Citations

Purpose To determine whether metabolic syndrome (MetS) is a risk factor for various forms of optic neuropathy including non-arteritic anterior ischaemic optic neuropathy (NAION). Methods This population-based analysis identified patients ≥40 years of age in Olmsted County, Minnesota, USA using the Rochester Epidemiology Project 2005–2018. Patients with MetS were identified if three or more of the five standard criteria for diagnosing MetS were present: systemic hypertension, hyperglycaemia, hypertriglyceridaemia, reduced high-density lipoprotein cholesterol (hypoalphalipoproteinaemia) and central adiposity defined by increased body mass index. Charts of patients identified as having an optic neuropathy were reviewed to record specific diagnoses and compared with patients without ocular pathology other than cataract. The odds ratio (OR) of association with MetS was calculated and adjusted for age, sex and race with multivariate analysis for the various optic neuropathies. Results Patients with MetS were more likely to have an optic neuropathy than those without (OR 2.2, p<0.001). After adjusting for age, sex and race, the only optic neuropathy found to be significantly associated with MetS was NAION (OR 6.17, p=0.002). For patients with NAION, though each individual component of MetS was individually significantly associated with MetS, further analysis suggested that hypertriglyceridaemia, hypoalphalipoproteinaemia and hyperglycaemia were likely the key drivers in the overall significance between NAION and MetS. Conclusion Patients with MetS were more likely to have NAION. Further studies are needed to determine whether MetS is a modifiable risk factor for NAION.

Objective: To examine whether body mass index (BMI) changes modify the association between kidney donation and incident hypertension. Background: Obesity increases hypertension risk in both general and living kidney donor (LKD) populations. Donation-attributable risk in the context of obesity, and whether weight change modifies that risk, is unknown. Methods: Nested case-control study among 1558 adult LKDs (1976–2020) with obesity (median follow-up: 3.6 years; interquartile range: 2.0–9.4) and 3783 adults with obesity in the Coronary Artery Risk Development in Young Adults (CARDIA) and Atherosclerosis Risk in Communities (ARIC) studies (9.2 y; interquartile range: 5.3–15.8). Hypertension incidence was compared by donor status using conditional logistic regression, with BMI change investigated for effect modification. Results: Overall, LKDs and nondonors had similar hypertension incidence [incidence rate ratio (IRR): 1.16, 95% confidence interval (95% CI): 0.94–1.43, P=0.16], even after adjusting for BMI change (IRR: 1.25, 95% CI: 0.99–1.58, P=0.05). Although LKDs and nondonors who lost >5% BMI had comparable hypertension incidence (IRR: 0.78, 95% CI: 0.46–1.34, P=0.36), there was a significant interaction between donor and >5% BMI gain (multiplicative interaction IRR: 1.62, 95% CI: 1.15–2.29, P=0.006; relative excess risk due to interaction: 0.90, 95% CI: 0.24–1.56, P=0.007), such that LKDs who gained weight had higher hypertension incidence than similar nondonors (IRR: 1.83, 95% CI: 1.32–2.53, P<0.001). Conclusions: Overall, LKDs and nondonors with obesity had similar hypertension incidence. Weight stability and loss were associated with similar hypertension incidence by donor status. However, LKDs who gained >5% saw increased hypertension incidence versus similar nondonors, providing support for counseling potential LKDs with obesity on weight management postdonation.

Abstract Background Guidelines for follow-up after locoregional breast cancer treatment recommend imaging for distant metastases only in the presence of patient signs and/or symptoms. However, guidelines have not been updated to reflect advances in imaging, systemic therapy, or the understanding of biological subtype. We assessed the association between mode of distant recurrence detection and survival. Methods In this observational study, a stage-stratified random sample of women with stage II-III breast cancer in 2006-2007 and followed through 2016 was selected, including up to 10 women from each of 1217 Commission on Cancer facilities (n = 10 076). The explanatory variable was mode of recurrence detection (asymptomatic imaging vs signs and/or symptoms). The outcome was time from initial cancer diagnosis to death. Registrars abstracted scan type, intent (cancer-related vs not, asymptomatic surveillance vs not), and recurrence. Data were merged with each patient’s National Cancer Database record. Results Surveillance imaging detected 23.3% (284 of 1220) of distant recurrences (76.7%, 936 of 1220 by signs and/or symptoms). Based on propensity-weighted multivariable Cox proportional hazards models, patients with asymptomatic imaging compared with sign and/or symptom detected recurrences had a lower risk of death if estrogen receptor (ER) and progesterone receptor (PR) negative, HER2 negative (triple negative; hazard ratio [HR] = 0.73, 95% confidence interval [CI] = 0.54 to 0.99), or HER2 positive (HR = 0.51, 95% CI = 0.33 to 0.80). No association was observed for ER- or PR-positive, HER2-negative (HR = 1.14, 95% CI = 0.91 to 1.44) cancers. Conclusions Recurrence detection by asymptomatic imaging compared with signs and/or symptoms was associated with lower risk of death for triple-negative and HER2-positive, but not ER- or PR-positive, HER2-negative cancers. A randomized trial is warranted to evaluate imaging surveillance for metastases results in these subgroups.

