Citations

Background: Patients with telomere biology disorders (TBD) develop hepatic disease, including hepatitis, cirrhosis, and hepatopulmonary syndrome. No specific treatment exists for TBD-related liver disease, and the role of liver transplantation (LT) remains controversial. Our study objectives were to describe the clinical characteristics, management, and outcomes in patients with TBD-related liver disease, and their LT outcomes. Methods: Data from 83 patients with TBD-associated liver disease were obtained from 17 participating centers in the Clinical Care Consortium of Telomere-Associated Ailments and by self-report for our retrospective, multicenter, international cohort study. Results: Group A (“Advanced”) included 40 patients with advanced liver disease. Of these, 20 underwent LT (Group A T ). Group M (“Mild”) included 43 patients not warranting LT evaluation, none of whom were felt to be medically unfit for liver transplantation. Supplemental oxygen requirement, pulmonary arteriovenous malformation, hepatopulmonary syndrome, and higher bilirubin and international normalized ratio values were associated with Group A. Other demographics, clinical manifestations, and laboratory findings were similar between groups. Six group A patients were declined for LT; 3 died on the waitlist. Median follow-up post-LT was 2.9 years (range 0.6–13.2 y). One-year survival post-LT was 73%. Median survival post-LT has not been reached. Group A T patients had improved survival by age compared to all nontransplant patients (log-rank test p = 0.02). Of 14 patients with pretransplant hypoxemia, 8 (57%) had improved oxygenation after transplant. Conclusions: LT recipients with TBD do not exhibit excessive posttransplant mortality, and LT improved respiratory status in 57%. A TBD diagnosis should not exclude LT consideration.

AbstractBackgroundThe potential association of long‐term oral corticosteroid (OCS) use with adverse events (AEs) in patients with bullous pemphigoid (BP) is not well characterized in a real‐world setting.ObjectivesTo evaluate the effect of OCS use and treatment duration on the incident AEs in patients with BP.MethodsThis retrospective cohort study used medical and pharmacy claims and patient enrollment data from IQVIA PharMetrics® Plus from 2006−2021. Eligible patients had a diagnosis of BP between 1 January 2006 and 30 June 2020 (≥2 claims for BP ≥ 30 days apart). Patients in the OCS cohort also had a claim for OCS use, ≥7.5 mg daily dose of prednisone or equivalent, and no claims for a nonoral systemic corticosteroid (CS) at any time during the study period. A control cohort of patients with BP not using OCS was also selected. Relative risk ratios were estimated between the incidence of AEs in OCS users with different exposure durations (short‐term, <30 days; medium‐term, 30−90 days; long‐term, >90 days) and nonusers by Poisson regression, after adjusting for age, sex, prior drug use, and baseline Charlson Comorbidity Index score within the follow‐up period.ResultsAt the 1‐year follow‐up, long‐term OCS users had a higher incidence of infections, cataract, osteoporosis, heart failure, depression or anxiety, and diabetes compared with OCS nonusers (p < 0.05). Furthermore, compared with nonusers, long‐term users had increased 1‐year risks (risk ratio; 95% confidence interval) for heart failure (2.27; 1.50−3.44), diabetes (2.05; 1.30−3.24), osteoporosis (1.72; 1.23−2.41), and infection (1.50; 1.13−1.99). Long‐term OCS users also had increased 1‐year risks for heart failure (2.00; 1.21−3.28) and osteoporosis (1.70; 1.16−2.50) compared with short‐term OCS users.ConclusionsLong‐term OCS use (≥7.5 mg) in patients with BP was associated with an increased risk of AEs. Study findings demonstrate a need for steroid‐sparing options with an improved safety profile.

Background: The mosquito-borne Chikungunya virus infection is one of the most important emerging virus diseases globally. Local transmission has been found in the United States. There are very few published reports concerning the cardiac complications in general and less of arrhythmias in particular. Chikungunya can be fatal: there have been sudden deaths reports . Objective: To investigate arrhythmic complications of Chikungunya myocarditis. Methods: Prospective multicenter observational study of 280 patients with a Chikunguya infection from a Venezuelan Outbreak. Clinical evaluation, ECG, laboratory including virological evaluation and cardiac biomarkers, Echocardiogram, Holter and cardiac MRI procedures were carried out. Results: Of the 280 patients examined, 113 patients were male, with a mean age of 59 ± 9; 270 patients presented with fever and polyarthralgia and 85 developed palpitations. Arrhythmias occured in 45% of cases; they included bradyarrhythmias (33%), atrial and ventricular ectopic beats and tachyarrhythmias in which atrial fibrillation was observed in 19 cases. There were also ectopic atrial tachycardia and non sustained ventricular tachycardia, conduction disturbances and 3 cases of sudden death. Conclusion: Physicians should know that almost half of the Chikungunya patients will develop arrhythmias and manifest or silent myocarditis. In the proper epidemiological context, the triad of fever, polyarthralgia and new arrhythmia including bradiarrhythmias suggest Chikungunya Myocarditis.

