MP77-14 OUTCOMES OF MRI-US FUSION TARGETED PROSTATE BIOPSY IN MEN WITHOUT HISTORY OF PREVIOUS BIOPSY: REDUCTION OF OVER-DETECTION AND IMPROVED RISK STRATIFICATION.

Abstract Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): Siemens Healthineers Introduction Coronary CT angiography (CCTA) plays an increasing role in the detection and risk stratification of patients with coronary artery disease (CAD). The Coronary Artery Disease – Reporting and Data System (CAD-RADS) allows for standardized classification of CCTA results and, thus, may improve patient management. Purpose Aim of this study was to assess the impact of CCTA in combination with CAD-RADS on patient management and to identify the impact of cardiovascular risk factors (CVRF) on CAD severity. Methods CCTA was performed on a third-generation dual-source CT scanner in patients, who were referred to a radiology centre by their attending physicians. In a total of 4801 patients, CVRF were derived from medical reports and anamnesis. Results The study population consisted of 4770 patients (62.0 (54.0-69.0) years, 2841 males) with CAD (CAD-RADS 1-5), while 31 patients showed no CAD and were excluded from further analyses. Age, male gender and the number of CVRF were associated with more severe CAD stages (all p < 0.001). 3040 patients (63.7 %) showed minimal or mild CAD requiring optimization of CVRF i.e. medical therapy but no further assessment at his time. A group of 266 patients (5.6 %) had a severe CAD defined as CAD-RADS 4B/5. In the multivariate regression analysis, age, male gender, history of smoking, diabetes mellitus and hyperlipidaemia were significant predictors for severe CAD, whereas arterial hypertension and family history of CAD did not reach significance. Of note, a subgroup of 28 patients (10.5 %) with a severe CAD (68.5 (65.5-70.0) years, 26 males, both p = n.s.) had no CVRF. Conclusions CCTA in combination with the CAD-RADS allowed for effective risk stratification of CAD patients. The majority of the patients showed non-obstructive CAD and, thus, could be treated conservatively without the need for further CAD assessment. CVRF out of arterial hypertension and family history had an impact on CAD severity reflected in higher CAD-RADs gradings. Of note, a relevant fraction of patients with CAD did not have any CVRF and, thus, may not be covered by risk stratification models. CAD-RADS n Age (years) Males (%) 1 1453 56.0 (50.0-62.0) 623 (42.9 %) 2 1587 62.0 (55.0-69.0) 918 (57.8 %) 3 1067 66.0 (59.0-71.0) 749 (70.2 %) 4A 397 66.0 (59.0-72.0) 317 (79.8 %) 4B 162 67.0 (61.0-74.0) 139 (85.8 %) 5 104 66.0 (58.5.0-77.0) 95 (91.3 %)

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Novel SCN5A p.Val1667Asp Missense Variant Segregation and Characterization in a Family with Severe Brugada Syndrome and Multiple Sudden Deaths

International Journal of Molecular Sciences ◽

10.3390/ijms22094700 ◽

2021 ◽

Vol 22 (9) ◽

pp. 4700

Author(s):

Michelle M. Monasky ◽

Emanuele Micaglio ◽

Giuseppe Ciconte ◽

Ilaria Rivolta ◽

Valeria Borrelli ◽

...

Keyword(s):

Genetic Testing ◽

Family History ◽

Risk Stratification ◽

Brugada Syndrome ◽

Electrophysiological Study ◽

Functional Characterization ◽

The Family ◽

Novel Variant ◽

History Of ◽

Scn5a Gene

Genetic testing in Brugada syndrome (BrS) is still not considered to be useful for clinical management of patients in the majority of cases, due to the current lack of understanding about the effect of specific variants. Additionally, family history of sudden death is generally not considered useful for arrhythmic risk stratification. We sought to demonstrate the usefulness of genetic testing and family history in diagnosis and risk stratification. The family history was collected for a proband who presented with a personal history of aborted cardiac arrest and in whom a novel variant in the SCN5A gene was found. Living family members underwent ajmaline testing, electrophysiological study, and genetic testing to determine genotype-phenotype segregation, if any. Patch-clamp experiments on transfected human embryonic kidney 293 cells enabled the functional characterization of the SCN5A novel variant in vitro. In this study, we provide crucial human data on the novel heterozygous variant NM_198056.2:c.5000T>A (p.Val1667Asp) in the SCN5A gene, and demonstrate its segregation with a severe form of BrS and multiple sudden deaths. Functional data revealed a loss of function of the protein affected by the variant. These results provide the first disease association with this variant and demonstrate the usefulness of genetic testing for diagnosis and risk stratification in certain patients. This study also demonstrates the usefulness of collecting the family history, which can assist in understanding the severity of the disease in certain situations and confirm the importance of the functional studies to distinguish between pathogenic mutations and harmless genetic variants.

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Risk stratification in men with a negative prostate biopsy: An interim analysis of a prospective cohort study

BJU International ◽

10.1111/bju.15443 ◽

2021 ◽

Author(s):

Mads Sandahl ◽

Bodil Ginnerup Pedersen ◽

Benedicte Parm Ulhøi ◽

Michael Borre ◽

Karina Dalsgaard Sørensen

Keyword(s):

Cohort Study ◽

Risk Stratification ◽

Prospective Cohort Study ◽

Prostate Biopsy ◽

Prospective Cohort ◽

Interim Analysis ◽

Negative Prostate Biopsy

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Do the pain scores during prostate biopsy change in patients with a prior history of prostate biopsy?

European Urology Supplements ◽

10.1016/s1569-9056(16)15014-6 ◽

2016 ◽

Vol 15 (5) ◽

pp. e1183

Author(s):

D. Bolat ◽

M.E. Aydin ◽

B. Gunlusoy ◽

T. Degirmenci ◽

Y.K. Topcu ◽

...

