and RP. There was a higher prevalence of chronic obstructive pulmonary disease (COPD) in RP than DP (66.5% vs 53.2%; p<0.05) (Table). The in-hospital mortality rate was highest in DP compared to other groups. Coarsened exact matching method was used to balance covariates between non-pneumonitis and pneumonitis patients (DP and RP). Multivariate logistic regression showed that pneumonitis patients had higher odds of intubation (OR: 1.57; 95% CI: 1.24-1.99; p<0.05) and mortality (OR: 1.48; 95% CI: 1.28-1.71; p<0.05) than non-pneumonitis. Pneumonitis patients also had 23% longer length of stay than non-pneumonitis patients. We then compared the outcomes between DP and RP using the same matching algorithm, however, there was no significant difference in the outcomes between the two groups. Over the study years, the trend for DP significantly increased, whereas the RP trend was stable. Conclusions: Hospitalized pneumonitis patients had relatively poor clinical outcomes compared to patients without pneumonitis. The trend of hospitalized drug-induced pneumonitis is increasingly common. [Table: see text]

The incidence of and risk factors for radiation pneumonitis in patients treated with simultaneous bevacizumab and thoracic radiotherapy

BackgroundFirst-line chemotherapy combined with bevacizumab is one of the standard treatment modes for patients with advanced non-small cell lung cancer (NSCLC). Thoracic radiotherapy (TRT) can provide significant local control and survival benefits to patients during the treatment of advanced NSCLC. However, the safety of adding TRT has always been controversial, especially because of the occurrence of radiation pneumonia (RP) during bevacizumab treatment. Therefore, in this study, we used an expanded sample size to evaluate the incidence of RP when using bevacizumab in combination with TRT.Patients and methodsUsing an institutional query system, all medical records of patients with NSCLC who received TRT during first-line chemotherapy combined with bevacizumab from 2017 to 2020 at Shandong Cancer Hospital and Institute were reviewed. RP was diagnosed via computed tomography and was classified according to the RTOG toxicity scoring system. The risk factors for RP were identified using univariate and multivariate analyses. The Kaplan–Meier method was used to calculate progression-free survival (PFS) and overall survival (OS).ResultsUltimately, 119 patients were included. Thirty-eight (31.9%) patients developed Grade ≥ 2 RP, of whom 27 (68.1%) had Grade 2 RP and 11 (9.2%) had Grade 3 RP. No patients developed Grade 4 or 5 RP. The median time for RP occurrence was 2.7 months (range 1.2–5.4 months). In univariate analysis, male, age, KPS score, V20 > 16.9%, V5 > 33.6%, PTV (planning target volume)-dose > 57.2 Gy, and PTV-volume > 183.85 cm3 were correlated with the occurrence of RP. In multivariate analysis, male, V20 > 16.9%, and PTV-volume > 183.85 cm3 were identified as independent predictors of RP occurrence. The mPFS of all patients was 14.27 (95% CI, 13.1–16.1) months. The one-year and two-year PFS rates were 64.9% and 20.1%, respectively. The mOS of all patients was 37.09 (95% CI, 33.8–42.0) months. The one-year survival rate of all patients was 95%, and the two-year survival rate was 71.4%.ConclusionsThe incidence of Grade ≥ 2 RP in NSCLC patients who received both bevacizumab and TRT was 31.9%. Restricting factors such as V20 and PTV will help reduce the risk of RP in these patients. For patients who receive both bevacizumab and TRT, caution should be exercised when increasing TRT, and treatment strategies should be optimized to reduce the incidence of RP.

Clinical predictors of severe radiation pneumonitis in patients undergoing thoracic radiotherapy for lung cancer

Clinical predictors of severe radiation pneumonitis in patients undergoing thoracic radiotherapy for lung cancer

Timing of Radiation Pneumonitis in Patients with Stage 3 Non-Small-Cell Lung Cancer Receiving Consolidation Durvalumab after Chemoradiation