Abstract Background: Immune checkpoint inhibitors (ICIs) have significantly improved outcomes for patients with metastatic non-small cell lung cancer (NSCLC). However, clinical management is challenging. The PD-L1 biomarker does not optimally guide the choice between ICI monotherapy and combination ICI-chemotherapy, and there are currently no biomarkers to predict immune-related adverse events (irAEs). Here, we describe a versatile platform based on plasma proteomics and machine learning for generating predictive tools to support treatment decisions. Methods: Pre-treatment plasma samples were collected from 616 NSCLC patients receiving ICI-based therapy (NCT04056247). Clinical benefit (CB) data and irAEs were recorded. Proteomic profiling of plasma samples was performed using the SomaScan® assay, covering ~7000 proteins per sample. Proteins associated with Clinical Benefit (progression-free survival at 12 months) were classified as resistance-associated proteins (RAPs). Proteins associated with grade ≥3 irAEs occurring within the first 100 days of treatment were classified as toxicity-associated proteins (TAPs). RAPs and TAPs were integrated into two separate machine learning-based models, yielding CB and irAE probabilities, respectively. The CB model used a CB probability threshold to assign patients a PROphet-positive or PROphet-negative result. Bioinformatic analysis was performed on RAPs and TAPs. Results: CB and irAE models displayed strong predictive performance with a high correlation between predicted probability and observed CB or irAE rate (CB model: R2=0.98; p-value&lt;0.0001; irAE model: R2= 0.92; p-value &lt;0.0001). In the CB model, patients classified as PROphet-positive achieved significantly longer overall survival (OS) than PROphet-negative patients, with a median OS of 25.9 vs. 10.8 months (hazard ratio, HR = 0.51; p-value&lt;0.001). Furthermore, patients with PD-L1 ≥50% tumors and a PROphet-negative result had significantly longer OS with ICI-chemotherapy in comparison to ICI monotherapy (HR=0.23, p-value = 0.0003), suggesting that combination therapy is preferable for such patients despite high PD-L1 levels. Bioinformatic analysis showed that RAPs related to immune regulation, angiogenesis, chemo-resistance, and other potential resistance mechanisms displayed higher expression levels in patients who did not benefit from treatment. Neutrophil- and inflammation-related proteins were significantly enriched in patients who experienced irAEs. Conclusions: We describe two machine-learning based predictive tools that may be used separately or in combination to inform treatment decisions based on the patient’s likelihood to benefit from ICI therapy and to develop serious irAEs. Our findings also provide biological insights related to treatment resistance and immune-related toxicity. Citation Format: Michal Harel, Petros Christopoulos, Igor Puzanov, Jair Bar, Iris Kamer, Niels Reinmuth, Ina Koch, Mor Moskovitz, Adva Levy-Barda, Alona Zer, Michal Lotem, David Farrugia, Rivka Katzenelson, Gillian Price, Abed Agbarya, Helen Cheley, Adam Hassani, Mahmoud Abu-Amna, Tom Geldart, Anirban Chatterjee, Andreas Polychronis, Maya Gottfried, Yanyan Lou, Tatiana Harkovsky, Alison Brewster, Ido Wolf, Ella Tepper, Ben Yellin, Itamar Sela, Coren Lahav, Yehonatan Elon, Raya Leibowitz, Adam P. Dicker, Young Kwang Chae, Ryan J. Sullivan, David Carbone, David Gandara, Jarushka Naidoo. Plasma proteomics-based models for predicting therapeutic benefit and immune-related adverse events in non-small cell lung cancer patients treated with immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1208.

PURPOSE Current guidelines for the management of metastatic non–small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. PATIENTS AND METHODS We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247 ) of patients undergoing PD-1/PD-L1 inhibitor–based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. RESULTS Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor–based treatments, evidenced by high concordance between predicted and observed CB ( R 2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). CONCLUSION Plasma proteome–based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor–based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