Abstract Gallbladder cancer (GBC) is one of the deadliest cancers, with a 5-year-survival-rate of less than 5 percent for late-stage disease. The response rate to chemotherapy among GBC patients is generally poor. Recent research has attempted to identify diagnostic, prognostic, and predictive biomarkers, however, currently, no biomarkers can accurately diagnose GBC and predict patients’ prognosis. Integrative analysis of molecular and clinical characterization has not been fully established, and minimal improvement has been made to the survival of these patients, in part due to the heterogeneity of GBC. Machine learning techniques have been proven to empower analysis of big data in oncology, allowing for improvement in the generation of biomarkers to predict patient outcomes. Using machine learning, we can utilize high-throughput RNA sequencing with clinicopathologic data to develop a predictive tool for GBC prognosis. Current predictive models for GBC outcomes often utilize clinical data only, with the highest C-statistic reported being 0.71. C-statistic values over 0.7 generally indicate good models, however 0.8 is the threshold for strong predictive models. We aim to build a superior algorithm to predict overall survival in GBC patients with advanced disease, using machine learning approaches to prioritize biomarkers for GBC prognosis. We have identified over 80 fresh frozen GBC tissue samples from Mayo Clinic Rochester, Dongsan Medical Center in Daegu, Korea, University of the Witwatersrand, in Johannesburg, South Africa, Lithuanian University of Health Science in Vilnius, Lithuania, and University of Calgary in Calgary, Canada, from patients enrolled between 2012 and 2021. We will perform next-generation RNA sequencing on these tissue samples. The patients’ clinical, pathologic and survival data will be abstracted from the medical record uniformly across sites. Feature engineering and dimensionality reduction will be performed. Then random forests, support vector machines, and gradient boosting machines will be applied to train the data. Variable importance will prioritize multi-omic markers. Standard 5-fold cross validation will be used to assess performance of each ML algorithm. If overall survival can be better predicted with the addition patients’ transcriptional sequencing data compared to using clinical profiles alone, we can gain a greater understanding of key biomarkers driving the tumor phenotype. Citation Format: Linsey Jackson, Loretta Allotey, Valles Kenneth, Gavin Oliver, Asha Nair, Daniel O'Brien, Rondell Graham, Mitesh Borad, Arjun Athreya, Lewis Roberts. Prognostic biomarkers for gallbladder cancer: A machine learning approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1944.

