Citations

AbstractWe conducted the first large genome‐wide association study to identify novel genetic variants that predict better (or poorer) prognosis in colorectal cancer patients receiving standard first‐line oxaliplatin‐based chemotherapy vs chemotherapy without oxaliplatin. We used data from two phase III trials, NCCTG N0147 and NCCTG N9741 and a population‐based patient cohort, DACHS. Multivariable Cox proportional hazards models were employed, including an interaction term between each SNP and type of treatment for overall survival (OS) and progression‐free survival. The analysis was performed for studies individually, and the results were combined using fixed‐effect meta‐analyses separately for resected stage III colon cancer (3098 patients from NCCTG N0147 and 549 patients from DACHS) and mCRC (505 patients from NCCTG N9741 and 437 patients from DACHS). We further performed gene‐based analysis as well as in silico bioinformatics analysis for CRC‐relevant functional genomic annotation of identified loci. In stage III colon cancer patients, a locus on chr22 (rs11912167) was associated with significantly poorer OS after oxaliplatin‐based chemotherapy vs chemotherapy without oxaliplatin (Pinteraction < 5 × 10−8). For mCRC patients, three loci on chr1 (rs1234556), chr12 (rs11052270) and chr15 (rs11858406) were found to be associated with differential OS (P < 5 × 10−7). The locus on chr1 located in the intronic region of RCSD1 was replicated in an independent cohort of 586 mCRC patients from ALGB/SWOG 80405 (Pinteraction = .04). The GWA gene‐based analysis yielded for RCSD1 the most significant association with differential OS in mCRC (P = 6.6 × 10−6). With further investigation into its biological mechanisms, this finding could potentially be used to individualize first‐line treatment and improve clinical outcomes.

ImportanceCurrent olfactory neuroblastoma (ONB) staging systems inadequately delineate locally advanced tumors, do not incorporate tumor grade, and poorly estimate survival and recurrence.ObjectiveThe primary aims of this study were to (1) examine the clinical covariates associated with survival and recurrence of ONB in a modern-era multicenter cohort and (2) incorporate Hyams tumor grade into existing staging systems to assess its ability to estimate survival and recurrence.Design, Setting, and ParticipantsThis retrospective, multicenter, case-control study included patients with ONB who underwent treatment between January 1, 2005, and December 31, 2021, at 9 North American academic medical centers.InterventionStandard-of-care ONB treatment.Main Outcome and MeasuresThe main outcomes were overall survival (OS), disease-free survival (DFS), and disease-specific survival (DSS) as C statistics for model prediction.ResultsA total of 256 patients with ONB (mean [SD] age, 52.0 [15.6] years; 115 female [44.9%]; 141 male [55.1%]) were included. The 5-year rate for OS was 83.5% (95% CI, 78.3%-89.1%); for DFS, 70.8% (95% CI, 64.3%-78.0%); and for DSS, 94.1% (95% CI, 90.5%-97.8%). On multivariable analysis, age, American Joint Committee on Cancer (AJCC) stage, involvement of bilateral maxillary sinuses, and positive margins were associated with OS. Only AJCC stage was associated with DFS. Only N stage was associated with DSS. When assessing the ability of staging systems to estimate OS, the best-performing model was the novel modification of the Dulguerov system (C statistic, 0.66; 95% CI, 0.59-0.76), and the Kadish system performed most poorly (C statistic, 0.57; 95% CI, 0.50-0.63). Regarding estimation of DFS, the modified Kadish system performed most poorly (C statistic, 0.55; 95% CI, 0.51-0.66), while the novel modification of the AJCC system performed the best (C statistic, 0.70; 95% CI, 0.66-0.80). Regarding estimation of DSS, the modified Kadish system was the best-performing model (C statistic, 0.79; 95% CI, 0.70-0.94), and the unmodified Kadish performed the worst (C statistic, 0.56; 95% CI, 0.51-0.68). The ability for novel ONB staging systems to estimate disease progression across stages was also assessed. In the novel Kadish staging system, patients with stage VI disease were approximately 7 times as likely to experience disease progression as patients with stage I disease (hazard ratio [HR], 6.84; 95% CI, 1.60-29.20). Results were similar for the novel modified Kadish system (HR, 8.99; 95% CI, 1.62-49.85) and the novel Dulguerov system (HR, 6.86; 95% CI, 2.74-17.18).Conclusions and RelevanceThe study findings indicate that 5-year OS for ONB is favorable and that incorporation of Hyams grade into traditional ONB staging systems is associated with improved estimation of disease progression.

