Individual Risk Stratification Research Articles

The association of cardiac troponin and cardiovascular events in patients with concomitant heart failure preserved ejection fraction and atrial fibrillation

BackgroundLimited data are available for risk stratification in patients with atrial fibrillation (AF) and combined heart failure with preserved ejection fraction (HFpEF). We aimed to explore the prognostic utility of high-sensitivity cardiac troponin I (hs-cTnI) in patients with newly detected AF and concomitant HFpEF.MethodsFrom August 2014 to December 2016, 2,361 patients with newly detected AF were polled in a retrospective single-center registry. Of which, 634 patients were eligible for HFpEF diagnosis (HFA-PEFF score ≥ 5) and 165 patients were excluded with exclusion criteria. Finally, 469 patients are classified into elevated or non-elevated hs-cTnI groups based on the 99th percentile upper reference limit (URL). The primary outcome was the incidence of major adverse cardiac and cerebrovascular events (MACCE) during follow-up.ResultsIn 469 patients, 295 were stratified into the non-elevated hs-cTnI group (< 99th percentile URL of hs-cTnI) and 174 were placed in the elevated hs-cTnI group (≥ 99th percentile URL of hs-cTnI). The median follow-up period was 24.2 (interquartile range, 7.5–38.6) months. During the follow-up period, 106 patients (22.6%) in the study population experienced MACCE. In a multivariable Cox regression model, the elevated hs-cTnI group had a higher incidence of MACCE (adjusted hazard ratio [HR], 1.54; 95% confidence interval [CI], 1.08–2.55; p = 0.03) and coronary revascularization-caused readmission (adjusted HR, 3.86; 95% CI, 1.39–15.09; p = 0.02) compared with the non-elevated hs-cTnI group. The incidence of heart failure-caused readmission tended to occur more frequently in the elevated hs-cTnI group (8.5% versus 15.5%; adjusted HR, 1.52; 95% CI, 0.86–2.67; p = 0.08).ConclusionsOne-fifth of patients with AF and concomitant HFpEF experienced MACCE during follow-up, and elevated hs-cTnI was independently associated with higher risk of MACCE, as driven by heart failure and revascularization-caused readmission. This finding suggested that hs-cTnI may be a useful tool in individualized risk stratification of future cardiovascular events in patients with AF and concomitant HFpEF.

Morphology-Voltage-P-wave-duration (MVP) score to select patients for continuous atrial fibrillation screening to prevent stroke

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): The LOOP Study was funded by Innovation Fund Denmark [grant number 12-1352259], The Research Foundation for the Capital Region of Denmark, The Danish Heart Foundation [grant number 11-04-R83-A3363-22625], Aalborg University Talent Management Program, Arvid Nilssons Fond, Skibsreder Per Henriksen, R og Hustrus Fond, the European Union’s Horizon 2020 program [grant number 847770], Læge Sophus Carl Emil Friis og hustru Olga Doris Friis’ Legat, and an unrestricted grant from Medtronic. Background It is well known that atrial fibrillation (AF) confers a substantially increased risk of ischemic stroke, but data on health benefits from AF screening are scarce. The newly proposed MVP risk score combining the duration, voltage and morphology of P-wave has been demonstrated to be predictive of AF and might therefore also be useful in risk-stratifying individuals for AF screening and subsequent treatment. Purpose The present study sought to examine MVP risk score and its P-wave components for prediction of AF screening effects. Methods The LOOP Study randomized AF-naïve individuals aged 70-90 years with additional stroke risk factors to either continuous AF screening with implantable loop recorder (ILR) and subsequent anticoagulation initiation upon detection of AF episode ≥6 minutes, or usual care. In this secondary analysis, the LOOP participants with a baseline 12-lead electrocardiogram (ECG) suitable for P-wave measurement were included. Results Of 5759 participants included, 265 (4.6%) had had ischemic stroke during follow-up: 213 (4.9%) of 4311 in the control group versus 64 (3.6%) of 1448 in the ILR group. Among the participants in the control group, a significantly increased risk of ischemic stroke was observed for MVP score 5-6 versus score 0-2 (hazard ratio (HR) 1.66 [95% confidence interval (CI): 1.01-2.75]) and for the presence of interatrial block (IAB) versus no IAB (HR 1.85 [95% CI: 1.19-2.86]), whereas a P-wave voltage in lead I (PWVI) &amp;lt;100 µV was associated with risk reduction compared to higher voltage (HR 0.65 [95% CI: 0.45-0.93]). Further spline analysis revealed longer P-wave duration (PWD) to also be correlated with higher stroke risk (HR 1.49 [95% CI: 1.11-2.00] for &amp;gt;110 versus ≤110 ms). Compared with usual care, ILR screening did not significantly reduce the stroke risk regardless of MVP risk score, PWD, PWVI, or IAB pattern at baseline. Conclusions In an elderly population with additional stroke risk factors, both the P-wave parameters and the combined MVP risk score based on 12-lead ECG were associated with ischemic stroke, but these did not successfully demonstrate an association with effects of AF screening on stroke prevention.

