INTRODUCTION:Immune checkpoint inhibitors (ICIs), although revolutionary in the field of oncology, have been associated with immune-related adverse events (irAEs) that affect nearly every organ of the body. Many common AEs are well documented, but in this review, we highlight some rare irAEs that are mostly limited to reports of observational or case studies. Although these irAEs can be difficult to associate with ICI use due to their scarcity and often delayed onset, understanding and characterizing these rare irAEs is crucial to refining treatment strategies and improving outcomes for patients with cancer receiving ICIs. AREAS COVERED:This review covers the rare irAEs affecting various organ systems, including cardiac, dermatological, endocrine, gastrointestinal, hematological, hepatobiliary, neurological, ocular, pancreatic, renal, and rheumatological. Information regarding irAEs compiled in this review are largely derived from case reports and case series and includes discussion surrounding proposed etiology, phenotype, and treatment of AEs. EXPERT OPINION:Rare irAEs can occur in nearly all organ systems. Although it is difficult to attribute causation of an AE to ICIs, it is important for clinicians to be aware of possible AEs to rapidly diagnose and treat potential symptoms. Further research should focus on strategies to improve recognition of rare irAEs.

Background and objectives: Therapeutic agents for cancer can cause unique pulmonary toxicities and mimic other conditions. The advent of new targeted molecular and immune therapies has changed the landscape of cancer treatment. These adverse events pose diagnostic and therapeutic challenges. This review aims to summarize the clinical presentations, radiographic patterns, and management strategies for noninfectious pulmonary complications associated with cancer therapies. Materials and methods: A literature review was conducted focusing on drug-induced lung injury (DILI), radiation-induced lung injury (RILI), pleural disease, pulmonary vascular complications, and other inflammatory conditions in patients with cancer. The data sources included clinical trials, guideline recommendations, observational studies, and expert consensus addressing incidence, pathophysiology, imaging findings, and treatment approaches. Results: Noninfectious pulmonary sequelae of anti-neoplastic therapies encompass a broad spectrum of etiologies. DILI occurs in up to 30% with variable onset and severity. The patterns can be diverse but include interstitial pneumonitis, organizing pneumonia, and diffuse alveolar damage. RILI is common and influenced by the radiation dose, volume, and concurrent therapies, and it may have both acute and chronic clinical and radiographic presentations. Pleural disease may arise from radiation and other agents, and the determination of etiology can impact management. Pulmonary vascular disease arises from many different etiologies, including therapies such as tyrosine kinase inhibitors and proteosome inhibitors, thromboembolic disease, as well as rare processes, including pulmonary veno-occlusive disease. Other conditions such as transfusion-related lung injury, cryptogenic organizing pneumonia, and interstitial lung abnormalities can also further complicate the diagnosis. Conclusions: Noninfectious pulmonary complications related to cancer therapies are diverse and often indistinguishable from infectious or malignant processes. The integration of clinical history, imaging, and selective invasive testing are needed for a timely diagnosis. Management typically involves withdrawal of the offending agent and corticosteroids, with immunosuppressive therapy reserved for severe or refractory cases. The awareness of these entities and early recognition are critical to optimizing outcomes.

