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A New Comprehensive Colorectal Cancer Risk Prediction Model Incorporating Family History, Personal Characteristics, and Environmental Factors.

ABSTRACT: PURPOSE:Reducing colorectal cancer incidence and mortality through early detection would improve efficacy if targeted. We developed a colorectal cancer risk prediction model incorporating personal, family, genetic, and environmental risk factors to enhance prevention. METHODS:A familial risk profile (FRP) was calculated to summarize individuals' risk based on detailed cancer family history (FH), family structure, probabilities of mutation in major colorectal cancer susceptibility genes, and a polygenic component. We developed risk models, including individuals' FRP or binary colorectal cancer FH, and colorectal cancer risk factors collected at enrollment using population-based colorectal cancer cases (N = 4,445) and controls (N = 3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). Model validation used CCFRC follow-up data for population-based (N = 12,052) and clinic-based (N = 5,584) relatives with no cancer history at recruitment to assess model calibration [expected/observed rate ratio (E/O)] and discrimination [area under the receiver-operating-characteristic curve (AUC)]. RESULTS:The E/O [95% confidence interval (CI)] for FRP models for population-based relatives were 1.04 (0.74-1.45) for men and 0.86 (0.64-1.20) for women, and for clinic-based relatives were 1.15 (0.87-1.58) for men and 1.04 (0.76-1.45) for women. The age-adjusted AUCs (95% CI) for FRP models for population-based relatives were 0.69 (0.60-0.78) for men and 0.70 (0.62-0.77) for women, and for clinic-based relatives were 0.77 (0.69-0.84) for men and 0.68 (0.60-0.76) for women. The incremental values of AUC for FRP over FH models for population-based relatives were 0.08 (0.01-0.15) for men and 0.10 (0.04-0.16) for women, and for clinic-based relatives were 0.11 (0.05-0.17) for men and 0.11 (0.06-0.17) for women. CONCLUSIONS:Both models calibrated well. The FRP-based model provided better risk stratification and risk discrimination than the FH-based model. IMPACT:Our findings suggest detailed FH may be useful for targeted risk-based screening and clinical management.

SUBMITTER: Zheng Y

PROVIDER: S-EPMC7060114 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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A New Comprehensive Colorectal Cancer Risk Prediction Model Incorporating Family History, Personal Characteristics, and Environmental Factors.

Zheng Yingye Y Hua Xinwei X Win Aung K AK MacInnis Robert J RJ Gallinger Steven S Marchand Loic Le LL Lindor Noralane M NM Baron John A JA Hopper John L JL Dowty James G JG Antoniou Antonis C AC Zheng Jiayin J Jenkins Mark A MA Newcomb Polly A PA

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20200113 3

<h4>Purpose</h4>Reducing colorectal cancer incidence and mortality through early detection would improve efficacy if targeted. We developed a colorectal cancer risk prediction model incorporating personal, family, genetic, and environmental risk factors to enhance prevention.<h4>Methods</h4>A familial risk profile (FRP) was calculated to summarize individuals' risk based on detailed cancer family history (FH), family structure, probabilities of mutation in major colorectal cancer susceptibility ...[more]