IgA nephropathy: a review of existing and emerging therapies.

IgA nephropathy (IgAN) is the most common form of primary glomerulonephritis worldwide. Recently, there have been multiple advances in the understanding of IgAN pathophysiology and therapeutic options. Despite the advent of new treatment options, individual risk stratification of the disease course and choosing the best treatment strategy for the patient remains challenging. A multitude of clinical trials is ongoing, opening multiple opportunities for enrollment. In this brief review we discuss the current approach to the management of IgAN and highlight the ongoing clinical trials.

The Role of Triglyceride-Glucose Index in the Prediction of the Development of Hypertension - Findings from a Community Cohort in Singapore.

Triglyceride-glucose index (TyGI) is an emerging surrogate marker of insulin resistance. We aim to explore the role of triglyceride-glucose index in the prediction of the development of hypertension. We conducted a retrospective cohort study that included 3,183 study participants identified from a community health screening programme who had no baseline hypertension and were then followed up after an average of 1.7 years. Cox proportional-hazard model was used to assess the association between risk of incident hypertension and TyGI in quartiles, while adjusting for demographics and clinical characteristics. Hypertension occurred in 363 study participants (11.4%). Those who developed hypertension had higher TyGI [8.6 (IQR 8.2-9.0)] than those who did not [8.2 (IQR 8.0-8.7)] (p<0.001). Significant association between TyGI and hypertension was observed in both the unadjusted and proportional hazard model [Quartile (Q)2, p=0.010; Q3, p<0.001 and Q4, p<0.001] and the model that adjusted for demographics (Q2, p=0.016; Q3, p=0.003; Q4, p<0.001). In the model adjusted for clinical covariates, the hazard of developing hypertension remained higher in TyGI Q4 compared to TyGI Q1(Hazard Ratio=2.57; 95% Confidence Interval: 1.71, 3.87). Increasing triglyceride-glucose index accounted for 16.4% of the association between increasing BMI and incident hypertension, after adjusting for age, gender, ethnicity and baseline HDL cholesterol (p<0.001). Triglyceride-glucose index was an independent predictor of the development of hypertension. It may potentially be used as an inexpensive indicator to predict the development of hypertension and risk-stratify individuals to aid management in clinical practice.

Analysis of Plasma Metabolic Profile on Ganglion Cell–Inner Plexiform Layer Thickness With Mortality and Common Diseases

The neural retina is considered a unique window to systemic health, but its biological link with systemic health remains unknown. To investigate the independent associations of retinal ganglion cell-inner plexiform layer thickness (GCIPLT) metabolic profiles with rates of mortality and morbidity of common diseases. This cohort study evaluated UK Biobank participants enrolled between 2006 and 2010, and prospectively followed them up for multidisease diagnosis and mortality. Additional participants from the Guangzhou Diabetes Eye Study (GDES) underwent optical coherence tomography scanning and metabolomic profiling and were included for validation. Systematic analysis of circulating plasma metabolites to identify GCIPLT metabolic profiles; prospective associations of these profiles with mortality and morbidity of 6 common diseases with their incremental discriminative value and clinical utility. Among 93 838 community-based participants (51 182 [54.5%] women), the mean (SD) age was 56.7 (8.1) years and mean (SD) follow-up was 12.3 (0.8) years. Of 249 metabolic metrics, 37 were independently associated with GCIPLT, including 8 positive and 29 negative associations, and most were associated with the rates of future mortality and common diseases. These metabolic profiles significantly improved the models for discriminating type 2 diabetes over clinical indicators (C statistic: 0.862; 95% CI, 0.852-0.872 vs clinical indicators only, 0.803; 95% CI, 0.792-0.814; P < .001), myocardial infarction (0.792; 95% CI, 0.775-0.808 vs 0.768; 95% CI, 0.751-0.786; P < .001), heart failure (0.803; 95% CI, 0.786-0.820 vs 0.790; 95% CI, 0.773-0.807; P < .001), stroke (0.739; 95% CI, 0.714-0.764 vs 0.719; 95% CI, 0.693-0.745; P < .001), all-cause mortality (0.747; 95% CI, 0.734-0.760 vs 0.724; 95% CI, 0.711-0.738; P < .001), and cardiovascular disease mortality (0.790; 95% CI, 0.767-0.812 vs 0.763; 95% CI, 0.739-0.788; P < .001). Additionally, the potential of GCIPLT metabolic profiles for risk stratification of cardiovascular diseases were further confirmed in the GDES cohort using a different metabolomic approach. In this prospective study of multinational participants, GCIPLT-associated metabolites demonstrated the potential to inform mortality and morbidity risks. Incorporating information on these profiles may facilitate individualized risk stratification for these health outcomes.