Biological aging occurs heterogeneously across individuals and organs. However, current measures of biological age incompletely capture organ-specific differences in health and disease risk. Because chest CT visualizes multiple thoracic organs, it offers an opportunity to quantify structural aging across organ systems. Here, we developed MOSAIC-Age, a framework characterizing eight organ-specific aging clocks on chest CT. The clocks were developed and validated using 9,971 CT scans from CT-RATE and MIDRC, and subsequently locked and applied to two independent prospective cohorts with 35,293 participants from the National Lung Screening Trial and Genetic Epidemiology of COPD study. CT-derived biological age gaps (BAGs) were examined in relation to lifestyle and socioeconomic factors, prevalent comorbidities, incident chronic diseases, and all-cause and cause-specific mortality. Higher BAGs, indicating organs that appeared older on CT than expected for their chronological age, were broadly associated with adverse health characteristics, chronic disease burden, and increased mortality risk. Multiple disease outcomes were associated with aging across several organs, whereas in multivariable analyses including all eight organ-specific BAGs, the remaining associations were more organ specific. A greater number of markedly older-appearing organs and a faster pace of aging were each associated with higher mortality. Together, these findings demonstrate that routine chest CT captures both shared and organ-specific patterns of biological aging and establish CT-derived organ aging as a quantitative imaging biomarker for assessing multi-organ health and long-term disease risk. ### Competing Interest Statement The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: N. I. V. receives consulting fees from Regeneron, Amgen, Xencor, AstraZeneca, Tempus, Pfizer, Summit, OncoHost, Guardant, ImmunityBio, and research funding from EMD Serono, IDEAYA, Amgen, Summit, Regeneron, Sanofi, BMS, and OncoHost, outside the submitted work. M.C.B.G. has received research funding from Siemens Healthcare. T. C. reports speaker fees/honoraria (including travel/meeting expenses) from ASCO Post, AstraZeneca, Bio Ascend, Bristol Myers Squibb, Clinical Care Options, IDEOlogy Health, Medical Educator Consortium, Medscape, OncLive, PeerView, Physicians' Education Resource, Targeted Oncology; advisory role/consulting fees (including travel/meeting expenses) from AstraZeneca, Bristol Myers Squibb, Daiichi Sankyo, Genentech, Johnson & Johnson, Merck, Nuvalent, oNKo-innate, Pfizer, and RAPT Therapeutics; and institutional research funding from AstraZeneca, Bristol Myers Squibb and Merck. X. L. reports receiving consultant and advisory fees from Eli Lilly, AstraZeneca, EMD Serono, Daiichi Sankyo, Spectrum Therapeutics, Boehringer Ingelheim, Hengrui Therapeutics, Novartis, and research funding from Eli Lilly, Boehringer Ingelheim, all outside of the submitted work. M. A. reports research funding from Genentech, Nektar Therapeutics, Merck, GlaxoSmithKline, Novartis, Jounce Therapeutics, Bristol Myers Squibb, Eli Lilly, Adaptimmune, Shattuck Labs, Gilead, Verismo Therapeutics, and Lyell; advisory board roles for GlaxoSmithKline, Shattuck Labs, Bristol Myers Squibb, AstraZeneca, Insightec, Regeneron, Genprex, and Lyell; speaker fees from AstraZeneca, Nektar Therapeutics, SITC, and Regeneron; and participation on a safety review committee for Nanobiotix-MDA Alliance, Henlius, all outside of the submitted work. A.A.S. reports serving on the advisory board of DELFI Diagnostics and as an advisor to Droplet Biosciences, all outside of the submitted work. D.E.G. reports research funding from AstraZeneca, Karyopharm, and Novocure; stock ownership in Gilead and Medtronic; stock options in Early Marker, Inc. and OncoSeer Diagnostics, Inc.; consulting and advisory roles for AbbVie, AstraZeneca, Bayer, Catalyst Pharmaceuticals, EMD Serono, and GSK; service on data and safety monitoring boards for Daiichi Sankyo, Summit Therapeutics, and Taiho Oncology; royalties from Oxford University Press; and roles as co-founder and Chief Medical Officer of OncoSeer Diagnostics, Inc., all outside of the submitted work. J. Y. C. has received travel sponsorship from Accuray and Varian Medical Systems, and grants from Varian Medical Systems, outside the submitted work. D. L. G. reports honoraria for scientific advisory boards from AstraZeneca, Sanofi, Alethia Biotherapeutics, Menarini, Eli Lilly, 4D Pharma and Onconova, and research support from Janssen, Takeda, Astellas, Ribon Therapeutics, NGM Biopharmaceuticals, Boehringer Ingelheim, Mirati Therapeutics and AstraZeneca, all outside of the submitted work. C. C. W. reports research support from Medical Imaging and Data Resource Center from NIBIB/University of Chicago and royalties from Elsevier, outside of the submitted work. J. V. H. reports receiving advisory/consulting fees from AstraZeneca, Boehringer Ingeheim, Catalyst, Genentech, GlaxoSmithKline, Guardant Health, Foundation Medicine, Hengrui Therapeutics, Eli Lilly, Novartis, Spectrum, Sanofi, Takeda Pharmaceuticals, Mirati Therapeutics, Bristiol Myers Squibb, BrightPath Biotherapeutics, Janssen Global Services, Nexus Health Systems, EMD Serono, Pneuma Respiratory, Kairos Venture Investments, Leads Biolabs, RefleXion, and research funding from GlaxoSmithKline, AstraZeneca, Spectrum, all outside of the submitted work. J. Z. reports grants from Merck, Novartis, Johnson and Johnson; and personal fees from BMS, AZ, Novartis, Johnson and Johnson, GenePlus, Hengrui, Innovent, outside the submitted work. J. W. reports research funding from Siemens Healthcare. The remaining authors declare that they have no competing interests. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Institutional Review Board of The University of Texas MD Anderson Cancer Center gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes CT-RATE imaging data are available through the Hugging Face repository under the repository's access conditions for academic, research, and educational use (https://huggingface.co/datasets/ibrahimhamamci/CT-RATE). MIDRC imaging data are available through the MIDRC Data Commons to registered users under the applicable MIDRC data use agreement (https://data.midrc.org/). The NLST imaging data are available through The Cancer Imaging Archive (https://www.cancerimagingarchive.net/collection/nlst/), and NLST clinical data are available through the NCI Cancer Data Access System (https://cdas.cancer.gov/nlst/). The COPDGene phenotype and imaging data used in this study are available through controlled access via dbGaP under study accession numbers phs000179.v7.p2 and phs004023.v1.p2, respectively. The paired CT/PET-CT data are not publicly available owing to patient privacy considerations but are available for research purposes from the corresponding author upon reasonable request. The pretrained organ-clock model weights are also available from the corresponding author upon reasonable request. National Institutes of Health, R01CA262425, R01CA276178 Cancer Prevention and Research Institute of Texas, RP240117 Victory Houston Permanent Health Funds QIAC Partnership in Research Grant Rexanna's Foundation for Fighting Lung Cancer

