Risk Of Pneumonitis Research Articles

Evaluation of Pneumonitis in a Phase II Study of Consolidation Immunotherapy with Nivolumab and Ipilimumab or Nivolumab Alone following Concurrent Chemoradiotherapy for Unresectable Stage IIIA/IIIB Non-small Cell Lung Cancer (NSCLC)

Unresectable stage III Non-Small-Cell-Lung-Cancer (NSCLC) has had an evolving landscape of treatment options with the approvals of immuno-oncologic (IO) therapy. There have been relatively few studies that have evaluated the risk of pneumonitis in patients receiving IO after concurrent chemoradiation treatment (CCRT). This study is to evaluate the relationship of pneumonitis and radiation dose in patients receiving consolidative IO with Nivolumab or Nivolumab plus ipilimumab. Patients with stage III NSCLC who underwent CCRT were enrolled on BTCRC-LUN16-081, a randomized phase II trial assessing the efficacy of nivolumab or nivolumab plus ipilimumab as consolidation therapy. These patients were evaluated for radiation dose parameters and correlation with pneumonitis was examined. After CCRT, patients were enrolled to receive consolidative IO therapy on BTCRC-LUN16-081, and 104 patients had Dose Volume Histogram (DVH) information available for analysis. Of these patients, 58 (55.8%) had stage IIIA and 46 (44.2%) had stage IIIB disease according to 7th edition IASLC. During this period 29 patients (27.9%) had at least grade 2 pneumonitis. Utilizing logistic regression and evaluating different cut offs for lung V20, patients receiving a V20 of greater than 23% had a higher risk of grade 2 or greater pneumonitis (p-value 0.0246, 38% vs. 16%). There was no significant difference in rates of pneumonitis between the two different IO regimens. Traditional lung DVH cutoffs (V5>65%, V20>35%, mean >20 Gy) were not associated with pneumonitis in this study. The use of nivolumab or nivolumab plus ipilimumab after definitive CCRT is safe and effective. Lung V20 > 23% was associated with a higher risk of Grade 2 or higher pneumonitis. Radiation dose constraints for lungs in patients receiving consolidative IO after CCRT should continue to be evaluated and optimized when feasible.

Common methodological pitfalls in ICI pneumonitis risk prediction studies.

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. 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. 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. 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.

Comparison of the risk of hospital admission, need for ventilation, sepsis, pneumonitis and death among the recent monkeypox outbreak and historical outbreaks

BackgroundThe course of monkeypox can be severe. Our aim was to retrospectively compare the risk of hospital admission, the need for ventilation, sepsis, pneumonitis and death between the recent outbreak and historical outbreaks.Materials and MethodsCases of monkeypox were retrieved from the TriNetX database and assigned to either cohort I (recent outbreak between May 1st and September 16th, 2022) and cohort II (historical outbreaks before May 1st, 2022). After matching for age distribution, statistical analysis was performed.ResultsOf 640 patients with monkeypox 81 subjects per cohort remained after matching (mean age±standard deviation = 36.1±18.3 years). Within 56 days after diagnosis 10 patients per cohort were hospitalized (12.4%) and/or developed sepsis (12.4%). The risk of ventilation and pneumonitis were significantly lower among cohort I compared with cohort II (0 vs. 10 cases; risk difference = 12.4%; p = 0.001; Log-Rank test). No cases of death were recorded.ConclusionEven though monkeypox provides a risk of severe courses, the infection is self-limiting in most cases. Unlike past outbreaks, the risk of ventilation and pneumonitis may be relatively low among recent outbreaks.

Protocol for the T-REX-trial: tailored regional external beam radiotherapy in clinically node-negative breast cancer patients with 1-2 sentinel node macrometastases – an open, multicentre, randomised non-inferiority phase 3 trial

IntroductionModern systemic treatment has reduced incidence of regional recurrences and improved survival in breast cancer (BC). It is thus questionable whether regional radiotherapy (RT) is still beneficial in patients with...