Nomograms referenced by cardiac magnetic resonance in the prediction of cardiac injuries in patients with ST-elevation myocardial infarction

BackgroundEvaluation of cardiac injuries is essential in patients with ST-elevation myocardial infarction (STEMI). Cardiac magnetic resonance (CMR) has become the gold standard for quantifying cardiac injuries; however, its routine application is limited. A nomogram is a useful tool for prognostic prediction based on the comprehensive utilization of clinical data. We presumed that the nomogram models established using CMR as a reference could precisely predict cardiac injuries. MethodsThis analysis included 584 patients with acute STEMI from a CMR registry study for STEMI (NCT03768453). The patients were divided into training (n = 408) and testing (n = 176) datasets. The least absolute shrinkage and selection operator method and multivariate logistic regression were used to construct nomograms for predicting left ventricular ejection fraction (LVEF) ≤40%, infarction size (IS) ≥ 20% on the LV mass, and microvascular dysfunction. ResultsThe nomogram for predicting LVEF≤40%, IS≥20%, and microvascular dysfunction comprised 14, 10, and 15 predictors, respectively. With the nomograms, the individual risk probability of developing specific outcomes could be calculated, and the weight of each risk factor was demonstrated. The C-index of the nomograms in the training dataset were 0.901, 0.831, and 0.814, respectively, and were comparable in the testing set, showing good nomogram discrimination and calibration. The decision curve analysis demonstrated good clinical effectiveness. Online calculators were also constructed. ConclusionsWith the CMR results as the reference standard, the established nomograms demonstrated good effectiveness in predicting cardiac injuries after STEMI and could provide physicians with a new option for individual risk stratification.

Risk factors associated with safety of preschool peanut oral immunotherapy.

An understanding of how patient characteristics such as age, baseline peanut-specific IgE, and atopic comorbidities may influence potential safety outcomes during peanut oral immunotherapy (P-OIT) could aid in shared decision making between clinicians and patient families. This study explored the relationship between baseline patient characteristics and reactions during P-OIT using a large sample size to better understand potential risk factors influencing P-OIT safety. Data were obtained from the Food Allergy Immunotherapy (FAIT) registry, which collects real-world OIT data from community and academic allergy clinics across Canada. Multivariable logistic regression modeling was performed to examine the relationship between baseline patient characteristics and reactions during P-OIT. Multiple imputation was applied to reduce potential bias caused by missingness and to maximize the use of available information to preserve statistical power. Between April 2017 and June 2021, a total of 653 eligible patients initiated P-OIT. Multivariable regression analysis showed pre-OIT grade 2+ initial reaction (odds ratio [OR]= 1.33, 95% confidence interval [CI] 1.10, 1.61), allergic rhinitis (OR= 1.60, 95% CI 1.08, 2.38), older age (OR= 1.01, 95% CI 1.00, 1.02), and higher baseline peanut-specific IgE (OR= 1.02, 95% CI 1.02, 1.03) were associated with grade 2+ reaction during P-OIT after adjusting for potential risk factors. Our study identified several clinically important risk factors for grade 2+ reactions during P-OIT: pre-OIT grade 2+ initial reaction, allergic rhinitis, older age, and higher baseline peanut-specific IgE. These results highlight the need for individualized risk stratification for OIT.