e16600 Background: Enfortumab vedotin plus pembrolizumab (EV+P) is first line standard of care for locally advanced or metastatic urothelial carcinoma (LA/mUC). Both agents carry pneumonitis risk, yet real-world incidence and predictors of pneumonitis with this combination remain poorly characterized. Methods: We conducted a retrospective cohort study of patients receiving EV+P for LA/mUC at MD Anderson Cancer Center. Pneumonitis was adjudicated by a pulmonologist and graded per CTCAE v5.0. Given the high risk for mortality from other causes, cumulative incidence was estimated using Fine-Gray competing risk analysis with death as competing event. Risk factors were evaluated using univariable subdistribution hazard regression. Results: Among 264 patients (median age 72 years; 76% male; 67% metastatic; median follow-up 10.3 months), pneumonitis developed in 17 (6.4%; 95% CI, 4.1-10.1%): Grade 1-2, 9 (53%); Grade ≥3, 8 (47%). Median time to onset was 69 days (IQR, 48-82), with 82% of events occurring within 90 days. During follow-up, 70 deaths occurred; the 90-day cumulative incidence was 5.4% (95% CI, 2.5-8.3%). One patient (6%) required ICU admission; none required mechanical ventilation. Corticosteroids were administered in 7 (41%). In competing risk regression, baseline interstitial lung abnormalities (ILA; sHR 2.99; 95% CI, 0.84-10.66; P = 0.09), prior ICI therapy (sHR 2.46; 95% CI, 0.81-7.44; P = 0.11), and COPD (sHR 2.36; 95% CI, 0.80-6.96; P = 0.12) showed the strongest signals, though statistical significance was not reached (Table). Pneumonitis incidence was higher in patients with ILA (17.6% vs 5.7% without), and 12.9% with prior ICI vs 5.6% without. In time-dependent Cox analysis, pneumonitis was associated with a trend toward increased mortality (HR 1.67; 95% CI, 0.76–3.69; P = 0.20), though this did not reach statistical significance. Conclusions: Pneumonitis occurred in 6.4% of patients receiving EV+P; however, 47% of events were Grade ≥3 and most occurred within 90 days. Baseline ILA, prior ICI therapy, and COPD showed higher incidence, representing hypothesis-generating signals for risk stratification. Close pulmonary monitoring during early treatment cycles may be warranted in patients with these features. Risk factors for pneumonitis (fine-gray subdistribution hazard model). Variable sHR (95% CI) P-value Age (per 10 years) 0.88 (0.66-1.17) 0.39 Male sex 0.57 (0.21-1.55) 0.27 Ever smoker 1.18 (0.44-3.17) 0.75 Interstitial lung abnormalities 2.99 (0.84-10.66) 0.09 Prior ICI therapy 2.46 (0.81-7.44) 0.11 COPD 2.36 (0.80-6.96) 0.12 Prior therapy lines (per line) 1.16 (0.99-1.35) 0.07 ECOG ≥2 0.63 (0.15-2.73) 0.54 Abbreviations: CI, confidence interval; COPD, chronic obstructive pulmonary disease; ECOG, Eastern Cooperative Oncology Group; ICI, immune checkpoint inhibitor; sHR, subdistribution hazard ratio.

