scholarly journals iCARE: R package to build, validate and apply absolute risk models

2016 ◽  
Author(s):  
Parichoy Pal Choudhury ◽  
Paige Maas ◽  
Amber Wilcox ◽  
William Wheeler ◽  
Mark Brook ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Estimation ◽  
Absolute Risk ◽  
Disease Incidence ◽  
Model Averaging ◽  
R Package ◽  
Time Interval ◽  
Nucleotide Polymorphisms ◽  
Risk Models ◽  
Different Populations

AbstractThis report describes a R package, called the Individualized Coherent Absolute Risk Estimation (iCARE) tool, that allows researchers to build and evaluate models for absolute risk and apply them to estimate an individual’s risk of developing disease during a specified time interval based on a set of user defined input parameters. An attractive feature of the software is that it gives users flexibility to update models rapidly based on new knowledge on risk factors and tailor models to different populations by specifying three input arguments: (1) a model for relative risk, (2) an age-specific disease incidence rate, (3) the distribution of risk factors for the population of interest. The tool can handle missing information on risk factors for individuals for whom risks are to be predicted using a coherent approach where all estimates are derived from a single model after appropriate model averaging. The software allows single nucleotide polymorphisms (SNPs) to be incorporated into the model using published odds ratios and allele frequencies. The validation component of the software implements the methods for evaluation of model calibration, discrimination and risk-stratification based on independent validation datasets. We provide an illustration of the utility of iCARE for building, validating and applying absolute risk models using breast cancer as an example.

Risk stratification and risk assessment

2015 ◽  
Author(s):  
Ian Graham ◽  
Therese Cooney ◽  
Dirk De Bacquer
Keyword(s):  
Risk Factors ◽  
Relative Risk ◽  
Risk Estimation ◽  
Absolute Risk ◽  
Cvd Risk ◽  
Mortality And Morbidity ◽  
Risk Factor Management ◽  
Estimation System ◽  
Very High ◽  
Apparently Healthy

Cardiovascular disease (CVD) is the biggest cause of death worldwide. The underlying atherosclerosis starts in childhood and is often advanced when it becomes clinically apparent many years later. CVD is manageable: in countries where it has reduced this is due to changes in lifestyle and risk factors and to therapy. Risk factor management reduces mortality and morbidity. In apparently healthy people CVD risk is most frequently the result of multiple interacting risk factors and a risk estimation system such as SCORE can assist in making logical management decisions. In younger people a low absolute risk may conceal a very high relative risk, and use of the relative risk chart or calculation of their ‘risk age’ may help in advising them of the need for intensive life style efforts. All risk estimation systems are relatively crude and require attention to qualifying statements.

scholarly journals Estimation of Absolute Cardiovascular Risk in Individuals with Diabetes Mellitus: Rationale and Approaches

2011 ◽  
Vol 2011 ◽  
pp. 1-5 ◽  
Author(s):  
Justin B. Echouffo-Tcheugui ◽  
Modele O. Ogunniyi ◽  
André P. Kengne
Keyword(s):  
Risk Factors ◽  
Cardiovascular Risk ◽  
Preventive Measures ◽  
Care Delivery ◽  
Risk Estimation ◽  
Discriminative Power ◽  
Global Risk ◽  
Risk Models ◽  
Absolute Cardiovascular Risk ◽  
Cardiovascular Risk Estimation

Purpose. To examine the usefulness of cardiovascular risk estimation models in people with diabetes. Methods. Review of published studies that compare the discriminative power of major cardiovascular risk factors single or in combination in individuals with and without diabetes, for major cardiovascular outcomes. Results. In individuals with and without diabetes, major risk factors affect cardiovascular risk similarly, with no evidence of any significant interaction. Accounting for diabetes-specific parameters, cardiopreventative therapies can significantly improve risk estimation in diabetes. General and diabetes-specific cardiovascular risk models have a useful discriminative power, but tend to overestimate risk in individuals with diabetes. Their impact on care delivery, adherence to therapies, and patients' outcome remain poorly understood. Conclusions. The high-risk status conferred by diabetes does not preclude the estimation of absolute cardiovascular risk estimation using global risk tools in individuals with diabetes, as this is useful for the initiation and intensification of preventive measures.