Asymptomatic channelopathies : Risk stratification and primary prophylaxis

In general, asymptomatic patients with channelopathies are at increased risk of sudden cardiac death (SCD), due to pathogenic variants in genes encoding ion channels that result in pathological ion currents. Channelopathies include long-QT syndrome (LQTS), Brugada syndrome (BrS), catecholaminergic polymorphic ventricular tachycardia (CPVT), and short-QT syndrome (SQTS). In addition to the patient's clinical presentation, history and clinical tests, the main diagnostic tools are electrocardiography and genetic testing to identify known gene mutations. Early and correct diagnosis as well as further risk stratification of affected individuals and their relatives are paramount for prognosis. The recent availability of risk score calculators for LQTS and BrS allows SCD risk to be accurately estimated. The extent to which these improve patient selection for treatment with an implantable cardioverter-defibrillator (ICD) system is currently unknown. In most cases, initiation of basic therapy in asymptomatic patients in the form of avoidance of triggers, which are usually medication or stressful situations, is sufficient and contributes to risk reduction. In addition, there are other risk-reducing prophylactic measures, such as permanent medication with nonselective β‑ blockers (for LQTS and CPVT) or mexiletine for LQTS3. Patients and their family members should be referred to specialized outpatient clinics for individual risk stratification in the sense of primary prophylaxis.

Risk factors for recurrent disease in small papillary thyroid cancers – a Swedish register-based study

AimsTo study the correlation between clinicopathological risk factors and the risk for intervention-requiring cancer recurrence in patients with small papillary thyroid cancers (sPTCs).Materials and methodsRecords for 397 patients with sPTC (T1 ≤ 20mm) were obtained from the Scandinavian Quality Register for Thyroid, Parathyroid and Adrenal Surgery (SQRTPA) between 2010 and 2016. Follow-up time was at least 5 years. Data regarding intervention-requiring cancer recurrence were obtained from patient medical records and analysed regarding lymph node (LN) status (N0, N1a and N1b) and recurrence.ResultsAge was significantly lower in the N1a and N1b groups compared to N0 (45 vs. 40.5 vs. 49 years, respectively; p = 0.002). Tumour size was smaller in the N1a group compared to N1b group (9 vs. 11.8 mm; p <0.01). The mean number of metastatic LNs at initial surgery was higher in the N1b compared to N1a group (6.6 vs. 3; p = 0.001), and in the recurrent compared to the non-recurrent group (7 versus 3.9; p <0.01). The recurrence rate was higher in the N1b group than the N1a and N0 groups (25% vs. 2.4% vs. 1.4%, respectively; p = 0.001).ConclusionsLymph node stage N1b at diagnosis, and having five or more metastatic nodes, are strong risk factors for cancer recurrence and decreased disease-free survival in sPTC. The management of patients with sPTC should include thorough lymph node mapping for optimal treatment and individual risk stratification.

Progressive Multifocal Leukoencephalopathy (PML) With Anti-CD20 and Other Monoclonal Antibody (mAb) Therapies in Multiple Sclerosis (P8-3.016)

<h3>Objective:</h3> To review the incidence of progressive multifocal leukoencephalopathy (PML) associated with monoclonal antibody (mAb) therapies, specifically anti-CD20 medications used in multiple sclerosis (MS). <h3>Background:</h3> PML is an opportunistic and fatal inflammatory disease of the central nervous system, which occurs almost exclusively in immunocompromised hosts; therefore, patients receiving mAb immunotherapy become an at-risk population. B cell-depleting mAbs targeting CD20+ cells have become widely used in MS. Although their efficacy is well-known, their associated risk of PML, especially among those without previous disease-modifying therapy (DMT) exposure, has been insufficiently studied. <h3>Design/Methods:</h3> A systematic literature review of PubMed, Google Scholar, EMBASE, and Scopus was conducted by two independent researchers from June 1, 1997, to July 10, 2022. Further data was obtained from the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database and individual pharmaceutical companies (Genentech, Novartis, and TG Therapeutics). Carryover cases from prior exposure to other immunosuppressants were excluded. <h3>Results:</h3> Between 2015 and 2017, 10 cases of PML were reported in the FAERS database among 334 MS patients taking rituximab; two had previously received natalizumab, leaving eight cases in total. Rituximab-associated PML was also seen in lymphoproliferative disorders (n=52), rheumatoid arthritis (n=9), and granulomatosis with polyangiitis (n=2). Two fatal PML cases were found in MS patients taking ocrelizumab. No cases of PML were reported with ofatumumab in MS; however, 5 cases were reported in chronic lymphocytic leukemia. PML has not been observed with ublituximab, which is currently under FDA review. Among other DMTs, PML was frequently reported with natalizumab (n=884), fingolimod (n=30), dimethyl fumarate (n=12), and alemtuzumab (n=1). <h3>Conclusions:</h3> Anti-CD20 therapies are a safe class of medications with a low infectious risk for PML, especially compared to other mAbs used in MS, such as natalizumab. Nonetheless, risk stratification in susceptible individuals, as done with natalizumab, could prove beneficial with all mAb treatments. <b>Disclosure:</b> Dr. Sharma has nothing to disclose. Dr. Srivastava has nothing to disclose. Dr. JENA has nothing to disclose. Dr. Kakara has nothing to disclose. Dr. Sriwastava has nothing to disclose. Maha Daimee has nothing to disclose. Dr. Xu has nothing to disclose.