20 Pneumonitis Risk Following Combined Osimertinib and Thoracic Radiotherapy in Egfr-Mutated Non-Small Cell Lung Cancer

20 Pneumonitis Risk Following Combined Osimertinib and Thoracic Radiotherapy in Egfr-Mutated Non-Small Cell Lung Cancer

Impact of Baseline Interstitial Lung Abnormalities on Pneumonitis Risk in Patients Receiving Immune Checkpoint Inhibitors for Non–Small-Cell Lung Cancer

Introduction/BackgroundImmune-related pneumonitis is a potentially fatal complication of treatment with immune checkpoint inhibitors (ICIs). Interstitial lung disease (ILD) is associated with increased risk for pneumonitis, but the impact of interstitial abnormalities (ILA) in the absence of ILD has not been extensively assessed. We examined the relationship between ILA on pretreatment chest computed tomography (CT) scans and risk of pneumonitis in patients with non–small-cell lung cancer (NSCLC). MethodsThis retrospective cohort study included consecutive adult patients who received ICI for NSCLC between January 2013 and January 2020 at our institution. Two thoracic radiologists blinded to clinical outcomes independently reviewed pre-ICI chest CTs to identify and categorize ILA using previously published definitions. We used uni- and multivariable analysis adjusted for age, radiation, and smoking status to assess for associations between ILA, clinicopathologic characteristics, and symptomatic (CTCAE grade ≥2) pneumonitis. ResultsOf 475 patients who received ICI treatment and met inclusion criteria, baseline ILA were present in 78 (16.4%) patients, most commonly as a subpleural nonfibrotic pattern. In total, 43 (9.1%) of 475 patients developed symptomatic pneumonitis. Pneumonitis occurred in 16.7% of patients with ILA compared to 7.6% patients without ILA (P < .05). Presence of ground glass and extent of lung parenchymal involvement were associated with an increased risk of pneumonitis. On multivariable analysis, baseline ILA remained associated with increased risk of symptomatic pneumonitis (OR 2.2, 95% CI, 1.0-4.5). ConclusionsBaseline ILAs are associated with the development of symptomatic pneumonitis in patients with NSCLC treated with ICI. Additional studies are needed to validate these observations.

NTCP Calculations of Five Different Irradiation Techniques for the Treatment of Thymoma.

This study provided normal tissue complication probability (NTCP) calculations from photon radiotherapy techniques in eleven patients with thymoma. Five plans were created for each participant using three-dimensional conformal radiotherapy (3D-CRT), five-field intensity modulated radiotherapy (5F-IMRT), seven-field IMRT (7F-IMRT), and volumetric modulated arc therapy with full arcs (FA-VMAT) and partial arcs (PA-VMAT). The target coverage, homogeneity index and conformation number for the planning target volume (PTV) and dosimetric parameters for the organs-at-risk (OARs) were taken from the fifty-five generated plans. The patient-specific NTCP of the lungs, heart and esophagus was calculated with an in-house software tool using differential dose-volume histograms and the equivalent uniform dose model. The PTV dose metrics from 3D-CRT were inferior to those from IMRT and VMAT plans. The dose constraints for the OARs were met in all treatment plans. The NTCP range of the lungs, heart and esophagus was 0.34-0.49%, 0.03-0.06% and 0.08-0.10%, respectively. The NTCPs of the heart for the incidence of peridarditis from IMRT and VMAT were significantly smaller than those from conformal treatment (p < 0.05). The 7F-IMRT was significantly superior to FA-VMAT in reducing the NTCP of the lungs and the risk of pneumonitis (p = 0.001). Similar superiority of 5F-IMRT over PA-VMAT for lung protection was found (p = 0.009). The presented results may be employed in the selection of the appropriate irradiation technique for restricting the complications in the adjacent OARs.

Pneumonitis in Patients Receiving Thoracic Radiotherapy and Osimertinib: A Multi-Institutional Study

IntroductionThoracic radiotherapy (TRT) is increasingly used in patients receiving osimertinib for advanced NSCLC, and the risk of pneumonitis is not established. We investigated the risk of pneumonitis and potential risk factors in this population. MethodsWe performed a multi-institutional retrospective analysis of patients under active treatment with osimertinib who received TRT between April 2016 and July 2022 at two institutions. Clinical characteristics, including whether osimertinib was held during TRT and pneumonitis incidence and grade (Common Terminology Criteria for Adverse Events version 5.0) were documented. Logistic regression analysis was performed to identify risk factors associated with grade 2 or higher (2+) pneumonitis. ResultsThe median follow-up was 10.2 months (range: 1.9–53.2). Of 102 patients, 14 (13.7%) developed grade 2+ pneumonitis, with a median time to pneumonitis of 3.2 months (range: 1.5–6.3). Pneumonitis risk was not significantly increased in patients who continued osimertinib during TRT compared with patients who held osimertinib during TRT (9.1% versus 15.0%, p = 0.729). Three patients (2.9%) had grade 3 pneumonitis, none had grade 4, and two patients had grade 5 events (2.0%, diagnosed 3.2 mo and 4.4 mo post-TRT). Mean lung dose was associated with the development of grade 2+ pneumonitis in multivariate analysis (OR = 1.19, p = 0.021). ConclusionsAlthough the overall rate of pneumonitis in patients receiving TRT and osimertinib was relatively low, there was a small risk of severe toxicity. The mean lung dose was associated with an increased risk of developing pneumonitis. These findings inform decision-making for patients and providers.