scholarly journals iCARE: An R package to build, validate and apply absolute risk models

PLoS ONE ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. e0228198 ◽  
Author(s):  
Parichoy Pal Choudhury ◽  
Paige Maas ◽  
Amber Wilcox ◽  
William Wheeler ◽  
Mark Brook ◽  
...  
Keyword(s):  
Absolute Risk ◽  
R Package ◽  
Risk Models

scholarly journals Comparative validation of breast cancer risk prediction models and projections for future risk stratification

2018 ◽  
Author(s):  
Parichoy Pal Choudhury ◽  
Amber N. Wilcox ◽  
Mark N. Brook ◽  
Yan Zhang ◽  
Thomas Ahearn ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Risk Stratification ◽  
Invasive Breast Cancer ◽  
Prediction Models ◽  
Risk Estimation ◽  
Absolute Risk ◽  
Mammographic Breast Density ◽  
Polygenic Risk Score ◽  
Additional Information

AbstractBackgroundWell-validated risk models are critical for risk stratified breast cancer prevention. We used the Individualized Coherent Absolute Risk Estimation (iCARE) tool for comparative model validation of five-year risk of invasive breast cancer in a prospective cohort, and to make projections for population risk stratification.MethodsPerformance of two recently developed models, iCARE-BPC3 and iCARE-Lit, were compared with two established models (BCRAT, IBIS) based on classical risk factors in a UK-based cohort of 64,874 women (863 cases) aged 35-74 years. Risk projections in US White non-Hispanic women aged 50-70 years were made to assess potential improvements in risk stratification by adding mammographic breast density (MD) and polygenic risk score (PRS).ResultsThe best calibrated models were iCARE-Lit (expected to observed number of cases (E/O)=0.98 (95% confidence interval [CI]=0.87 to 1.11)) for women younger than 50 years; and iCARE-BPC3 (E/O=1.00 (0.93 to 1.09)) for women 50 years or older. Risk projections using iCARE-BPC3 indicated classical risk factors can identify ~500,000 women at moderate to high risk (>3% five-year risk). Additional information on MD and a PRS based on 172 variants is expected to increase this to ~3.6 million, and among them, ~155,000 invasive breast cancer cases are expected within five years.ConclusionsiCARE models based on classical risk factors perform similarly or better than BCRAT or IBIS. Addition of MD and PRS can lead to substantial improvements in risk stratification. Independent prospective validation of integrated models is needed prior to clinical evaluation risk stratified breast cancer screening and prevention.

Statin-induced adverse effects – facts and genes

2013 ◽  
Vol 154 (3) ◽  
pp. 83-92
Author(s):  
Mariann Harangi ◽  
Noémi Zsíros ◽  
Lilla Juhász ◽  
György Paragh
Keyword(s):  
Risk Factors ◽  
Single Nucleotide Polymorphisms ◽  
Adverse Effects ◽  
Adverse Events ◽  
Statin Therapy ◽  
Significant Proportion ◽  
Gene Mutations ◽  
Nucleotide Polymorphisms ◽  
Serious Adverse Events ◽  
Single Nucleotide

Statin therapy is considered to be safe and rarely associated with serious adverse events. However, a significant proportion of patients on statin therapy show some degree of intolerance which can lead to decreased adherence to statin therapy. The authors summarize the symptoms, signs and frequencies of the most common statin-induced adverse effects and their most important risk factors including some single nucleotide polymorphisms and gene mutations. Also, they review the available approaches to detect and manage the statin-intolerant patients. Orv. Hetil., 2013, 154, 83–92.