Keyword(s):

Prostate Biopsy ◽

Prior History ◽

Pain Scores ◽

History Of

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Natural History of Wild-Type Transthyretin Cardiac Amyloidosis and Risk Stratification Using a Novel Staging System

Journal of the American College of Cardiology ◽

10.1016/j.jacc.2016.06.033 ◽

2016 ◽

Vol 68 (10) ◽

pp. 1014-1020 ◽

Cited By ~ 171

Author(s):

Martha Grogan ◽

Christopher G. Scott ◽

Robert A. Kyle ◽

Steven R. Zeldenrust ◽

Morie A. Gertz ◽

...

Keyword(s):

Natural History ◽

Risk Stratification ◽

Cardiac Amyloidosis ◽

Staging System ◽

Wild Type ◽

History Of

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Abstract P019: A Single Model For Predicting Major Adverse Cardiovascular Events In Individuals With And Without History Of Atherosclerotic Cardiovascular Disease: The Atherosclerosis Risk In Communities (aric) Study

Circulation ◽

10.1161/circ.143.suppl_1.p019 ◽

2021 ◽

Vol 143 (Suppl_1) ◽

Author(s):

Yejin Mok ◽

Lena Mathews ◽

Ron C Hoogeveen ◽

Michael J Blaha ◽

Christie M Ballantyne ◽

...

Keyword(s):

Myocardial Infarction ◽

Cardiovascular Disease ◽

High Risk ◽

Risk Stratification ◽

Cardiovascular Events ◽

Major Adverse Cardiovascular Events ◽

Atherosclerotic Cardiovascular Disease ◽

Single Model ◽

History Of ◽

Very High

Background: In the 2018 AHA/ACC Cholesterol guideline, risk stratification is an essential element. The use of a Pooled Cohort Equation (PCE) is recommended for individuals without atherosclerotic cardiovascular disease (ASCVD), and the new dichotomous classification of very high-risk vs. high-risk has been introduced for patients with ASCVD. These distinct risk stratification systems mainly rely on traditional risk factors, raising the possibility that a single model can predict major adverse cardiovascular events (MACEs) in persons with and without ASCVD. Methods: We studied 11,335 ARIC participants with (n=885) and without (n=10,450) a history of ASCVD (myocardial infarction, ischemic stroke, and symptomatic peripheral artery disease) at baseline (1996-98). We modeled factors in the PCE and the new classification for ASCVD patients (Figure legend) in a single CVD prediction model. We examined their associations with MACEs (myocardial infarction, stroke, and heart failure) using Cox models and evaluated the discrimination and calibration for a single model including those factors. Results: During a median follow-up of 18.4 years, there were 3,658 MACEs (3,105 in participants without ASCVD). In general, the factors in the PCE and the risk classification system for ASCVD patients were associated similarly with MACEs regardless of baseline ASCVD status, although age and systolic blood pressure showed significant interactions. A single model with these predictors and the relevant interaction terms showed good calibration and discrimination for those with and without ASCVD (c-statistic=0.729 and 0.704, respectively) (Figure). Conclusion: A single CVD prediction model performed well in persons with and without ASCVD. This approach will provide a specific predicted risk to ASCVD patients (instead of dichotomy of very high vs. high risk) and eliminate a practice gap between primary vs. secondary prevention due to different risk prediction tools.

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Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools

BMC Medical Research Methodology ◽

10.1186/s12874-019-0839-0 ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Johanna Tolksdorf ◽

Michael W. Kattan ◽

Stephen A. Boorjian ◽

Stephen J. Freedland ◽

Karim Saba ◽

...

Keyword(s):

Prostate Cancer ◽

Risk Factors ◽

Family History ◽

Cancer Risk ◽

Risk Prediction ◽

Prostate Biopsy ◽

Prostate Cancer Risk ◽

High Grade ◽

Prediction Tools ◽

History Of

Abstract Background Online clinical risk prediction tools built on data from multiple cohorts are increasingly being utilized for contemporary doctor-patient decision-making and validation. This report outlines a comprehensive data science strategy for building such tools with application to the Prostate Biopsy Collaborative Group prostate cancer risk prediction tool. Methods We created models for high-grade prostate cancer risk using six established risk factors. The data comprised 8492 prostate biopsies collected from ten institutions, 2 in Europe and 8 across North America. We calculated area under the receiver operating characteristic curve (AUC) for discrimination, the Hosmer-Lemeshow test statistic (HLS) for calibration and the clinical net benefit at risk threshold 15%. We implemented several internal cross-validation schemes to assess the influence of modeling method and individual cohort on validation performance. Results High-grade disease prevalence ranged from 18% in Zurich (1863 biopsies) to 39% in UT Health San Antonio (899 biopsies). Visualization revealed outliers in terms of risk factors, including San Juan VA (51% abnormal digital rectal exam), Durham VA (63% African American), and Zurich (2.8% family history). Exclusion of any cohort did not significantly affect the AUC or HLS, nor did the choice of prediction model (pooled, random-effects, meta-analysis). Excluding the lowest-prevalence Zurich cohort from training sets did not statistically significantly change the validation metrics for any of the individual cohorts, except for Sunnybrook, where the effect on the AUC was minimal. Therefore the final multivariable logistic model was built by pooling the data from all cohorts using logistic regression. Higher prostate-specific antigen and age, abnormal digital rectal exam, African ancestry and a family history of prostate cancer increased risk of high-grade prostate cancer, while a history of a prior negative prostate biopsy decreased risk (all p-values < 0.004). Conclusions We have outlined a multi-cohort model-building internal validation strategy for developing globally accessible and scalable risk prediction tools.

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