AbstractBackgroundCOVID‐19 convalescent plasma (CCP) is an important therapeutic option for outpatients at high risk of hospitalization from SARS‐CoV‐2 infection. We assessed the safety of outpatient CCP transfusions administered during clinical trials.Study Design and MethodsWe analyzed data pertaining to transfusion‐related reactions from two randomized controlled trials in the U.S. that evaluated the efficacy of CCP versus control plasma in various ambulatory settings. Multivariable logistic regression was used to assess whether CCP was associated with transfusion reactions, after adjusting for potential confounders.ResultsThe combined study reported 79/1351 (5.9%) adverse events during the transfusion visit, with the majority 62/1351 (4.6%) characterized by mild, allergic‐type findings of urticaria, and/or pruritus consistent with minor allergic transfusion reactions; the other reported events were attributed to the patients' underlying disease, COVID‐19, or vasovagal in nature. We found no difference in the likelihood of allergic transfusion reactions between those receiving CCP versus control plasma (adjusted odds ratio [AOR], 0.75; 95% CI, 0.43–1.31). Risk of urticaria and/or pruritus increased with a pre‐existing diagnosis of asthma (AOR, 2.33; 95% CI, 1.16–4.67). We did not observe any CCP‐attributed antibody disease enhancement in participants with COVID‐19 or increased risk of infection. There were no life‐threatening severe transfusion reactions and no patients required hospitalization related to transfusion‐associated complications.DiscussionOutpatient plasma administration was safely performed for nearly 1400 participants. CCP is a safe therapeutic option for outpatients at risk of hospitalization from COVID‐19.

Importance People who smoked cigarettes may experience respiratory symptoms without spirometric airflow obstruction. These individuals are typically excluded from chronic obstructive pulmonary disease (COPD) trials and lack evidence-based therapies. Objective To define the natural history of persons with tobacco exposure and preserved spirometry (TEPS) and symptoms (symptomatic TEPS). Design, Setting, and Participants SPIROMICS II was an extension of SPIROMICS I, a multicenter study of persons aged 40 to 80 years who smoked cigarettes (&amp;gt;20 pack-years) with or without COPD and controls without tobacco exposure or airflow obstruction. Participants were enrolled in SPIROMICS I and II from November 10, 2010, through July 31, 2015, and followed up through July 31, 2021. Exposures Participants in SPIROMICS I underwent spirometry, 6-minute walk distance testing, assessment of respiratory symptoms, and computed tomography of the chest at yearly visits for 3 to 4 years. Participants in SPIROMICS II had 1 additional in-person visit 5 to 7 years after enrollment in SPIROMICS I. Respiratory symptoms were assessed with the COPD Assessment Test (range, 0 to 40; higher scores indicate more severe symptoms). Participants with symptomatic TEPS had normal spirometry (postbronchodilator ratio of forced expiratory volume in the first second [FEV 1 ] to forced vital capacity &amp;gt;0.70) and COPD Assessment Test scores of 10 or greater. Participants with asymptomatic TEPS had normal spirometry and COPD Assessment Test scores of less than 10. Patient-reported respiratory symptoms and exacerbations were assessed every 4 months via phone calls. Main Outcomes and Measures The primary outcome was assessment for accelerated decline in lung function (FEV 1 ) in participants with symptomatic TEPS vs asymptomatic TEPS. Secondary outcomes included development of COPD defined by spirometry, respiratory symptoms, rates of respiratory exacerbations, and progression of computed tomographic–defined airway wall thickening or emphysema. Results Of 1397 study participants, 226 had symptomatic TEPS (mean age, 60.1 [SD, 9.8] years; 134 were women [59%]) and 269 had asymptomatic TEPS (mean age, 63.1 [SD, 9.1] years; 134 were women [50%]). At a median follow-up of 5.76 years, the decline in FEV 1 was −31.3 mL/y for participants with symptomatic TEPS vs −38.8 mL/y for those with asymptomatic TEPS (between-group difference, −7.5 mL/y [95% CI, −16.6 to 1.6 mL/y]). The cumulative incidence of COPD was 33.0% among participants with symptomatic TEPS vs 31.6% among those with asymptomatic TEPS (hazard ratio, 1.05 [95% CI, 0.76 to 1.46]). Participants with symptomatic TEPS had significantly more respiratory exacerbations than those with asymptomatic TEPS (0.23 vs 0.08 exacerbations per person-year, respectively; rate ratio, 2.38 [95% CI, 1.71 to 3.31], P &amp;lt; .001). Conclusions and Relevance Participants with symptomatic TEPS did not have accelerated rates of decline in FEV 1 or increased incidence of COPD vs those with asymptomatic TEPS, but participants with symptomatic TEPS did experience significantly more respiratory exacerbations over a median follow-up of 5.8 years.