Impact of TMB/PD-L1 expression and pneumonitis on chemoradiation and durvalumab response in stage III NSCLC

Although concurrent chemoradiation (CRT) and durvalumab consolidation has become a standard treatment for stage III non-small cell lung cancer (NSCLC), clinicopathologic and genomic factors associated with its efficacy remain poorly characterized. Here, in a multi-institutional retrospective cohort study of 328 patients treated with CRT and durvalumab, we identify that very high PD-L1 tumor proportion score (TPS) expression ( ≥ 90%) and increased tumor mutational burden (TMB) are independently associated with prolonged disease control. Additionally, we identify the impact of pneumonitis and its timing on disease outcomes among patients who discontinue durvalumab: compared to patients who experienced early-onset pneumonitis ( < 3 months) leading to durvalumab discontinuation, patients with late-onset pneumonitis had a significantly longer PFS (12.7 months vs not reached; HR 0.24 [95% CI, 0.10 to 0.58]; P = 0.001) and overall survival (37.2 months vs not reached; HR 0.26 [95% CI, 0.09 to 0.79]; P = 0.017). These findings suggest that opportunities exist to improve outcomes in patients with lower PD-L1 and TMB levels, and those at highest risk for pneumonitis.

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

AimsPneumonitis 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 methodsWe 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. ResultsThe 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. ConclusionsRisk 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.

A nomogram model for predicting the risk of checkpoint inhibitor-related pneumonitis for patients with advanced non-small-cell lung cancer.

Immunotherapy extensively treats advanced non-small-cell lung cancer (NSCLC). Although immunotherapy is generally better tolerated than chemotherapy, it can cause multiple immune-related adverse events (irAEs) involving multiple organs. Checkpoint inhibitor-related pneumonitis (CIP) is a relatively uncommon irAE that, in severe cases, can be fatal. Potential risk factors for the occurrence of CIP are currently poorly understood. This study sought to develop a novel scoring system for predicting the risk of CIP based on a nomogram model. We retrospectively collected advanced NSCLC patients who received immunotherapy at our institution between January 1, 2018, and December 30, 2021. All patients who met the criteria were randomly divided into the training set and testing set (in a ratio of 7:3), and cases fulfilling the CIP diagnostic criteria were screened. The patients' baseline clinical characteristics, laboratory tests, imaging, and treatment information were extracted from the electronic medical records. The risk factors associated with the occurrence of CIP were identified based on the results of logistic regression analysis on the training set, and a nomogram prediction model was developed. The discrimination and prediction accuracy of the model was evaluated using the receiver operating characteristic (ROC) curve, the concordance index (C-index), and the calibration curve. Decision curve analysis (DCA) was used to evaluate the clinical applicability of the model. The training set comprised 526 (CIP: 42 cases), and the testing set comprised 226 (CIP: 18 cases) patients, respectively. In the training set, the final multivariate regression analysis revealed that age (p = 0.014; odds ratio [OR] = 1.056; 95% Confidence Interval [CI] =1.011-1.102), Eastern Cooperative Oncology Group performance status (p = 0.002; OR = 6.170; 95% CI = 1.943-19.590), history of prior radiotherapy (p < 0.001; OR = 4.005; 95% CI = 1.920-8.355), baseline white blood cell count (WBC) (p < 0.001; OR = 1.604; 95% CI = 1.250-2.059), and baseline absolute lymphocyte count (ALC) (p = 0.034; OR = 0.288; 95% CI = 0.091-0.909) were identified as independent risk factors for the occurrence of CIP. A prediction nomogram model was developed based on these five parameters. The area under the ROC curve and C-index of the prediction model in the training set and testing set were 0.787 (95% CI: 0.716-0.857) and 0.874 (95% CI: 0.792-0.957), respectively. The calibration curves are in good agreement. The DCA curves indicate that the model has good clinical utility. We developed a nomogram model that proved to be a good assistant tool for predicting the risk of CIP in advanced NSCLC. This model has the potential power to help clinicians in making treatment decisions.