Chronic obstructive pulmonary disease (COPD) affects 40–60

INTRODUCTION:Immune checkpoint inhibitors have become an increasingly effective treatment for various malignancies, although their use is associated with a range of organ toxicities. As these therapies become more prevalent, it is critical to establish appropriate management and long-term surveillance strategies for patients who develop immune-related adverse events. AREAS COVERED:This review explores the chronic sequelae that may result from immune-related adverse events and focuses specifically on their persistence, outcomes, and implications for future research. A literature review was conducted using PubMed to identify relevant articles from within the last 10 years. EXPERT OPINION:While acute management of irAEs has improved over the past decade, there is a major gap in understanding and addressing their chronic sequelae. Challenges in studying these sequelae include the complexity of cancer care, overlapping clinical presentations, and previously, a lack of long-term data. Continued research from large multicenter studies and dedicated databases can identify high-risk patients, inform risk-benefit discussions, refine management strategies, and pave the way for evidence-based, long-term care.

BACKGROUND:Checkpoint inhibitor pneumonitis (CIP) is a highly morbid complication of immune checkpoint immunotherapy, characterized by acute lung injury leading, in severe cases, to hypoxic respiratory failure and death. CIP incidence in lung cancer is high (10%-15%). Yet, the pathophysiology of CIP is poorly understood. OBJECTIVE/METHODS:To investigate the mechanisms underlying alveolar inflammation in patients with CIP, human bronchoalveolar lavage fluid (BALF) samples from control patients and patients with CIP were analyzed using flow cytometry, single-cell RNA sequencing (scRNA-seq), and ELISA. Findings were validated using multiple external cohorts. In vitro experiments and in vivo rodent models were employed to investigate the mechanisms driving alveolar inflammation in CIP. RESULTS:Analysis of scRNA-seq and flow cytometry data demonstrated increased macrophages in patients with CIP compared to controls. Several distinct proinflammatory alveolar macrophage subsets were increased in CIP. CIP macrophages expressed increased CCL18 at the transcript (scRNA-seq), cellular (flow cytometry) and secreted protein (BALF ELISA) levels. BALF CCL18 levels were associated with clinical CIP severity. CCL18 overexpression in mice promoted lung inflammation that phenocopied human CIP, including upregulation of proinflammatory macrophage subsets. CONCLUSION:These findings suggest that BALF macrophages and CCL18 protein levels are increased in patients with CIP and associate with greater CIP severity. Additionally, CCL18 promotes lung inflammation in mice that mimics human CIP, suggesting a causal role for CCL18 in CIP.

INTRODUCTION:Immune checkpoint inhibitors (ICIs) have transformed the treatment of multiple malignancies and significantly increased survival; however, by enhancing antitumor immunity, they can also cause off-target immune-related adverse events (irAEs), some of which become refractory to standard first-line corticosteroids. Refractory irAEs (r-irAEs) require timely recognition and personalized, organ-specific escalation strategies based on toxicity severity and mechanistic insights. AREAS COVERED:In this narrative review, we synthesize current evidence across organ systems on the epidemiology, clinical features, diagnostic evaluation, and management of r-irAEs, with a particular focus on second- and third-line immunosuppressive options. We summarize findings from retrospective cohorts, prospective studies, guideline statements, and high-quality case series relevant to steroid-refractory irAEs and highlight practical considerations for escalation. The literature search was performed in PubMed and Embase for publications from January 2010 through August 2025. EXPERT OPINION:Tailored treatment strategies and structured escalation algorithms are needed to optimize outcomes for patients with r-irAEs. Integration of emerging biomarkers, endoscopic and histologic findings, and tumor microenvironment features may facilitate earlier recognition of steroid-refractory disease and more individualized escalation of immunosuppression.

