scholarly journals Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals: a systematic literature review and external validation in the EPIC and UK Biobank prospective cohort studies

Gut ◽  
2018 ◽  
Vol 68 (4) ◽  
pp. 672-683 ◽  
Author(s):  
Todd Smith ◽  
David C Muller ◽  
Karel G M Moons ◽  
Amanda J Cross ◽  
Mattias Johansson ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Systematic Review ◽  
Prediction Models ◽  
Large Population ◽  
External Validation ◽  
Population Based ◽  
Prognostic Models ◽  
Uk Biobank ◽  
Asymptomatic Individuals ◽  
The Uk

ObjectiveTo systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts.DesignModels were identified through an update of a published systematic review and validated in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank. The performance of the models to predict the occurrence of colorectal cancer within 5 or 10 years after study enrolment was assessed by discrimination (C-statistic) and calibration (plots of observed vs predicted probability).ResultsThe systematic review and its update identified 16 models from 8 publications (8 colorectal, 5 colon and 3 rectal). The number of participants included in each model validation ranged from 41 587 to 396 515, and the number of cases ranged from 115 to 1781. Eligible and ineligible participants across the models were largely comparable. Calibration of the models, where assessable, was very good and further improved by recalibration. The C-statistics of the models were largely similar between validation cohorts with the highest values achieved being 0.70 (95% CI 0.68 to 0.72) in the UK Biobank and 0.71 (95% CI 0.67 to 0.74) in EPIC.ConclusionSeveral of these non-invasive models exhibited good calibration and discrimination within both external validation populations and are therefore potentially suitable candidates for the facilitation of risk stratification in population-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained.

scholarly journals 0154 A new, efficient web-based tool to collect and code lifetime job histories in large population-based studies: the COPD project in the UK Biobank cohort

2014 ◽  
Vol 71 (Suppl 1) ◽  
pp. A19.1-A19
Author(s):  
Sara De Matteis ◽  
Lesley Rushton ◽  
Debbie Jarvis ◽  
Magda Wheatley ◽  
Hadia Azhar ◽  
...  
Keyword(s):  
Large Population ◽  
Population Based ◽  
Uk Biobank ◽  
Web Based ◽  
The Uk

scholarly journals Optical Coherence Tomography in the UK Biobank Study – Rapid Automated Analysis of Retinal Thickness for Large Population-Based Studies

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0164095 ◽  
Author(s):  
Pearse A. Keane ◽  
Carlota M. Grossi ◽  
Paul J. Foster ◽  
Qi Yang ◽  
Charles A. Reisman ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Retinal Thickness ◽  
Large Population ◽  
Automated Analysis ◽  
Population Based ◽  
Optical Coherence ◽  
Uk Biobank ◽  
The Uk

scholarly journals External validation of risk prediction models for incident colorectal cancer using UK Biobank

2018 ◽  
Vol 118 (5) ◽  
pp. 750-759 ◽  
Author(s):  
J A Usher-Smith ◽  
A Harshfield ◽  
C L Saunders ◽  
S J Sharp ◽  
J Emery ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prediction Models ◽  
Characteristic Curve ◽  
External Validation ◽  
Risk Scores ◽  
Prior History ◽  
Uk Biobank ◽  
Risk Models ◽  
Potential Health ◽  
Men And Women

Abstract Background: This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire. Methods: External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries. Results: There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals. Conclusions: Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.

scholarly journals Analysis of MRI-derived spleen iron in the UK Biobank identifies genetic variation linked to iron recycling and erythrocyte morphology

2021 ◽  
Author(s):  
Elena P. Sorokin ◽  
Nicolas Basty ◽  
Brandon Whitcher ◽  
Yi Liu ◽  
Jimmy D. Bell ◽  
...  
Keyword(s):  
Iron Homeostasis ◽  
Genome Wide Association Study ◽  
Large Population ◽  
Population Based ◽  
Monocyte Count ◽  
Genetic Modifiers ◽  
Uk Biobank ◽  
Genetic Associations ◽  
Erythrocyte Morphology ◽  
The Uk

