scholarly journals Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors

2016 ◽  
Vol 152 (8) ◽  
pp. 889 ◽  
Author(s):  
Kylie Vuong ◽  
Bruce K. Armstrong ◽  
Elisabete Weiderpass ◽  
Eiliv Lund ◽  
Hans-Olov Adami ◽  
...  
2015 ◽  
Vol 33 (15_suppl) ◽  
pp. 1563-1563
Author(s):  
Kylie Vuong ◽  
Anne Elizabeth Cust ◽  
Bruce Konrad Armstrong ◽  
Kevin McGeechan

EP Europace ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 1400-1409 ◽  
Author(s):  
Antoine Delinière ◽  
Adrian Baranchuk ◽  
Joris Giai ◽  
Francis Bessiere ◽  
Delphine Maucort-Boulch ◽  
...  

Abstract Aims There is currently no reliable tool to quantify the risks of ventricular fibrillation or sudden cardiac arrest (VF/SCA) in patients with spontaneous Brugada type 1 pattern (BrT1). Previous studies showed that electrocardiographic (ECG) markers of depolarization or repolarization disorders might indicate elevated risk. We aimed to design a VF/SCA risk prediction model based on ECG analyses for adult patients with spontaneous BrT1. Methods and results This retrospective multicentre international study analysed ECG data from 115 patients (mean age 45.1 ± 12.8 years, 105 males) with spontaneous BrT1. Of these, 45 patients had experienced VF/SCA and 70 patients did not experience VF/SCA. Among 10 ECG markers, a univariate analysis showed significant associations between VF/SCA and maximum corrected Tpeak–Tend intervals ≥100 ms in precordial leads (LMaxTpec) (P < 0.001), BrT1 in a peripheral lead (pT1) (P = 0.004), early repolarization in inferolateral leads (ER) (P < 0.001), and QRS duration ≥120 ms in lead V2 (P = 0.002). The Cox multivariate analysis revealed four predictors of VF/SCA: the LMaxTpec [hazard ratio (HR) 8.3, 95% confidence interval (CI) 2.4–28.5; P < 0.001], LMaxTpec + ER (HR 14.9, 95% CI 4.2–53.1; P < 0.001), LMaxTpec + pT1 (HR 17.2, 95% CI 4.1–72; P < 0.001), and LMaxTpec + pT1 + ER (HR 23.5, 95% CI 6–93; P < 0.001). Our multidimensional penalized spline model predicted the 1-year risk of VF/SCA, based on age and these markers. Conclusion LMaxTpec and its association with pT1 and/or ER indicated elevated VF/SCA risk in adult patients with spontaneous BrT1. We successfully developed a simple risk prediction model based on age and these ECG markers.


2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaona Jia ◽  
Mirza Mansoor Baig ◽  
Farhaan Mirza ◽  
Hamid GholamHosseini

Background and Objective. Current cardiovascular disease (CVD) risk models are typically based on traditional laboratory-based predictors. The objective of this research was to identify key risk factors that affect the CVD risk prediction and to develop a 10-year CVD risk prediction model using the identified risk factors. Methods. A Cox proportional hazard regression method was applied to generate the proposed risk model. We used the dataset from Framingham Original Cohort of 5079 men and women aged 30-62 years, who had no overt symptoms of CVD at the baseline; among the selected cohort 3189 had a CVD event. Results. A 10-year CVD risk model based on multiple risk factors (such as age, sex, body mass index (BMI), hypertension, systolic blood pressure (SBP), cigarettes per day, pulse rate, and diabetes) was developed in which heart rate was identified as one of the novel risk factors. The proposed model achieved a good discrimination and calibration ability with C-index (receiver operating characteristic (ROC)) being 0.71 in the validation dataset. We validated the model via statistical and empirical validation. Conclusion. The proposed CVD risk prediction model is based on standard risk factors, which could help reduce the cost and time required for conducting the clinical/laboratory tests. Healthcare providers, clinicians, and patients can use this tool to see the 10-year risk of CVD for an individual. Heart rate was incorporated as a novel predictor, which extends the predictive ability of the past existing risk equations.


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