Introduction:Trastuzumab deruxtecan (T-DXd) has transformed treatment for HER2-expressing malignancies, yet pneumonitis remains a potentially fatal toxicity. Most pneumonitis data derive from breast cancer cohorts, but risk factors and outcomes in non-breast solid organ tumors are poorly characterized. Materials and Methods:We conducted a retrospective, single-center cohort study of adults with advanced non-breast solid organ tumors receiving T-DXd in routine clinical practice at a comprehensive cancer center (January 2019-May 2025). Pneumonitis was defined as new or worsening radiographic infiltrates not developing due to infection, disease progression, or an alternative etiology. Cumulative incidence was estimated using competing-risk methods. Fine-Gray subdistribution hazard regression identified risk factors, and extended Cox proportional hazards regression assessed the association between pneumonitis and overall survival. Results:Among 99 patients (median age, 65 years; 61% female), primary tumor sites included lung (43%), gynecologic (28%), gastrointestinal or esophageal (15%), and other (14%). Pneumonitis occurred in 11 patients (11.1%), predominantly among those with lung cancer (20.9% vs 3.6% non-lung; p = 0.009). Median time to onset was 144 days. Grade 5 pneumonitis occurred in three patients. In univariable competing-risk analysis, a higher T-DXd dose (subdistribution hazard ratio [sHR], 2.43; p = 0.001) and a short washout from prior therapy (≤14 days; sHR, 4.62; p = 0.01) were associated with pneumonitis. In the lung cancer subgroup, current smoking was associated with pneumonitis in an exploratory adjusted model (sHR, 3.55; p = 0.002). Pneumonitis was associated with a 3-fold increased mortality risk in adjusted time-varying Cox analysis (HR, 3.26; p = 0.003). Conclusion:T-DXd-associated pneumonitis disproportionately affects patients with lung cancer and confers substantial mortality risk. A higher T-DXd dose and a short interval from prior therapy may increase pneumonitis risk but require validation in larger cohorts.

e20531 Background: Interstitial lung abnormalities (ILAs) are established risk factors for immune checkpoint inhibitor–related pneumonitis (ICI-P), but qualitative ILA assessment is subjective. We evaluated whether quantitative lung fibrosis (QLF) metrics from pretreatment computed tomography (CT) are associated with ICI-P in patients with non–small cell lung cancer (NSCLC) receiving immune checkpoint inhibitors (ICIs). Methods: We retrospectively analyzed 241 patients with metastatic NSCLC treated with ICIs. Pretreatment CT scans underwent quantitative analysis using commercial software (VIDA) to extract QLFs representing consolidation, ground-glass opacity (GGO), emphysema, reticulation, and honeycombing. QLFs were quantified by percentage, volume, and estimated mass at total lung, lobar (upper vs lower), and subregional (core [central] vs peel [peripheral]) levels. Associations between QLFs and ICI-P were evaluated using univariate logistic regression. Results: Regional QLFs demonstrated differential associations with ICI-P. Upper-lobe QLFs were not associated with pneumonitis (all p≥0.13). In contrast, lower-lobe mass-based fibrosis metrics were associated with increased ICI-P risk, including GGO mass (OR 1.005, 95% CI 1.001–1.010; p=0.030), quantitative ILD (QILD) mass (OR 1.004, 95% CI 1.000–1.008; p=0.031), and quantitative ILA (QILA) mass (OR 1.004, 95% CI 1.001–1.007; p=0.024). Total-lung QILA mass showed a trend toward association (OR 1.002, 95% CI 1.000–1.004; p=0.086). Subregional analysis demonstrated stronger associations in peripheral (peel) regions; peel consolidation volume was associated with ICI-P (OR 1.102, 95% CI 1.013–1.198; p=0.023), whereas no core metric reached significance. Conclusions: Quantitative fibrosis metrics from pretreatment CT, particularly lower-lobe and peripheral mass-based QLFs, are associated with immune checkpoint inhibitor–related pneumonitis in NSCLC. Incorporation of regional quantitative fibrosis measures into baseline imaging assessment may help identify patients at elevated pneumonitis risk and inform surveillance strategies. These findings support further multivariable validation of quantitative CT fibrosis metrics as imaging biomarkers for immunotherapy-related pneumonitis. Associations between quantitative lung fibrosis metrics and immune checkpoint inhibitor–related pneumonitis in NSCLC. Region Metric (Mass-based QLF) (gm) OR 95% CI p-value Lower lobe GGO Mass 1.005 1.001–1.010 0.030 Lower lobe QILD Mass 1.004 1.000–1.008 0.031 Lower lobe QILA Mass 1.004 1.001–1.007 0.024 Upper lobe No significant predictors — — ≥0.13 Total lung QILA Mass 1.002 1.000–1.004 0.086