PMID: 31932410

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Project description:IntroductionThe pathogenesis and risk factors for hyperemesis gravidarum, excessive nausea and vomiting of pregnancy, are not adequately recognized. In our previous study, we found that women with a personal history of nausea in different situations and a family history of nausea and vomiting of pregnancy (NVP) were more likely to have severe NVP. The present study focuses on these themes in association with hyperemesis gravidarum in a hospital setting.Material and methodsWomen with hyperemesis gravidarum (n = 102) were recruited from among patients hospitalized due to hyperemesis gravidarum in Turku University Hospital, Finland. Our control group (Non-NVP group, n = 138) consisted of pregnant women with no NVP. Personal history of nausea in different situations was inquired about in relation to "motion sickness", "seasickness", "migraine", "other kind of headache", "after anesthesia", "during the use of contraception", and "other kinds of nausea". Relatives with NVP were divided into first-degree (mother and sisters) and second-degree (more distant) relatives.ResultsIn univariate analysis, a personal history of motion sickness, seasickness, nausea related to migraine, nausea with other headache and nausea in other situations were associated with hyperemesis gravidarum. After adjusting for age, parity, pre-pregnancy body mass index, marital status, and smoking, motion sickness (adjusted odds ratio [aOR] 5.24, 95% confidence interval [CI] 2.67-10.31, p < 0.0001), seasickness (aOR 4.82, 95% CI 2.32-10.03, p < 0.0001), nausea related to migraine (aOR 3.00, 95% CI 1.58-5.70, p < 0.001), and nausea in other situations (aOR 2.65, 95% CI 1.13-6.20, p = 0.025) remained significant. In multivariable analysis with all history of nausea variables, motion sickness (OR 2.76, 95% CI 1.29-5.89, p = 0.009) and nausea related to migraine (OR 3.10, 95% CI 1.40-6.86, p = 0.005) were associated with hyperemesis gravidarum. Having any affected relative (OR 3.51, 95%CI 1.84-6.73, p = 0.0002), especially a first-degree relative (OR 3.06, 95% CI 1.62-5.79, p = 0.0006), was also associated with hyperemesis gravidarum. Adjustment did not change the results.ConclusionsWomen with a personal history of nausea or a family history of NVP are more likely to suffer from hyperemesis gravidarum. These results are beneficial to better identify and help women at risk for hyperemesis gravidarum.

Project description:BackgroundThe cost of genomic information has fallen steeply, but the clinical translation of genetic risk estimates remains unclear. We aimed to undertake an integrated analysis of a complete human genome in a clinical context.MethodsWe assessed a patient with a family history of vascular disease and early sudden death. Clinical assessment included analysis of this patient's full genome sequence, risk prediction for coronary artery disease, screening for causes of sudden cardiac death, and genetic counselling. Genetic analysis included the development of novel methods for the integration of whole genome and clinical risk. Disease and risk analysis focused on prediction of genetic risk of variants associated with mendelian disease, recognised drug responses, and pathogenicity for novel variants. We queried disease-specific mutation databases and pharmacogenomics databases to identify genes and mutations with known associations with disease and drug response. We estimated post-test probabilities of disease by applying likelihood ratios derived from integration of multiple common variants to age-appropriate and sex-appropriate pre-test probabilities. We also accounted for gene-environment interactions and conditionally dependent risks.FindingsAnalysis of 2.6 million single nucleotide polymorphisms and 752 copy number variations showed increased genetic risk for myocardial infarction, type 2 diabetes, and some cancers. We discovered rare variants in three genes that are clinically associated with sudden cardiac death-TMEM43, DSP, and MYBPC3. A variant in LPA was consistent with a family history of coronary artery disease. The patient had a heterozygous null mutation in CYP2C19 suggesting probable clopidogrel resistance, several variants associated with a positive response to lipid-lowering therapy, and variants in CYP4F2 and VKORC1 that suggest he might have a low initial dosing requirement for warfarin. Many variants of uncertain importance were reported.InterpretationAlthough challenges remain, our results suggest that whole-genome sequencing can yield useful and clinically relevant information for individual patients.FundingNational Institute of General Medical Sciences; National Heart, Lung And Blood Institute; National Human Genome Research Institute; Howard Hughes Medical Institute; National Library of Medicine, Lucile Packard Foundation for Children's Health; Hewlett Packard Foundation; Breetwor Family Foundation.

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A New Comprehensive Colorectal Cancer Risk Prediction Model Incorporating Family History, Personal Characteristics, and Environmental Factors.

Publications

A New Comprehensive Colorectal Cancer Risk Prediction Model Incorporating Family History, Personal Characteristics, and Environmental Factors.

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