Polygenic score: An anchor holding the whole life course.

Polygenic score: An anchor holding the whole life course.

Abstract 5453: Individualized risk stratification in newly diagnosed multiple myeloma

Abstract Background: Clinical outcomes for newly diagnosed multiple myeloma (NDMM) patients are heterogenous with survival ranging from months to &amp;gt; 10 years. Though several clinical and genomic features predict outcomes, the “one-size-fits-all” treatment paradigm remains dominant for NDMM. Hypothesis: By integrating clinical, genomic and therapeutic data, using artificial intelligence, an individualized risk-prediction model for NDMM (IRM) can facilitate individually-tailored therapeutic decisions. Methods: We included 1933 patients with clinical and genomic data from 5 cohorts: MMRF CoMMpass (n=1062), MGP (n=492), Moffit AVATAR (n=177), UAMS (n=93), and MSKCC (n=109). The median follow-up was 43 months. Overall, we considered 160 clinical (e.g., age, ECOG, race), therapeutics, and genomic variables. To correct for time-dependent variables such as autologous stem cell transplant (ASCT) and continuous treatment, a multi-state model was designed across two phases: induction (phase 1), and post-induction (phase 2). Neural Cox Non-proportional-hazards (NCNPH) was used to integrate the data and build the model. Results: Overall, the 5-year overall survival (OS) c-index for IRM was 0.73, significantly higher than all existing prognostic models: R2-ISS (0.62), ISS (0.61) and R-ISS (0.56). The overall model accuracy was significantly improved by the inclusion of 12 genomic features, including 1q21 gain/amp, TP53 loss, t(4;14)(NSD2;IGH), complex copy number signatures, APOBEC mutational signature contribution, and del1p. Prescribed therapy emerged as a key determinant of risk, suggesting that effective combinations may have a different impact in the context of individual patient features, with the potential to significantly change clinical outcomes despite poor historical prognostication (i.e., treatment variance). Leveraging these concepts, we interrogated the clinical impact of ASCT and continuous treatment in the context of NDMM treated with bortezomib, lenalidomide and dexamethasone (VRd). Integrating predicted outcomes and treatment variance for all 4 possible treatment combinations (i.e., VRd +/- ASCT +/- continuous treatment) we identified 3 patient groups. In the first group (n=632), patients were characterized by complex genomic features, older age, high ISS, poor outcomes and limited treatment variance, reflecting aggressive and refractory myeloma. The second group (n=571) was characterized by high treatment variance, with favorable outcomes if ASCT and continuous treatment are provided. The last group (n=730) included patients with favorable clinical and genomic profiles, achieving good outcomes, with minimal advantage from ASCT. Conclusion: Integrating historical and emerging genomic features with clinical and therapeutic data, we developed the first individualized risk-prediction model for personally-tailored therapeutic decisions in NDMM. Citation Format: Arjun Raj Rajanna, Francesco Maura, Andriy Derkach, Bachisio Ziccheddu, Niels Weinhold, Kylee Maclachlan, Benjamin Diamond, Faith Davies, Eileen Boyle, Brian Walker, Alexandra Pos, Malin Hulcrantz, Ariosto Silva, Oliver Hampton, Jamie K. Teer, Niccolò Bolli, Graham Jackson, Martin Kaiser, Charlotte Pawlyn, Gordon Cook, Dennis Verducci, Dickran Kazandjian, Fritz Van Rhee, Saad Usmani, Kenneth H. Shain, Marc S. Raab, Gareth Morgan, Ola Landgren. Individualized risk stratification in newly diagnosed multiple myeloma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5453.