Critically ill patients with acute leukemia often require an intensive care unit (ICU) admission. As major therapeutic advances have been made during the last decades, the aim of this study was to assess temporal trends in ICU mortality, and identify prognostic factors to inform clinician decision-making. We conducted an individual participant data meta-analysis of studies including adults with acute leukemia admitted to the ICU. Patients with a history of allogeneic hematopoietic stem cell transplantation were excluded. Mixed-effects logistic regression models, accounting for center of ICU admission as a random variable, evaluated factors associated with ICU mortality, with particular focus on year of ICU admission, age (> 65 years) and invasive mechanical ventilation. A total of 2003 patients from 55 ICUs across 19 countries were included (median age 58 years [IQR 44–67]; 72

BackgroundThe efficacy of cellular therapies has been demonstrated in hematologic malignancies, and their use is expanding to solid tumors. Predictors of outcomes and toxicities remain limited in patients undergoing cellular therapies for solid tumors.MethodsData on patients with solid tumors who received cellular therapies between January 2016 and July 2025 in the Department of Investigational Cancer Therapeutics (Phase I Clinical Trials Program) at The University of Texas MD Anderson Cancer Center were reviewed retrospectively using the institutional CHIMERA database platform.ResultsAmong 122 patients, increased baseline C-reactive protein (CRP) was associated with shorter overall survival (OS) (hazard ratio [HR] 1.009, 95% confidence interval (CI) 1.005–1.013; P < 0.001), and higher log-transformed cell dose was associated with longer progression-free survival (PFS) (HR 0.636, 95% CI 0.476–0.850; P = 0.002). Among patients with baseline pulmonary function testing, zDLCO was associated with OS (HR 0.794, 95% CI 0.674-0.936; P = 0.006) and PFS (HR 0.826, 95% CI 0.696-0.979; P = 0.028). Cytokine release syndrome (CRS) occurred in 70 participants (57.4%). In the multivariate analysis, lower baseline absolute neutrophil count was associated with CRS of any grade (odds ratio [OR] 0.594, 95% CI 0.376-0.939; P = 0.026) and with CRS grade 2 or higher (OR 0.470, 95% CI 0.252-0.877; P = 0.018). Immune effector cell-associated neurotoxicity syndrome developed in 11 patients (9.0%).ConclusionsBaseline parameters such as CRP and pulmonary function may help identify patients at higher risk of adverse outcomes and toxicity during cellular therapy for solid tumors, and warrant prospective evaluation.