Purpose. Consolidation with durvalumab is standard of care in the management of unresectable stage 3 non-small-cell lung cancer (NSCLC) postchemoradiation, and pneumonitis is an independent potential treatment complication of both treatment strategies. This study seeks to determine the timing of radiation pneumonitis (RP) by receipt of durvalumab. In addition, we reviewed the preventative strategies guided by pathophysiology of pneumonitis. Methods. We identified patients with unresectable Stage 3 NSCLC who developed grade ≥2 RP after chemoradiotherapy. Time-to-RP was defined from date of completion of radiotherapy to date of radiological diagnosis of RP and accompanying clinical symptoms. Early RP was defined as RP within 2 months of completion of radiotherapy. Differences in time-to-RP by receipt of durvalumab were evaluated using Wilcoxon rank-sum test. Differences in those who had early vs late RP by receipt of durvalumab was evaluated using Fisher’s exact test. Logistic regression was used to evaluate patient and treatment factors associated with early RP. Results. Of the 144 patients with Stage 3 NSCLC who had definitive chemoradiotherapy, 31 (22%) developed grade ≥2 RP and were included in the study. There was one patient with grade 5 RP. The median age of the cohort was 67 years (range 41–87). The mean lung dose, V5Gy, and V20Gy were 15.8Gy (SD = 1.56), 60.14% (SD 2.73), and 29.96% (SD 1.82), respectively. Twelve (39%) patients received durvalumab. The median time-to-RP was 3.4 months (range: 1.7–7.2) and 2.3 months (range: 0.6–9.6) in patients who had durvalumab and no durvalumab, respectively (P=0.01). 83% (10/12) of patients who had durvalumab and 58% (11/19) of patients who did not have durvalumab had late RP (P=0.14). No other patient and treatment factors were associated with early RP. Conclusion. Patients on durvalumab may have late-onset RP; therefore, further studies with larger cohort of patients and development of new predictive models that incorporate evolving management are needed should preventative strategies of RP be considered in routine clinical practice.

Clinical Manifestation, Risk Factors, and Immune Checkpoint Inhibitor Rechallenge of Checkpoint Inhibitor-Associated Pneumonitis in Patients With Lung Cancer.

Immune-related adverse effects can lead to damage to various systems of the body, checkpoint inhibitor-associated pneumonitis (CIP) is one of the potentially lethal immune-related adverse effects. However, evidence regarding the risk factors associated with CIP is limited. To timely and accurate identification and prompt treatment of CIP, understanding the risk factors for multimorbidity among diverse study populations becomes crucial. We retrospectively analyzed the clinical data of 1131 patients with lung cancer receiving immunotherapy to identify 110 patients with CIP, the clinical characteristics and radiographic features of patients with CIP were analyzed. A case-control study was subsequently performed to identify the risk factors of CIP. The median treatment cycle was 5 cycles and the median time to onset of CIP was 4.2 months. CIP was mainly grade I or II. Most cases improved after discontinuation of immune checkpoint inhibitors (ICIs) or hormone therapy. Severe CIP tended to occur earlier in comparison to mild to moderate cases. The recurrence rate was 20.6% in ICI-rechallenged patients, and patients with relapsed CIP were usually accompanied by higher-grade adverse events than at first onset. Among the 7 patients with relapse, ICI-associated deaths occurred in 2 patients (28.6%). For rechallenging with ICIs after recovery from CIP, caution should be practiced. Male [odds ratio (OR): 2.067; 95% CI: 1.194-3.579; P = 0.009], history of chest radiation (OR: 1.642; 95% CI: 1.002-2.689; P = 0.049) and underlying lung disease (OR: 2.347; 95% CI: 1.008-5.464; P =0.048) was associated with a higher risk of CIP.

Safety and Efficacy of HL301 In Radiation Pneumonitis in Patients With Unresectable Non-Small Cell Lung Cancer Receiving Curative Concurrent Chemoradiotherapy: A Multicenter, Randomized, Double-Blinded, Placebo-Controlled, Phase 2a Clinical Trial

Objective: We aimed to investigate the safety and efficacy of HL301, a standardized combination product of seven medicinal plants, in radiation pneumonitis in patients with unresectable non-small cell lung cancer (NSCLC) undergoing curative concurrent chemoradiotherapy.Methods: The target accrual was 87 and a total of 63 patients were enrolled due to poor accrual rate. We randomly assigned the 63 patients to receive a placebo (arm A), or 1200 mg HL301 (arm B), or 1800 mg HL301 (arm C). Patients received weekly paclitaxel and carboplatin concurrently with intensity-modulated radiotherapy at 60–66 Gy in conventional fractionation. Durvalumab was administered as maintenance treatment according to standard clinical practice. HL301 was administered orally, daily for 12 weeks. The primary endpoint was incidence of grade ≥2 radiation pneumonitis at 24 weeks post-chemoradiotherapy.Results: The baseline characteristics of the patients were well balanced. The drug was tolerable with a compliance rate of 86.6%, 86.2%, and 88.8% in arms A, B, and C, respectively (P = 0.874). None of the patients experienced severe drug-related adverse events. No significant difference in the rate of adverse events were observed between the treatment arms. The incidence of grade ≥2 radiation pneumonitis at 24 weeks post-chemoradiotherapy was 37.5% (95% CI, 18.5–61.4%), 55.6% (95% CI, 33.7–75.4%), and 52.4% (95% CI, 32.4–71.7%) in arms A, B, and C, respectively (P=0.535).Conclusion: This is the first exploratory clinical trial to test the safety and efficacy of HL301 in patients with NSCLC. Safety and feasibility of HL301 were established but no signals of efficacy in reducing RP was observed in this dose level.