Analysis of the Potential Association of Drug-Metabolizing Enzymes CYP2C9*3 and CYP2C19*3 Gene Variations With Type 2 Diabetes: A Case-Control Study

2020 ◽  
Vol 21 (14) ◽  
pp. 1152-1160
Author(s):  
Imadeldin Elfaki ◽  
Rashid Mir ◽  
Faisel Mohammed Abu-Duhier ◽  
Chandan Kumar Jha ◽  
Adel Ibrahim Ahmad Al-Alawy ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Antiplatelet Drug ◽  
Drug Metabolizing Enzymes ◽  
Genotype Distribution ◽  
Nucleotide Polymorphisms ◽  
Metabolizing Enzymes ◽  
Specific Pcr ◽  
Increased Risk ◽  
Different Populations

Background:: Cytochrome P450s (CYPs) are drug-metabolizing enzymes catalyzing the metabolism of about 75% of drug in clinical use. CYP2C9 represents 20% CYP proteins in liver cells and is a crucial member of CYPs superfamily. CYP2C19 metabolizes very important drugs such as antiulcer drug omeprazole, the antiplatelet drug clopidogrel and anticonvulsant mephenytoin. Single nucleotide polymorphisms (SNPs) of CYP genes have been associated with unexpected drug reactions and diseases in different populations. Objective:: We examined the associations of CYP2C9*3 (rs1057910) and CYP2C19*3 (rs4986893) with T2D in Saudi population. Methods:: We used the allele-specific PCR (AS-PCR) and DNA sequencing in 111 cases and 104 controls for rs1057910, and in 119 cases and 110 controls for rs4986893. Results:: It is indicated that the genotype distribution of rs1057910 in cases and controls were not significantly different (P=0.0001). The genotypes of rs1057910 were not associated with type 2 diabetes (T2D) (P>0.05). Whereas the genotype distribution of rs4986893 in cases and controls was significantly different (P=0.049). The AA genotype of rs4986893 may be associated in increased risk to T2D with OR=17.25 (2.06-143.8), RR=6.14(0.96-39.20), P=0.008. Conclusion:: The CYP2C9*3 (rs1057910) may not be associated with T2D, while CYP2C19*3 (rs4986893) is probably associated with T2D. These findings need to be validated in follow-up studies with larger sample sizes and different populations.

EpiPen: An R Package to Investigate Two-Locus Epistatic Models

2014 ◽  
Vol 17 (4) ◽  
Author(s):  
Raymond K. Walters ◽  
Charles Laurin ◽  
Gitta H. Lubke
Keyword(s):  
Power Analysis ◽  
R Package ◽  
Simulation Studies ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Epistatic Interactions ◽  
Model Interpretation ◽  
Genome Wide ◽  
Using Data ◽  
Power Analyses

Epistasis is a growing area of research in genome-wide studies, but the differences between alternative definitions of epistasis remain a source of confusion for many researchers. One problem is that models for epistasis are presented in a number of formats, some of which have difficult-to-interpret parameters. In addition, the relation between the different models is rarely explained. Existing software for testing epistatic interactions between single-nucleotide polymorphisms (SNPs) does not provide the flexibility to compare the available model parameterizations. For that reason we have developed an R package for investigating epistatic and penetrance models, EpiPen, to aid users who wish to easily compare, interpret, and utilize models for two-locus epistatic interactions. EpiPen facilitates research on SNP-SNP interactions by allowing the R user to easily convert between common parametric forms for two-locus interactions, generate data for simulation studies, and perform power analyses for the selected model with a continuous or dichotomous phenotype. The usefulness of the package for model interpretation and power analysis is illustrated using data on rheumatoid arthritis.

scholarly journals Radiation necrosis after a combination of external beam radiotherapy and iodine-125 brachytherapy in gliomas