Abstract 4321: Clinical-grade early detection of esophageal cancer on data from a non-endoscopic device using deep learning

Abstract Aim: Our goal was to evaluate a novel deep learning system for integrated human-AI review of whole-slide images (WSIs) from the Cytosponge to predict progression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC). Background: Fewer than 1% of BE patients advance to EAC, therefore delineating the patients at elevated risk is crucial for prioritizing their surveillance and treatment. Previous work has shown that the Cytosponge, a non-endoscopic test, coupled with biomarkers (TFF3, atypia, p53) can be used to identify and risk-stratify individuals with BE. However, the Cytosponge workflow to date has required a time consuming pathology review. Methods: We collected 1,700 BE Cytosponge WSIs from over 800 patients. We hand-drew over 30,000 digital annotations on the WSIs, a 300-hour collaborative effort between a computer scientist and 4 pathologists. Using these data for training, validation, and testing, we developed a deep learning system to determine whether cellular atypia and/or p53 overexpression is present. We used this system in a machine-assisted (MA) review process to highlight the most diagnostically interesting regions of WSIs for pathologist review. In our proposed system, patients are automatically triaged into high or low confidence positive, and high confidence negative classes for both atypia and p53 status, and only low confidence cases are sent for MA review. Results: Out of 23 architectures, the best atypia model achieves an accuracy of 0.90, and the best p53 model 0.96. The model was concordant with pathologists in 342/425 (80.5%) validation and 301/330 (91.2%) test-set patients. The system also identified 83 validation cases with atypia and/or p53 that were not previously reported by the pathologists. Of these, 29 (35%) were confirmed abnormal with the ground truth endoscopy biopsies (11 high grade dysplasia or intramucosal carcinoma, 14 low grade dysplasia, 5 indefinite for dysplasia). In the test set 29 results were discordant with pathology including 6 (21%) confirmed abnormal on endoscopy biopsies (3 HGD/IMC, 2 LGD, 1 IND). We used the models’ outputs to localize where these “missed” regions lie in the WSIs, and pathologist MA review confirmed the presence of focal abnormalities (cellular atypia +/- p53 aberrance) correctly identified by the algorithm. If pathologists only review cases for which the model had low confidence, this preserves overall performance while reducing pathologist workload over twenty-fold. MA review on the remaining WSIs is 4.7 times faster than standard review for atypia screening and 16.0 times faster for p53. Conclusion: This work shows the potential of an integrated human-AI WSI review process to drastically expedite a time consuming task and improve on pathologist performance when abnormal regions are easy for human eyes to miss. This work therefore lays the groundwork for similar machine-doctor approaches in other areas of medicine. Citation Format: Adam G. Berman, Ahmad Miremadi, Maria O'Donovan, Shalini Malhotra, Monika Tripathi, Rebecca C. Fitzgerald, Florian Markowetz. Clinical-grade early detection of esophageal cancer on data from a non-endoscopic device using deep learning. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4321.

Prediction and prevention of the first episode of overt hepatic encephalopathy in patients with cirrhosis.

Hepatic encephalopathy (HE) is one of the most important complications of patients with liver cirrhosis. In addition, HE is associated with a dismal prognosis and has detrimental effects on patients' quality of life. Thus, it is of pivotal importance to identify patients at high risk for overt HE (OHE) in whom primary prophylaxis may be justified. In this narrative review, we aim to provide insight into predictors and prediction tools for a first-time episode of OHE and to scrutinize the current level of evidence of primary prophylaxis. In recent decades, several cognitive tests, composite scores, and blood-based biomarkers have been demonstrated to be predictive of a first-time episode of OHE. Among the best validated are the established tests for minimal HE, such as the Psychometric Hepatic Encephalopathy Score, determination of the critical flicker frequency, Stroop EncephalApp, or the Animal Naming Test. Individualized risk stratification using blood-based biomarkers and cross-sectional imaging (sarcopenia and spontaneous portosystemic shunts) is coming to the fore, but validation in larger multicenter cohorts is often lacking. On the basis of current evidence, a recommendation for primary prophylaxis of a first episode of OHE cannot be made in general. Only 2 studies have investigated the prevention of a first-time OHE episode as the primary endpoint. In this narrative review, we provide a concise overview of the current evidence levels on prediction tools and pharmacological prevention of a first episode of OHE. In addition, we give an outlook on future research targets to improve knowledge on this important topic.