AbstractAging, and the pathogenesis of many common diseases, involves iron homeostasis. A key role in iron homeostasis is played by the spleen, which is the largest filter of the blood and performs iron reuptake from old or damaged erythrocytes. Despite this important role, spleen iron content has not been measured previously in a large, population-based cohort. In this study, we quantify spleen iron in 41,764 participants of the UK Biobank using magnetic resonance imaging (MRI). We find that epidemiologic and environmental factors such as increased age, higher red meat consumption and lower alcohol intake correlate with higher spleen iron. Through genome-wide association study, we identify genetic associations between spleen iron and common variation at seven loci, including in two hereditary spherocytosis (HS) genes, ANK1 and SPTA1. HS-causing mutations in these genes are associated with lower reticulocyte volume and increased reticulocyte percentage, while our common alleles are associated with increased expression of ANK1 and SPTA1 in blood and with larger reticulocyte volume and reduced reticulocyte percentage. As genetic modifiers, these common alleles may explain mild spherocytosis phenotypes observed in some HS allele carriers. Further, we identify an association between spleen iron and MS4A7, which colocalizes with a quantitative trait locus for MS4A7 alternative splicing in whole blood, and with monocyte count and fraction. Through quantification of spleen iron in a large human cohort, we extend our understanding of epidemiological and genetic factors associated with iron recycling and erythrocyte morphology.

scholarly journals Prediction Models for Severe Manifestations and Mortality due to COVID-19: A Rapid Systematic Review

2021 ◽  
Author(s):  
Jamie L. Miller ◽  
Masafumi Tada ◽  
Michihiko Goto ◽  
Nicholas Mohr ◽  
Sangil Lee
Keyword(s):  
Systematic Review ◽  
Prediction Model ◽  
Prediction Models ◽  
External Validation ◽  
Clinical Signs ◽  
Risk Of Bias ◽  
Low Risk ◽  
Prognostic Models ◽  
Organ Support ◽  
Public Data

ABSTRACTBackgroundThroughout 2020, the coronavirus disease 2019 (COVID-19) has become a threat to public health on national and global level. There has been an immediate need for research to understand the clinical signs and symptoms of COVID-19 that can help predict deterioration including mechanical ventilation, organ support, and death. Studies thus far have addressed the epidemiology of the disease, common presentations, and susceptibility to acquisition and transmission of the virus; however, an accurate prognostic model for severe manifestations of COVID-19 is still needed because of the limited healthcare resources available.ObjectiveThis systematic review aims to evaluate published reports of prediction models for severe illnesses caused COVID-19.MethodsSearches were developed by the primary author and a medical librarian using an iterative process of gathering and evaluating terms. Comprehensive strategies, including both index and keyword methods, were devised for PubMed and EMBASE. The data of confirmed COVID-19 patients from randomized control studies, cohort studies, and case-control studies published between January 2020 and July 2020 were retrieved. Studies were independently assessed for risk of bias and applicability using the Prediction Model Risk Of Bias Assessment Tool (PROBAST). We collected study type, setting, sample size, type of validation, and outcome including intubation, ventilation, any other type of organ support, or death. The combination of the prediction model, scoring system, performance of predictive models, and geographic locations were summarized.ResultsA primary review found 292 articles relevant based on title and abstract. After further review, 246 were excluded based on the defined inclusion and exclusion criteria. Forty-six articles were included in the qualitative analysis. Inter observer agreement on inclusion was 0.86 (95% confidence interval: 0.79 - 0.93). When the PROBAST tool was applied, 44 of the 46 articles were identified to have high or unclear risk of bias, or high or unclear concern for applicability. Two studied reported prediction models, 4C Mortality Score from hospital data and QCOVID from general public data from UK, and were rated as low risk of bias and low concerns for applicability.ConclusionSeveral prognostic models are reported in the literature, but many of them had concerning risks of biases and applicability. For most of the studies, caution is needed before use, as many of them will require external validation before dissemination. However, two articles were found to have low risk of bias and low applicability can be useful tools.

scholarly journals Dementia risk in the general population: large-scale external validation of prediction models in the AGES-Reykjavik study