Background:Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy but can cause serious immune-related adverse events (irAEs), with pneumonitis (ICI-P) being among the most severe. Early identification of high-risk patients before ICI initiation is critical to close monitoring, enable timely intervention, and optimize outcomes. Purpose:To develop and validate a deep learning foundation model to predict ICI-P from baseline CT scans in patients with lung cancer. Methods:We designed the Checkpoint-Inhibitor Pneumonitis Hazard EstimatoR (CIPHER), a deep learning-powered foundation model combining contrastive learning with a transformer-based masked autoencoder to predict ICI-P from baseline CT scans in lung cancer patients. Using self-supervised learning, CIPHER was pre-trained on 590,284 CT slices from 2,500 non-small cell lung cancer (NSCLC) patients, to understand heterogeneous lung parenchyma. Following pre-training, the model was fine-tuned on an internal NSCLC cohort for ICI-P risk prediction, with images from 254 patients used for model development and from 93 patients for internal validation. We compared CIPHER with classical radiomic models. We also validated CIPHER on an external NSCLC cohort of 116 patients. Results:In our internal immunotherapy cohort, CIPHER consistently distinguished patients at elevated risk of ICI-P from those without the event, with AUCs ranging from 0.77 to 0.85. In head-to-head benchmarking, CIPHER achieved an AUC of 0.83, outperforming radiomic model. In the external validation cohort, CIPHER maintained high performance (AUC=0.83; balanced accuracy=81.7%), exceeding the radiomic models (Delong p=0.0318) and demonstrating superior specificity without sacrificing sensitivity. By contrast, radiomic model, despite high sensitivity (85.0%), showed markedly lower specificity (45.8%). Confusion matrix analyses confirmed CIPHER's robust classification, correctly identifying 80 of 96 non-ICI-P cases and 16 of 20 ICI-P cases. Conclusions:We developed and externally validated CIPHER for predicting future risk of developing ICI-P from pre-treatment CT scans. With prospective validation, CIPHER can be incorporated into routine patient management to improve outcomes.

Background: Malignant pleural effusions (MPEs) are common in cancer patients and significantly impair physical activity. Although symptom relief is the primary treatment goal, the extent of activity limitation and the effectiveness of interventions remain unclear. We used actigraphy to assess the impact of thoracentesis on activity level. The primary objective was to evaluate the association between physical activity (via ActiGraph), quality of life [Short Form 6-Dimension index (SF-6D) utility score], and dyspnea (Borg scale) at weeks 1 and 2 following thoracentesis. Methods: We conducted a prospective, observational, single-center study in adults with symptomatic, moderate-to-large MPEs. Results: Participants wore actigraphy devices for a mean of 17.7 hours daily. Higher average steps in week 2 significantly correlated with higher week 2 SF-6D utility scores. Higher calorie expenditure in week 1 significantly correlated with better week 1 SF-6D utility scores. However, no actigraphy metrics significantly affected SF-6D utility score changes from week 1 to week 2. For Borg, higher average triaxial movement in week 2 was modestly associated with lower dyspnea in week 2. Greater week 1 increases (slopes) in calories, moderate-to-vigorous physical activity (MVPA), and triaxial movement significantly predicted larger Borg scale reduction from week 1 to week 2. Conclusions: These findings suggest that improvement in SF-6D utility scores is tied to average activity levels (calories in week 1, steps in week 2), whereas dyspnea improvement by Borg scale over time is more strongly related to early gains in week 1 activity. Triaxial movement was also associated with less dyspnea in week 2.

Bronchiolitis obliterans syndrome (BOS) represents a significant source of morbidity and non-relapse mortality among children and young adults treated with allogeneic hematopoietic stem cell transplantation (aHSCT). Pulmonary function testing (PFT) pre- and post-aHSCT may allow for pre-symptomatic detection of BOS, and thus early intervention. Current guidelines and practices vary regarding which tests to perform and timing relative to transplant. A systematic review evaluating PFT before and after pediatric aHSCT was conducted to inform American Thoracic Society clinical practice guidelines on detection of BOS. To determine the optimal approach to conducting PFT prior to and after pediatric aHSCT. We performed a systematic review of the literature to identify studies of PFT in human aHSCT recipients < 25 years of age to address two questions: (1) Should pre-transplant screening PFT be performed in pediatric patients who will undergo aHSCT? (2) At what frequency should pediatric patients who have had aHSCT undergo PFT? We searched in Medline through August 2022 for studies that enrolled patients < 25 years of age being treated with aHSCT for whom PFT data were reported before or after transplant. The 30 studies with pre-transplant PFT data showed a wide range of findings, with the majority demonstrating abnormalities. In studies reporting respiratory symptoms, 85–100