External validation of NTCP-models for radiation pneumonitis in lung cancer patients treated with chemoradiotherapy

PurposeNormal tissue complication probability (NTCP) models can be used to estimate the risk of radiation pneumonitis (RP). The aim of this study was to externally validate the most frequently used prediction models for RP, i.e., the QUANTEC and APPELT models, in a large cohort of lung cancer patients treated with IMRT or VMAT. [1–2] Methods and materialsThis prospective cohort study, included lung cancer patients treated between 2013 and 2018. A closed testing procedure was performed to test the need for model updating. To improve model performance, modification or removal of variables was considered. Performance measures included tests for goodness of fit, discrimination, and calibration. ResultsIn this cohort of 612 patients, the incidence of RP ≥ grade 2 was 14.5%. For the QUANTEC-model, recalibration was recommended which resulted in a revised intercept and adjusted regression coefficient (from 0.126 to 0.224) of the mean lung dose (MLD),. The APPELT-model needed revision including model updating with modification and elimination of variables. After revision, the New RP-model included the following predictors (and regression coefficients): MLD (B = 0.250), age (B = 0.049, and smoking status (B = 0.902). The discrimination of the updated APPELT-model was higher compared to the recalibrated QUANTEC-model (AUC: 0.79 vs. 0.73). ConclusionsThis study demonstrated that both the QUANTEC- and APPELT-model needed revision. Next to changes of the intercept and regression coefficients, the APPELT model improved further by model updating and performed better than the recalibrated QUANTEC model. This New RP-model is widely applicable containing non-tumour site specific variables, which can easily be collected.

Efficacy and safety of durvalumab + chemotherapy vs. atezolizumab + chemotherapy in the treatment of small‑cell lung cancer: a retrospective comparative cohort study.

Durvalumab and atezolizumab have recently been approved in extensive small cell lung cancer (SCLC) with moderate median overall survival (OS) improvements. However, only limited data exist regarding the impact of immunotherapy in real-world SCLC patients. This study sought to assess the efficacy and safety of atezolizumab plus chemotherapy and durvalumab plus chemotherapy in the treatment of SCLC in a real-world setting. A retrospective cohort study of all patients treated for SCLC with chemotherapy with PD-L1 inhibitor, at 3 centers in China between February 1, 2020 and April 30, 2022. Patient characteristics, adverse-events and survival analyses were conducted. A total of 143 patients were enrolled in this study, 100 were treated with durvalumab and the remainder with atezolizumab. The baseline characteristics of the two groups were fundamentally balanced before using PD-L1 inhibitors (P>0.05). The median OS (mOS) of the patients who received durvalumab or atezolizumab as the first-line treatment were 22.0 and 10.0 months, respectively (P=0.03). Survival analysis of patients with brain metastasis (BM) revealed that the median progression-free survival (mPFS) of patients without BM treated with durvalumab plus chemotherapy (5.5 months) was longer than that of those with BM (4.0 months) (P=0.03). In contrast, in the atezolizumab plus chemotherapy regimen, BM did not affect survival. In addition, the addition of radiotherapy to treatment with PD-L1 inhibitors in combination with chemotherapy has a tendency to improve long-term survival. As for safety analysis, there was no significant difference in the incidence of immune-related adverse events (IRAEs) during PD-L1 inhibitor therapy between the 2 groups (P>0.05). And during treatment with immunochemotherapy, radiotherapy was not associated with the development of IRAE (P=0.42) but increased the risk of immune-related pneumonitis (P=0.026). The implication of this study for clinical practice is a preference for durvalumab in first-line immunotherapy for SCLC. In addition, appropriate radiotherapy during treatment with PD-L1 inhibitors in combination with chemotherapy may prolong long-term survival, but the occurrence of immune-related pneumonitis should be vigilant. Data from this study are limited and the baseline characteristics of the two populations still need to be more finely classified.

Independent association of metabolic tumor response on FDG-PET with pulmonary toxicity following risk-adaptive chemoradiation for unresectable non-small cell lung cancer: Inherent radiosensitivity or immune response?