ABSTRACT Aims Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine learning (ML)-based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. Methods and results A ridge logistic regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo (InterTAK) Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). Thirty-one clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the curve (AUC), sensitivity and specificity. As secondary endpoint, a K-medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the 10 most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85–0.92), a sensitivity of 0.85 (0.78–0.95) and a specificity of 0.76 (0.74–0.79) in the internal validation cohort and an AUC of 0.82 (0.73–0.91), a sensitivity of 0.74 (0.61–0.87) and a specificity of 0.79 (0.77–0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs. 15.5% vs. 5.4% vs. 1.0.8% vs. 0.5%) which were consistent also in the external cohort. Conclusion A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death.

Background: Recognizing the early signs of cancer risk is vital for informing prevention, early detection, and survival. Methods: To investigate whether changes in circulating metabolites characterize the early stages of colorectal cancer (CRC) development, we examined the associations between a genetic risk score (GRS) associated with CRC liability (72 single-nucleotide polymorphisms) and 231 circulating metabolites measured by nuclear magnetic resonance spectroscopy in the Avon Longitudinal Study of Parents and Children (N = 6221). Linear regression models were applied to examine the associations between genetic liability to CRC and circulating metabolites measured in the same individuals at age 8 y, 16 y, 18 y, and 25 y. Results: The GRS for CRC was associated with up to 28% of the circulating metabolites at FDR-P < 0.05 across all time points, particularly with higher fatty acids and very-low- and low-density lipoprotein subclass lipids. Two-sample reverse Mendelian randomization (MR) analyses investigating CRC liability (52,775 cases, 45,940 controls) and metabolites measured in a random subset of UK Biobank participants (N = 118,466, median age 58 y) revealed broadly consistent effect estimates with the GRS analysis. In conventional (forward) MR analyses, genetically predicted polyunsaturated fatty acid concentrations were most strongly associated with higher CRC risk. Conclusions: These analyses suggest that higher genetic liability to CRC can cause early alterations in systemic metabolism and suggest that fatty acids may play an important role in CRC development. Funding: This work was supported by the Elizabeth Blackwell Institute for Health Research, University of Bristol, the Wellcome Trust, the Medical Research Council, Diabetes UK, the University of Bristol NIHR Biomedical Research Centre, and Cancer Research UK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work used the computational facilities of the Advanced Computing Research Centre, University of Bristol - http://www.bristol.ac.uk/acrc/ .

Recognizing the early signs of cancer risk is vital for informing prevention, early detection, and survival. To investigate whether changes in circulating metabolites characterise the early stages of colorectal cancer (CRC) development, we examined associations between a genetic risk score (GRS) associated with CRC liability (72 single nucleotide polymorphisms) and 231 circulating metabolites measured by nuclear magnetic resonance spectroscopy in the Avon Longitudinal Study of Parents and Children (N=6,221). Linear regression models were applied to examine associations between genetic liability to colorectal cancer and circulating metabolites measured in the same individuals at age 8, 16, 18 and 25 years. The GRS for CRC was associated with up to 28% of the circulating metabolites at FDR-P<0.05 across all time points, particularly with higher fatty acids and very-low- and low-density lipoprotein subclass lipids. Two-sample reverse Mendelian randomization (MR) analyses investigating CRC liability (52,775 cases, 45,940 controls) and metabolites measured in a random subset of UK Biobank participants (N=118,466, median age 58y) revealed broadly consistent effect estimates with the GRS analysis. In conventional (forward) MR analyses, genetically predicted polyunsaturated fatty acid concentrations were most strongly associated with higher CRC risk. These analyses suggest that higher genetic liability to CRC can cause early alterations in systemic metabolism, and suggest that fatty acids may play an important role in CRC development.

AbstractRadiation oncology is an integral part of the multidisciplinary team caring for children with cancer. The primary goal of our committee is to enable the delivery of the safest dose of radiation therapy (RT) with the maximal potential for cure, and to minimize toxicity in children by delivering lower doses to normal tissues using advanced technologies like intensity‐modulated RT (IMRT) and proton therapy. We provide mentorship for y ators and are actively involved in educating the global radiation oncology community. We are leaders in the effort to discover novel radiosensitizers, radioprotectors, and advanced RT technologies that could help improve outcomes of children with cancer.