Abstract Objectives The objective of this study was to explore the prevalence, characteristics and risk factors of COVID-19 breakthrough infections (BIs) in idiopathic inflammatory myopathies (IIMs) using data from the COVID-19 Vaccination in Autoimmune Diseases (COVAD) study. Methods A validated patient self-reporting e-survey was circulated by the COVAD study group to collect data on COVID-19 infection and vaccination in 2022. BIs were defined as COVID-19 occurring ≥14 days after two vaccine doses. We compared BI characteristics and severity among patients with IIMs, patients with other autoimmune rheumatic and non-rheumatic diseases (AIRD, nrAID), and healthy controls (HCs). Multivariable Cox regression models were used to assess the risk factors for BI, severe BI ,and hospitalizations among patients with IIMs. Results Among the 9449 included responses, BIs occurred in 1447 respondents (15.3%). The median age was 44 years [interquartile range (IQR) 21], 77.4% were female, and 182 BIs (12.9%) occurred among the 1406 patients with IIMs. Multivariable Cox regression among the data for patients with IIMs showed increasing age to be a protective factor for BIs [hazard ratio (HR) = 0.98, 95% CI = 0.97–0.99], and HCQ and SSZ use were risk factors (HR = 1.81, 95% CI = 1.24–2.64, and HR = 3.79, 95% CI = 1.69–8.42, respectively). Glucocorticoid use was a risk factor for a severe BI (HR = 3.61, 95% CI = 1.09–11.8). Non-white ethnicity (HR = 2.61, 95% CI = 1.03–6.59) was a risk factor for hospitalization. Compared with other groups, patients with IIMs required more supplemental oxygen therapy (IIMs = 6.0% vs AIRDs = 1.8%, nrAIDs = 2.2% and HCs = 0.9%), intensive care unit admission (IIMs = 2.2% vs AIRDs = 0.6%, nrAIDs and HCs = 0%), advanced treatment with antiviral or monoclonal antibodies (IIMs = 34.1% vs AIRDs = 25.8%, nrAIDs = 14.6% and HCs = 12.8%) and had more hospitalization (IIMs = 7.7% vs AIRDs = 4.6%, nrAIDs = 1.1% and HCs = 1.5%). Conclusion Patients with IIMs are susceptible to severe COVID-19 BIs. Age and immunosuppressive treatments were related to the risk of BIs.

INTRODUCTION: Modeling supporting recommendations for colonoscopy and stool-based colorectal cancer (CRC) screening tests assumes 100% sequential participant adherence. The impact of observed adherence on the long-term effectiveness of screening is unknown. We evaluated the effectiveness of a program of screening colonoscopy every 10 years vs annual high-sensitivity guaiac-based fecal occult blood testing (HSgFOBT) using observed sequential adherence data. METHODS: The MIcrosimulation SCreening ANalysis (MISCAN) model used observed sequential screening adherence, HSgFOBT positivity, and diagnostic colonoscopy adherence in HSgFOBT-positive individuals from the National Colonoscopy Study (single-screening colonoscopy vs ≥4 HSgFOBT sequential rounds). We compared CRC incidence and mortality over 15 years with no screening or 10 yearly screening colonoscopy vs annual HSgFOBT with 100% and differential observed adherence from the trial. RESULTS: Without screening, simulated incidence and mortality over 15 years were 20.9 (95% probability interval 15.8–26.9) and 6.9 (5.0–9.2) per 1,000 participants, respectively. In the case of 100% adherence, only screening colonoscopy was predicted to result in lower incidence; however, both tests lowered simulated mortality to a similar level (2.1 [1.6–2.9] for screening colonoscopy and 2.5 [1.8–3.4] for HSgFOBT). Observed adherence for screening colonoscopy (83.6%) was higher than observed sequential HSgFOBT adherence (73.1% first round; 49.1% by round 4), resulting in lower simulated incidence and mortality for screening colonoscopy (14.4 [10.8–18.5] and 2.9 [2.1–3.9], respectively) than HSgFOBT (20.8 [15.8–28.1] and 3.9 [2.9–5.4], respectively), despite a 91% adherence to diagnostic colonoscopy with FOBT positivity. The relative risk of CRC mortality for screening colonoscopy vs HSgFOBT was 0.75 (95% probability interval 0.68–0.80). Findings were similar in sensitivity analyses with alternative assumptions for repeat colonoscopy, test performance, risk, age, and projection horizon. DISCUSSION: Where sequential adherence to stool-based screening is suboptimal and colonoscopy is accessible and acceptable—as observed in the National Colonoscopy Study—offering screening colonoscopy can increase screening effectiveness.

Abstract During the 20th century, inflammatory bowel disease (IBD) was considered a disease of early-industrialized regions in North America, Europe, and Oceania. At the turn of the 21st century, incidence of IBD increased in newly-industrialized and emerging regions in Africa, Asia, and Latin America, while prevalence in early-industrialized regions started to grow steadily. Changes in incidence and prevalence denote evolution of IBD across four epidemiologic stages: Stage 1 (Emergence), characterized by low incidence and prevalence; stage 2 (Acceleration in Incidence), characterized by rapidly rising incidence and low prevalence; and stage 3 (Compounding Prevalence), characterized by decelerating, plateauing, or declining incidence and steadily rising prevalence. A fourth stage (Prevalence Equilibrium) has been proposed where the slope of prevalence plateaus due to shifting demographics of an aging IBD population, but it has not yet been evidenced. To date, these stages have been theoretical without specific incidence/prevalence indicators defining transition points. Using real-world data from 490 population-based studies comprising 80 global regions and spanning over a century (1920–2023), we show spatiotemporal transitions across stages 1–3 and model transition towards stage 4. Understanding the evolution of IBD across epidemiologic stages allows healthcare systems to better prepare for the future worldwide burden of IBD.