BackgroundIn the context of a phase II trial of risk-adaptive chemoradiation, we evaluated whether tumor metabolic response could serve as a correlate of treatment sensitivity and toxicity. MethodsForty-five patients with AJCCv7 stage IIB-IIIB NSCLC enrolled on the FLARE-RT phase II trial (NCT02773238). [18F]fluorodeoxyglucose (FDG) PET-CT images were acquired prior to treatment and after 24 Gy during week 3. Patients with unfavorable on-treatment tumor response received concomitant boosts to 74 Gy total over 30 fractions rather than standard 60 Gy. Metabolic tumor volume and mean standardized uptake value (SUVmean) were calculated semi-automatically. Risk factors of pulmonary toxicity included concurrent chemotherapy regimen, adjuvant anti-PDL1 immunotherapy, and lung dosimetry. Incidence of CTCAE v4 grade 2+ pneumonitis was analyzed using the Fine-Gray method with competing risks of metastasis or death. Peripheral germline DNA microarray sequencing measured predefined candidate genes from distinct pathways: 96 DNA repair, 53 immunology, 38 oncology, 27 lung biology. ResultsTwenty-four patients received proton therapy, 23 received ICI, 26 received carboplatin-paclitaxel, and 17 pneumonitis events were observed. Pneumonitis risk was significantly higher for patients with COPD (HR 3.78 [1.48, 9.60], p = 0.005), those treated with immunotherapy (HR 2.82 [1.03, 7.71], p = 0.043) but not with carboplatin-paclitaxel (HR 1.98 [0.71, 5.54], p = 0.19). Pneumonitis rates were similar among selected patients receiving 74 Gy radiation vs 60 Gy (p = 0.33), proton therapy vs photon (p = 0.60), or with higher lung dosimetric V20 (p = 0.30). Patients in the upper quartile decrease in SUVmean (>39.7%) were at greater risk for pneumonitis (HR 4.00 [1.54, 10.44], p = 0.005) and remained significant in multivariable analysis (HR 3.34 [1.23, 9.10], p = 0.018). Germline DNA gene alterations in immunology pathways were most frequently associated with pneumonitis. ConclusionTumor metabolic response as measured by mean SUV is associated with increased pneumonitis risk in a clinical trial cohort of NSCLC patients independent of treatment factors. This may be partially attributed to patient-specific differences in immunogenicity.

Clinical features and risk factors for interstitial lung disease spreading in low-dose irradiated areas after definitive radiotherapy with or without durvalumab consolidation therapy for patients with non-small cell lung cancer

BackgroundThe current standard of care for patients with unresectable locally advanced non-small cell lung cancer (NSCLC) is chemoradiotherapy (CRT) combined with durvalumab consolidation therapy. However, radiotherapy (RT) always carries the risk of radiation pneumonitis (RP), which can preclude durvalumab continuation. In particular, the spread of interstitial lung disease (ILD) in low-dose areas or extending beyond the RT field often makes it difficult to determine the safety of continuation or rechallenging of durvalumab. Thus, we retrospectively analyzed ILD/RP after definitive RT with and without durvalumab, with assessment of radiologic features and dose distribution in RT.MethodsWe retrospectively evaluated the clinical records, CT imaging, and radiotherapy planning data of 74 patients with NSCLC who underwent definitive RT at our institution between July 2016 and July 2020. We assessed the risk factors for recurrence within one year and occurrence of ILD/RP.ResultsKaplan-Meier method showed that ≥ 7 cycles of durvalumab significantly improved 1-year progression free survival (PFS) (p < 0.001). Nineteen patients (26%) were diagnosed with ≥ Grade 2 and 7 (9.5%) with ≥ Grade 3 ILD/RP after completing RT. There was no significant correlation between durvalumab administration and ≥ Grade 2 ILD/RP. Twelve patients (16%) developed ILD/RP that spread outside the high-dose (> 40 Gy) area, of whom 8 (67%) had ≥ Grade 2 and 3 (25%) had Grade 3 symptoms. In unadjusted and multivariate Cox proportional-hazards models adjusted for V20 (proportion of the lung volume receiving ≥ 20 Gy), high HbA1c level was significantly correlated with ILD/RP pattern spreading outside the high-dose area (hazard ratio, 1.842; 95% confidence interval, 1.35–2.51).ConclusionsDurvalumab improved 1-year PFS without increasing the risk of ILD/RP. Diabetic factors were associated with ILD/RP distribution pattern spreading in the lower dose area or outside RT fields, with a high rate of symptoms. Further study of the clinical background of patients including diabetes is needed to safely increase the number of durvalumab doses after CRT.