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Indrawati Hadi ◽  
Daniel Reitz ◽  
Raphael Bodensohn ◽  
Olarn Roengvoraphoj ◽  
Stefanie Lietke ◽  
...  
Keyword(s):  
Risk Factors ◽  
Radiation Necrosis ◽  
Irradiation Time ◽  
External Beam Radiotherapy ◽  
High Grade Glioma ◽  
Metabolic Imaging ◽  
Time Interval ◽  
Low Grade ◽  
External Beam ◽  
Iodine 125

Abstract Purpose Frequency and risk profile of radiation necrosis (RN) in patients with glioma undergoing either upfront stereotactic brachytherapy (SBT) and additional salvage external beam radiotherapy (EBRT) after tumor recurrence or vice versa remains unknown. Methods Patients with glioma treated with low-activity temporary iodine-125 SBT at the University of Munich between 1999 and 2016 who had either additional upfront or salvage EBRT were included. Biologically effective doses (BED) were calculated. RN was diagnosed using stereotactic biopsy and/or metabolic imaging. The rate of RN was estimated with the Kaplan Meier method. Risk factors were obtained from logistic regression models. Results Eighty-six patients (49 male, 37 female, median age 47 years) were included. 38 patients suffered from low-grade and 48 from high-grade glioma. Median follow-up was 15 months after second treatment. Fifty-eight patients received upfront EBRT (median total dose: 60 Gy), and 28 upfront SBT (median reference dose: 54 Gy, median dose rate: 10.0 cGy/h). Median time interval between treatments was 19 months. RN was diagnosed in 8/75 patients. The 1- and 2-year risk of RN was 5.1% and 11.7%, respectively. Tumor volume and irradiation time of SBT, number of implanted seeds, and salvage EBRT were risk factors for RN. Neither of the BED values nor the time interval between both treatments gained prognostic influence. Conclusion The combination of upfront EBRT and salvage SBT or vice versa is feasible for glioma patients. The risk of RN is mainly determined by the treatment volume but not by the interval between therapies.

scholarly journals Cumulative incidence and risk factors for radiation induced leukoencephalopathy in high grade glioma long term survivors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Robert Terziev ◽  
Dimitri Psimaras ◽  
Yannick Marie ◽  
Loic Feuvret ◽  
Giulia Berzero ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cumulative Incidence ◽  
High Grade Glioma ◽  
High Grade ◽  
Nucleotide Polymorphisms ◽  
Increased Risk ◽  
Radiation Induced ◽  
Long Term Survivors

AbstractThe incidence and risk factors associated with radiation-induced leukoencephalopathy (RIL) in long-term survivors of high-grade glioma (HGG) are still poorly investigated. We performed a retrospective research in our institutional database for patients with supratentorial HGG treated with focal radiotherapy, having a progression-free overall survival > 30 months and available germline DNA. We reviewed MRI scans for signs of leukoencephalopathy on T2/FLAIR sequences, and medical records for information on cerebrovascular risk factors and neurological symptoms. We investigated a panel of candidate single nucleotide polymorphisms (SNPs) to assess genetic risk. Eighty-one HGG patients (18 grade IV and 63 grade III, 50M/31F) were included in the study. The median age at the time of radiotherapy was 48 years old (range 18–69). The median follow-up after the completion of radiotherapy was 79 months. A total of 44 patients (44/81, 54.3%) developed RIL during follow-up. Twenty-nine of the 44 patients developed consistent symptoms such as subcortical dementia (n = 28), gait disturbances (n = 12), and urinary incontinence (n = 9). The cumulative incidence of RIL was 21% at 12 months, 42% at 36 months, and 48% at 60 months. Age > 60 years, smoking, and the germline SNP rs2120825 (PPARg locus) were associated with an increased risk of RIL. Our study identified potential risk factors for the development of RIL (age, smoking, and the germline SNP rs2120825) and established the rationale for testing PPARg agonists in the prevention and management of late-delayed radiation-induced neurotoxicity.

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