AbstractBackgroundUropathogen resistance, fluoroquinolone‐resistance (FQR), and extended spectrum beta‐lactamase (ESBL), has been observed to be emerging worldwide with prevalences above recommended thresholds for routine empirical treatment. The primary aim of our study was to determine the prevalence of FQR from a geographically diverse sample of United States emergency departments (EDs).MethodsWe conducted a multi‐center, observational cohort study using a network of 15 geographically diverse US EDs. All patients ≥18 years of age with the primary or secondary diagnosis of urinary tract infection (UTI) in the ED identified using International Classification of Diseases (ICD‐10) diagnosis code of cystitis, pyelonephritis, or UTI from 2018 to 2020 were included. We calculated descriptive statistics for uropathogens and susceptibilities. Logistic regression analysis was used to identify antimicrobial resistance risk factors associated with FQR Escherichia coli.ResultsAmong 3779 patients who met inclusion criteria, median age was 62.9 years (interquartile range [IQR]: 41–77.6) and 76.3% were female. The most common diagnoses were complicated (41.2%) and uncomplicated cystitis (40.3%). E. coli was the most common pathogen (63.2%), followed by Klebsiella pneumoniae (13.2%) and Enterococcus species (5.8%). Across all sites, overall E. coli FQ‐resistance prevalence was 22.1%, ranging from 10.5 to 29.7% by site. The prevalence of ESBL‐producing uropathogen was 7.4%, ranging from 3.6% to 11.6% by site. Previous IV or oral antimicrobial use in the past 90‐days and history of a multi‐drug resistant pathogen were associated with FQ‐resistant E. coli (odds ratio [OR] 2.68, 95% confidence interval [CI]: 2.04–3.51, and OR 6.93, 95% CI: 4.95–9.70, respectively). Of the patients who had FQ‐resistant E. coli or an ESBL‐producing uropathogen isolated, 116 (37.1%) and 61 (36.7%) did not have any documented risk factors for resistance.ConclusionFQ‐resistant E. coli is widely prevalent across US sites highlighting the need for ongoing monitoring of antimicrobial resistance and, at some locations, modification of empirical treatments.

SummaryThe phase I/II AU‐003 study in patients with treatment‐naïve (TN) or relapsed/refractory (R/R) chronic lymphocytic leukaemia/small lymphocytic lymphoma demonstrated that zanubrutinib therapy results in clinically meaningful and durable responses with acceptable safety and tolerability. We report updated safety and efficacy data for 123 patients with a median follow‐up of 47·2 months. Patients received zanubrutinib 160 mg twice daily (81 patients), 320 mg once daily (40), or 160 mg once daily (two). Discontinuations due to adverse events or disease progression were uncommon. The overall response rate (ORR) was 95·9% (TN, 100%; R/R, 95%) with 18·7% achieving complete response (CR). Ongoing response at 3 years was reported in 85·7%. The ORR in patients with del(17p)/tumour protein p53 mutation was 87·5% (CR 16·7%). The 2‐ and 3‐year progression‐free survival estimates were 90% (TN, 90%; R/R, 91%) and 83% (TN, 81%; R/R, 83%) respectively. The most reported Grade ≥3 adverse events were neutropenia (15·4%), pneumonia (9·8%), hypertension (8·9%) and anaemia (6·5%). The annual incidence of atrial fibrillation, major haemorrhage, Grade ≥3 neutropenia and Grade ≥3 infection decreased over time. With a median follow‐up of ~4 years, responses remain clinically meaningful and durable and long‐term tolerability to zanubrutinib therapy continues.

Précis: For patients with glaucoma, metabolic syndrome was associated with higher intraocular pressure and greater central corneal thickness. Patients with metabolic syndrome were more likely to have ocular hypertension. Purpose: The purpose of this study was to determine whether glaucomatous optic neuropathy, also known as glaucoma, and ocular hypertension are more likely to occur in patients with metabolic syndrome. Patients and Methods: Patients in Olmsted County, MN, were identified as having metabolic syndrome based on diagnosis codes, laboratory values, and/or medication use to meet 3 or more of the 5 standard criteria for diagnosing metabolic syndrome: systemic hypertension, hyperglycemia, hypertriglyceridemia, reduced high-density lipoprotein cholesterol, and central adiposity defined by increased body mass index. Patients with glaucoma, including primary open angle, low tension, pigment dispersion, and pseudoexfoliation, were identified using diagnostic codes. The charts of patients with glaucoma were individually reviewed to collect visual acuity, intraocular pressure, cup to disc ratio, central corneal thickness, visual field mean deviation, retinal nerve fiber layer thickness, and treatment of intraocular pressure. Patients with ocular hypertension were separately identified and similarly evaluated. Results: For patients with glaucoma, those with metabolic syndrome had higher intraocular pressure and greater central corneal thickness compared with those without metabolic syndrome. After adjustment for central corneal thickness, there was no longer a significant difference in intraocular pressure between groups. Metabolic syndrome was also associated with the diagnosis of ocular hypertension, and although central corneal thickness trended higher in patients with metabolic syndrome, it did not attain statistical significance. Conclusion: In Olmsted County, though metabolic syndrome was associated with ocular hypertension and higher intraocular pressure in patients with glaucoma, the results were likely related to a thicker central corneal in this patient population.