Incidence and Risk Factors for Pneumonitis Associated With Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer: A Single Center Experience.

Immune checkpoint inhibitor (ICI) pneumonitis causes substantial morbidity and mortality. Estimates of real-world incidence and reported risk factors vary substantially. We conducted a retrospective review of 419 patients with advanced non-small cell lung cancer (NSCLC) who were treated with anti-PD-(L)1 with or without anti-CTLA-4 therapy. Clinical, imaging, and microbiological data were evaluated by multidisciplinary adjudication teams. The primary outcome of interest was grade ≥2 (CTCAEv5) pneumonitis. Clinicopathologic variables, tobacco use, cancer therapies, and preexisting lung disease were assessed for univariate effects using Cox proportional hazards models. We created multivariate Cox proportional hazards models to assess risk factors for pneumonitis and mortality. Pneumonitis, pneumonia, and progression were modeled as time-dependent variables in mortality models. We evaluated 419 patients between 2013 and 2021. The cumulative incidence of pneumonitis was 9.5% (40/419). In a multivariate model, pneumonitis increased the risk for mortality (HR 1.6, 95% CI, 1.0-2.5), after adjustment for disease progression (HR 1.6, 95% CI, 1.4-1.8) and baseline shortness of breath (HR 1.5, 95% CI, 1.2-2.0). Incomplete resolution was more common with more severe pneumonitis. Interstitial lung disease was associated with higher risk for pneumonitis (HR 5.4, 95% CI, 1.1-26.6), particularly in never smokers (HR 26.9, 95% CI, 2.8-259.0). Pneumonitis occurred at a high rate and significantly increased mortality. Interstitial lung disease, particularly in never smokers, increased the risk for pneumonitis.

A multiomics approach-based prediction of radiation pneumonia in lung cancer patients: impact on survival outcome.

To predict the risk of radiation pneumonitis (RP), a multiomics model was built to stratify lung cancer patients. Our study also investigated the impact of RP on survival. This study retrospectively collected 100 RP and 99 matched non-RP lung cancer patients treated with radiotherapy from two independent centres. They were divided into training (n = 175) and validation cohorts (n = 24). The radiomics, dosiomics and clinical features were extracted from planning CT and electronic medical records and were analysed by LASSO Cox regression. A multiomics prediction model was developed by the optimal algorithm. Overall survival (OS) between the RP, non-RP, mild RP, and severe RP groups was analysed by the Kaplan‒Meier method. Sixteen radiomics features, two dosiomics features, and one clinical feature were selected to build the best multiomics model. The optimal performance for predicting RP was the area under the receiver operating characteristic curve (AUC) of the testing set (0.94) and validation set (0.92). The RP patients were divided into mild (≤ 2 grade) and severe (> 2 grade) RP groups. The median OS was 31months for the non-RP group compared with 49months for the RP group (HR = 0.53, p = 0.0022). Among the RP subgroup, the median OS was 57months for the mild RP group and 25months for the severe RP group (HR = 3.72, p < 0.0001). The multiomics model contributed to improving the accuracy of RP prediction. Compared with the non-RP patients, the RP patients displayed longer OS, especially the mild RP patients.

CBCT-guided adaptive radiotherapy using self-supervised sequential domain adaptation with uncertainty estimation.

Adaptive radiotherapy (ART) is an advanced technology in modern cancer treatment that incorporates progressive changes in patient anatomy into active plan/dose adaption during the fractionated treatment. However, the clinical application relies on the accurate segmentation of cancer tumors on low-quality on-board images, which has posed challenges for both manual delineation and deep learning-based models. In this paper, we propose a novel sequence transduction deep neural network with an attention mechanism to learn the shrinkage of the cancer tumor based on patients' weekly cone-beam computed tomography (CBCT). We design a self-supervised domain adaption (SDA) method to learn and adapt the rich textural and spatial features from pre-treatment high-quality computed tomography (CT) to CBCT modality in order to address the poor image quality and lack of labels. We also provide uncertainty estimation for sequential segmentation, which aids not only in the risk management of treatment planning but also in the calibration and reliability of the model. Our experimental results based on a clinical non-small cell lung cancer (NSCLC) dataset with sixteen patients and ninety-six longitudinal CBCTs show that our model correctly learns weekly deformation of the tumor over time with an average dice score of 0.92 on the immediate next step, and is able to predict multiple steps (up to 5 weeks) for future patient treatments with an average dice score reduction of 0.05. By incorporating the tumor shrinkage predictions into a weekly re-planning strategy, our proposed method demonstrates a significant decrease in the risk of radiation-induced pneumonitis up to 35% while maintaining the high tumor control probability.