MP55-03 CORRELATION BETWEEN PSMA PET/CT DATA AND PATHOLOGICAL TUMOUR STAGING AND GRADING OF PROSTATE CANCER

MP55-03 CORRELATION BETWEEN PSMA PET/CT DATA AND PATHOLOGICAL TUMOUR STAGING AND GRADING OF PROSTATE CANCER

Colorectal Cancer Risk Assessment and Precision Approaches to Screening: Brave New World or Worlds Apart?

Current colorectal cancer (CRC) screening recommendations take a "one-size-fits-all" approach using age as the major criterion to initiate screening. Precision screening that incorporates factors beyond age to risk stratify individuals could improve on current approaches and optimally use available resources with benefits for patients, providers, and health care systems. Prediction models could identify high-risk groups who would benefit from more intensive screening, while low-risk groups could be recommended less intensive screening incorporating noninvasive screening modalities. In addition to age, prediction models incorporate well-established risk factors such as genetics (eg, family CRC history, germline, and polygenic risk scores), lifestyle (eg, smoking, alcohol, diet, and physical inactivity), sex, and race and ethnicity among others. Although several risk prediction models have been validated, few have been systematically studied for risk-adapted population CRC screening. In order to envisage clinical implementation of precision screening in the future, it will be critical to develop reliable and accurate prediction models that apply to all individuals in a population; prospectively study risk-adapted CRC screening on the population level; garner acceptance from patients and providers; and assess feasibility, resources, cost, and cost-effectiveness of these new paradigms. This review evaluates the current state of risk prediction modeling and provides a roadmap for future implementation of precision CRC screening.

Do Dosiomic Features Extracted From Planned 3-Dimensional Dose Distribution Improve Biochemical Failure-Free Survival Prediction: an Analysis Based on a Large Multi-Institutional Data Set

The objective of this work was to investigate whether including additional dosiomic features can improve biochemical failure-free survival prediction compared with models with clinical features only or with clinical features as well as equivalent uniform dose and tumor control probability. This retrospective study included 1852 patients who received diagnoses of localized prostate cancer between 2010 and 2016 and were treated with curative external beam radiation therapy in Albert, Canada. A total of 1562 patients from 2 centers were used for developing 3 random survival forest models: Model A included only 5 clinical features; Model B included 5 clinical features, equivalent uniform dose, and tumor control probability; and Model C considered 5 clinical features and 2074 dosiomic features derived from the planned dose distribution of the clinical target volume and planning target volume with further feature selection to determine prognostic features. No feature selection was performed for models A and B. Two hundred ninety patients from another 2 centers were used for independent validation. Individual model-based risk stratification was examined, and the log-rank tests were performed to test statistically significant differences between the risk groups. The 3 models' performances were evaluated using Harrell's concordance index (C-index) and compared using one-way repeated-measures analysis of variance with post hoc paired t test. Model C selected 6 dosiomic features and 4 clinical features to be prognostic. There were statistically significant differences between the 4 risk groups for both training and validation data sets. The C-index for the out-of-bag samples of the training data set was 0.650, 0.648, and 0.669 for models A, B, and C, respectively. The C-index for the validation data set for models A, B, and C was 0.653, 0.648, and 0.662, respectively. Although gains were modest, Model C was statistically significantly better than models A and B. Dosiomics contain information beyond common dose-volume histogram metrics from planned dose distributions. Incorporation of prognostic dosiomic features in biochemical failure-free survival outcome models can lead to statistically significant although modest improvement in performance.

Nasal Construction in Congenital Arhinia Due to Novel SMCHD1 Gene Variant.