DNA Repair Genetics and the Risk of Radiation Pneumonitis in Patients With Lung Cancer: A Systematic Review and Meta-analysis

AimsERCC1 rs11615 and ERCC2 rs238406 single nuclear polymorphism (SNPs) are known for their association with treatment outcome, likely related to radiosensitivity of both tumor and normal tissue in patients with non-small-cell lung cancer. This study aimed to review the effect of 1) these ERCC1/2 SNPs and 2) other SNPs of DNA repair genes on radiation pneumonitis (RP) in patients with lung cancer. Materials and methodsSNPs of our interest included ERCC1 rs11615 and ERCC2 rs238406 and other genes of DNA repair pathways that are functional and biologically active. DNA repair SNPs reported by at least two independent studies were pooled for meta-analysis. The study endpoint was radiation pneumonitis (RP) after radiotherapy. Recessive, dominant, homozygous, heterozygous, and allelic genotype models were used where appropriate. ResultsA total of 16 studies (3080 patients) were identified from the systematic review and 12 studies (2090 patients) on 11 SNPs were included in the meta-analysis. The SNPs were ATM rs189037, ATM rs373759, NEIL1 rs4462560, NEIL1 rs7402844, APE1 rs1130409, XRCC3 rs861539, ERCC1 rs11615, ERCC1 rs3212986, ERCC2 rs238406, ERCC2 rs13181, and XRCC1 rs25487. ERCC1 rs11615 (236 patients) and ERCC2 rs238406 (254 patients) were not significantly associated with RP. Using the allelic model, the G allele for NEIL1 gene was significantly associated with a reduced odds of developing symptomatic (grade ≥2) RP compared to the C allele for rs7402844 (OR 0.70, 95% CI: 0.49, 0.99, P = 0.04). Similarly, the T allele for APE1 gene was significantly associated with a reduced odds of developing symptomatic (grade ≥2) RP compared to the G allele for rs1130409 (OR 0.59, 95% CI: 0.43, 0.81, P = 0.001). ConclusionGenetic variation in the DNA repair pathway genes may play a significant role in the risk of developing radiation pneumonitis in patients with lung cancer. Further studies are needed on genotypic features of DNA repair pathway genes and their association with treatment sensitivity, as such knowledge may guide personalized radiation dose prescription.

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.

A dynamic nomogram predicting symptomatic pneumonia in patients with lung cancer receiving thoracic radiation

PurposeThe most common and potentially fatal side effect of thoracic radiation therapy is radiation pneumonitis (RP). Due to the lack of effective treatments, predicting radiation pneumonitis is crucial. This study aimed to develop a dynamic nomogram to accurately predict symptomatic pneumonitis (RP ≥ 2) following thoracic radiotherapy for lung cancer patients.MethodsData from patients with pathologically diagnosed lung cancer at the Zhongshan People’s Hospital Department of Radiotherapy for Thoracic Cancer between January 2017 and June 2022 were retrospectively analyzed. Risk factors for radiation pneumonitis were identified through multivariate logistic regression analysis and utilized to construct a dynamic nomogram. The predictive performance of the nomogram was validated using a bootstrapped concordance index and calibration plots.ResultsAge, smoking index, chemotherapy, and whole lung V5/MLD were identified as significant factors contributing to the accurate prediction of symptomatic pneumonitis. A dynamic nomogram for symptomatic pneumonitis was developed using these risk factors. The area under the curve was 0.89(95% confidence interval 0.83–0.95). The nomogram demonstrated a concordance index of 0.89(95% confidence interval 0.82–0.95) and was well calibrated. Furthermore, the threshold values for high- risk and low- risk were determined to be 154 using the receiver operating curve.ConclusionsThe developed dynamic nomogram offers an accurate and convenient tool for clinical application in predicting the risk of symptomatic pneumonitis in patients with lung cancer undergoing thoracic radiation.