Predict Early Pneumonitis in Health Care Using Hybrid Model Algorithms

Earlier methods concentrated on constructing a single CNN model, while the ensemble learning paradigm has received less attention. Based on our survey results, we chose to utilize an ensemble model comprising multiple CNN models to predict pneumonia diagnosis from x-rays. We proposed employing hybrid model algorithms to predict early pneumonitis in health care. Hybrid model algorithms are increasingly used in healthcare due to their ability to combine the strengths of multiple algorithms to achieve better performance than a single algorithm. In the case of early detection of pneumonitis, this is particularly important, as it is a serious condition that requires prompt diagnosis and treatment to prevent further complications. Artificial neural networks are well suited to process complex and non-linear data, which is important in healthcare where patient data can be highly heterogeneous. Decision trees can identify the most important features for predicting pneumonitis and can be used to generate rules for clinical decision-making. Support vector machines can be used for classification tasks, which is important in identifying patients who are at high risk for pneumonitis. By combining these algorithms in a hybrid model, it may be possible to achieve better performance than using a single algorithm alone. For example, an artificial neural network could be used to pre-process the data and identify the most important features, which are then fed into a decision tree for rule generation. The resulting rules could then be used to classify patients using a support vector machine.

Comparison of pneumonitis risk between immunotherapy alone and in combination with chemotherapy: an observational, retrospective pharmacovigilance study.

Importance: Checkpoint inhibitor pneumonitis (CIP) is a rare but serious adverse event that may impact treatment decisions. However, there is limited information comparing CIP risks between immune checkpoint inhibitor (ICI) monotherapy and combination with chemotherapy due to a lack of direct cross-comparison in clinical trials. Objective: To determine whether ICI combination with chemotherapy is superior to ICI in other drug regimens (including monotherapy) in terms of CIP risk. Study Design and Methods: This observational, cross-sectional and worldwide pharmacovigilance cohort study included patients who developed CIP from the World Health Organization database (WHO) VigiBase and the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Individual case safety reports (ICSR) were extracted from 2015 to 2020 in FAERS and from 1967 to 2020 in VigiBase. Timing and reporting odds ratio (ROR) of CIP in different treatment strategies were used to detect time-to-onset and the risk of pneumonitis after different immunotherapy regimens. Results: A total of 93,623 and 114,704 ICI-associated ICSRs were included in this study from VigiBase and FAERS databases respectively. 3450 (3.69%) and 3278 (2.86%) CIPs occurred after therapy initiation with a median of 62days (VigiBase) and 40days (FAERS). Among all the CIPs, 274 (7.9%) and 537 (16.4%) CIPs were associated with combination therapies. ICIs plus chemotherapy combination was associated with pneumonitis in both VigiBase [ROR 1.35, 95% CI 1.18-1.52] and FAERS [ROR 1.39, 95% CI 1.27-1.53]. The combination of anti-PD-1 antibodies and anti-CTLA-4 antibodies with chemotherapy demonstrated an association with pneumonitis in both VigiBase [PD-1+chemotherapy: 1.76, 95% CI 1.52-2.05; CTLA-4+chemotherapy: 2.36, 95% CI 1.67-3.35] and FAERS [PD-1+chemotherapy: 1.70, 95% CI 1.52-1.91; CTLA-4+chemotherapy: 1.70, 95% CI 1.31-2.20]. Anti-PD-L1 antibodies plus chemotherapy combinations did not show the association. Conclusion: Compared to ICI in other drug regimens (including monotherapy), the combination of ICI plus chemotherapy is significantly associated with higher pneumonitis toxicity. Anti-PD-1/CTLA4 medications in combination with chemotherapy should be obviated in patients with potential risk factors for CIP. Trial Registration: clinicaltrials.gov, ChiCTR2200059067.