Arhinia, or congenital absence of the nose, is an exceedingly rare anomaly caused by pathogenic variants in the gene SMCHD1 . Arhinia exhibits unique reconstructive challenges, as the midface is deficient in skeletal and soft tissue structures. The authors present 2 related patients with arhinia who harbor a novel SMCHD1 gene variant and illustrate their surgical midface and nasal construction. Targeted sequencing was carried out on DNA samples from the 2 affected patients, 1 anosmic and 1 healthy parent, to identify variants in exons 3 to 13 of SMCHD1 . The affected patients and anosmic parent were found to have a novel SMCHD1 gene variant p.E473V. A staged surgical approach was applied. First, both patients underwent a LeFort II osteotomy and distraction osteogenesis to improve the projection of the midfacial segment, followed by tissue expansion of the forehead, and nasal construction with a forehead flap that was placed over a costochondral framework derived from rib cartilage. The novel gene variant could guide future investigations on genetic pathways and molecular processes that underly the physiological and pathologic development of the nose. Further investigations on the variable expressivity ranging from anosmia to arhinia could improve clinical genetic screens for risk stratification of individuals with anosmia on passing on arhinia to their children. Due to the exceptional rarity and complexity of congenital arhinia, most surgical approaches are developed on a single-case basis. This case series, albeit limited to 2 cases, is the largest pedigree of such cases in the literature. It highlights key principles of a staged approach to nasal construction in arhinia and discusses nuances and improvements learned between both patients. It subsequently offers an optimized guide to this surgical strategy.

The value of cardiopulmonary exercise testing and stress echocardiography in the prediction of all-cause mortality in adults with end-stage renal disease

ABSTRACT We aimed to assess the prognostic utility of different parameters routinely assessed from cardiopulmonary exercise testing (CPET) and exercise echocardiography in adults with end-stage renal disease (ESRD). Forty-two ESRD (37 male) individuals (age: 58 ± 13 years, height: 169.30 ± 8.30 cm, weight: 81 ± 15 kg, body surface area: 1.92 ± 0.20 m2) underwent a maximal/symptom limited CPET, with a full cross-sectional echocardiogram performed at baseline and peak exercise. All participants were prospectively followed over a 10-year period, with all-cause mortality as the primary endpoint. After the follow-up period, a total of 19 participants (45%) died. Left atrial size (4.70 ± 0.70 vs. 3.65 ± 0.50 cm, P < 0.001) and anteroseptal wall thickness (1.28 ± 0.40 vs. 1.06 ± 0.02 cm, P = 0.002) were significantly greater in those that died, while peak heart rate was significantly lower (108 ± 12 vs. 128 ± 14 bpm, P < 0.001). The prevalence of myocardial ischaemia (13 vs. 8 participants, P = 0.03) was significantly greater, while peak VO2 (9.80 ± 2.10 vs. 15.90 ± 4.30 ml·kg−1·min−1, P < 0.001) was significantly lower in those that died. Following multivariate cox regression, myocardial ischaemia (Hazard Ratio 3.08; 95% Confidence Interval 1.09–8.70; P = 0.03) and peak VO2 (HR 0.73; 95% CI 0.64–0.84; P < 0.001) were significant independent predictors of 10-year all-cause mortality. This is the first study to establish peak VO2 as powerful marker of all-cause mortality when assessed with clinical, resting and stress echocardiography parameters in people with ESRD over a 10-year follow up period. This observation indicates that, in clinical practice, CPET and exercise echocardiography may serve as valuable tools for the risk stratification of individuals with ESRD. Highlights We aimed to assess the prognostic utility of cardiopulmonary exercise testing (CPET) and exercise echocardiography in end-stage renal disease (ESRD) with 10-year mortality. Peak aerobic capacity and the presence of ischaemic heart disease were independently associated with all-cause mortality. This observation indicates that, in clinical practice, CPET and exercise echocardiography may serve as valuable tools for the risk stratification of individuals with end-stage renal disease.

Clinical risk stratification in glaucoma.

Glaucoma is the leading cause of preventable sight loss in the United Kingdom and the provision of timely glaucoma care has been highlighted as a significant challenge in recent years. Following a recent high-profile investigation, The Healthcare Safety Investigation Branch recommended the validation of risk stratification models to safeguard the vision-related quality of life of glaucoma patients. There continues to be no nationally agreed evidence-based risk stratification model for glaucoma care across the United Kingdom. Some models have used simple measures of disease staging such as visual field mean deviation as surrogates for risk, but more refined, individualised risk stratification models should include factors related to both visual impairment and visual disability. Candidate tools should also incorporate both ocular and systemic co-morbidities, rate of disease progression, visual needs and driving status and undergo clinical refinement and validation to justify implementation. The disruption to routine glaucoma care caused by the COVID-19 pandemic has only highlighted the importance of such risk stratification models and has accelerated their development, application and evaluation. This review aims to critically appraise the available evidence underpinning current approaches for glaucoma risk stratification and to discuss how these may be applied to contemporary glaucoma care within the United Kingdom. Further research will be essential to justify and validate the utility of glaucoma risk stratification models in everyday clinical practice.