Novel model integrating computed tomography-based image markers with genetic markers for discriminating radiation pneumonitis in patients with unresectable stage III non-small cell lung cancer receiving radiotherapy: a retrospective multi-center radiogenomics study

BackgroundChemoradiotherapy is a critical treatment for patients with locally advanced and unresectable non-small cell lung cancer (NSCLC), and it is essential to identify high-risk patients as early as possible owing to the high incidence of radiation pneumonitis (RP). Increasing attention is being paid to the effects of endogenous factors for RP. This study aimed to investigate the value of computed tomography (CT)-based radiomics combined with genomics in analyzing the risk of grade ≥ 2 RP in unresectable stage III NSCLC.MethodsIn this retrospective multi-center observational study, 100 patients with unresectable stage III NSCLC who were treated with chemoradiotherapy were analyzed. Radiomics features of the entire lung were extracted from pre-radiotherapy CT images. The least absolute shrinkage and selection operator algorithm was used for optimal feature selection to calculate the Rad-score for predicting grade ≥ 2 RP. Genomic DNA was extracted from formalin-fixed paraffin-embedded pretreatment biopsy tissues. Univariate and multivariate logistic regression analyses were performed to identify predictors of RP for model development. The area under the receiver operating characteristic curve was used to evaluate the predictive capacity of the model. Statistical comparisons of the area under the curve values between different models were performed using the DeLong test. Calibration and decision curves were used to demonstrate discriminatory and clinical benefit ratios, respectively.ResultsThe Rad-score was constructed from nine radiomic features to predict grade ≥ 2 RP. Multivariate analysis demonstrated that histology, Rad-score, and XRCC1 (rs25487) allele mutation were independent high-risk factors correlated with RP. The area under the curve of the integrated model combining clinical factors, radiomics, and genomics was significantly higher than that of any single model (0.827 versus 0.594, 0.738, or 0.641). Calibration and decision curve analyses confirmed the satisfactory clinical feasibility and utility of the nomogram.ConclusionHistology, Rad-score, and XRCC1 (rs25487) allele mutation could predict grade ≥ 2 RP in patients with locally advanced unresectable NSCLC after chemoradiotherapy, and the integrated model combining clinical factors, radiomics, and genomics demonstrated the best predictive efficacy.

Development and validation of a nomogram for predicting immune-related pneumonitis after sintilimab treatment.

Immune-related pneumonitis is a rare and potentially fatal adverse event associated with sintilimab. We aimed to develop and validate a nomogram for predicting the risk of immune-related pneumonitis in patients treated with sintilimab. The least absolute shrinkage and selection operator (LASSO) regression was used to determine risk factors. Multivariable logistic regression was used to establish a prediction model. Its clinical validity was evaluated using calibration, discrimination, decision, and clinical impact curves. Internal validation was performed against the validation set and complete dataset. The study included 632 patients; 59 were diagnosed with immune-related pneumonitis. LASSO regression analysis identified that the risk factors for immune-related pneumonitis were pulmonary metastases (odds ratio [OR], 4.015; 95% confidence interval [CI]: 1.725-9.340) and metastases at >3 sites (OR, 2.687; 95% CI: 1.151-6.269). The use of combined antibiotics (OR, 0.247; 95% CI: 0.083-0.738) and proton pump inhibitors (OR, 0.420; 95% CI: 0.211-0.837) were protective factors. The decision and clinical impact curves showed that the nomogram had clinical value for patients treated with sintilimab. We have developed and validated a practical nomogram model of sintilimab-associated immune-related pneumonitis, which provides clinical value for determining the risk of immune-related pneumonitis and facilitating the safe administration of sintilimab therapy.

The Impact of PM2.5 on Radiation-induced Pneumonitis in Patients With Breast Cancer.

Exposure to particulate matter (PM) air pollution is known to adversely affect respiratory disease, but no study has examined its effect on radiation-induced pneumonitis (RIP) in patients with breast cancer. We conducted a retrospective review of 2,736 patients with breast cancer who received postoperative radiation therapy (RT) between 2017 and 2020 in a single institution. The distance between the PM measurement station and our institution was only 3.43 km. PM data, including PM2.5 and PM10, were retrieved from the open dataset in the official government database. Overall incidence rate of RIP was 1.74%. After adjusting for age, RT technique, regional irradiation, fractionation and boost, the average value of PM2.5 was significantly associated with a higher risk of RIP (p=0.047) when patients received ≥20 fractions of RT. Specifically, PM2.5 ≥35 (μg/m3) showed a significantly higher risk of RIP (p=0.019) in patients with ≥20 fractions of RT. This is the first study to reveal the association between PM2.5 and RIP in patients with breast cancer who received 20 fractions or more of postoperative RT. We demonstrated that high PM2.5 levels around the RT institution were associated with RIP, suggesting that reducing PM air pollution may be a modifiable risk factor.