2021 ◽  
Author(s):  
Jet M. J. Vonk ◽  
Jacoba P. Greving ◽  
Vilmundur Gudnason ◽  
Lenore J. Launer ◽  
Mirjam I. Geerlings
Keyword(s):  
High Risk ◽  
General Population ◽  
Large Scale ◽  
Prediction Models ◽  
External Validation ◽  
Predictive Performance ◽  
Population Based ◽  
Cognitive Testing ◽  
Prognostic Models ◽  
Dementia Risk

AbstractWe aimed to evaluate the external performance of prediction models for all-cause dementia or AD in the general population, which can aid selection of high-risk individuals for clinical trials and prevention. We identified 17 out of 36 eligible published prognostic models for external validation in the population-based AGES-Reykjavik Study. Predictive performance was assessed with c statistics and calibration plots. All five models with a c statistic > .75 (.76–.81) contained cognitive testing as a predictor, while all models with lower c statistics (.67–.75) did not. Calibration ranged from good to poor across all models, including systematic risk overestimation or overestimation for particularly the highest risk group. Models that overestimate risk may be acceptable for exclusion purposes, but lack the ability to accurately identify individuals at higher dementia risk. Both updating existing models or developing new models aimed at identifying high-risk individuals, as well as more external validation studies of dementia prediction models are warranted.

scholarly journals Correction: External validation of risk prediction models for incident colorectal cancer using UK Biobank

2020 ◽  
Vol 122 (10) ◽  
pp. 1572-1575
Author(s):  
J. A. Usher-Smith ◽  
A. Harshfield ◽  
C. L. Saunders ◽  
S. J. Sharp ◽  
J. Emery ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Uk Biobank ◽  
Risk Prediction Models

scholarly journals The molecular genetics of hand preference revisited

2018 ◽  
Author(s):  
Carolien G.F. de Kovel ◽  
Clyde Francks
Keyword(s):  
Complex Traits ◽  
Large Population ◽  
Enrichment Analysis ◽  
Hand Preference ◽  
Population Based ◽  
Gene Set Enrichment Analysis ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

AbstractHand preference is a prominent behavioural trait linked to human brain asymmetry. A handful of genetic variants have been reported to associate with hand preference or quantitative measures related to it. Most of these reports were on the basis of limited sample sizes, by current standards for genetic analysis of complex traits. Here we performed a genome-wide association analysis of hand preference in the large, population-based UK Biobank cohort (N=331,037). We used gene-set enrichment analysis to investigate whether genes involved in visceral asymmetry are particularly relevant to hand preference, following one previous report. We found no evidence implicating any specific candidate variants previously reported. We also found no evidence that genes involved in visceral laterality play a role in hand preference. It remains possible that some of the previously reported genes or pathways are relevant to hand preference as assessed in other ways, or else are relevant within specific disorder populations. However, some or all of the earlier findings are likely to be false positives, and none of them appear relevant to hand preference as defined categorically in the general population. Within the UK Biobank itself, a significant association implicates the gene MAP2 in handedness.

scholarly journals A population scale analysis of rare SNCA variation in the UK Biobank

2020 ◽  
Author(s):  
Cornelis Blauwendraat ◽  
Mary B. Makarious ◽  
Hampton L. Leonard ◽  
Sara Bandres-Ciga ◽  
Hirotaka Iwaki ◽  
...  
Keyword(s):  
Copy Number ◽  
Human Genetics ◽  
Large Population ◽  
Point Mutations ◽  
Population Based ◽  
Alpha Synuclein ◽  
Uk Biobank ◽  
Snca Gene ◽  
Large Complex ◽  
The Uk

Parkinson disease (PD) is a complex neurodegenerative disease with a variety of genetic and environmental factors contributing to disease. The SNCA gene encodes for the alpha-synuclein protein which plays a central role in PD, where aggregates of this protein are one of pathological hallmarks of disease. Rare point mutations and copy number gains of the SNCA gene have been shown to cause autosomal dominant PD and common DNA variants identified using GWAS are a moderate risk factor for PD. The UK Biobank is a large prospective study including 500,000 individuals and has revolutionized human genetics. Here we assessed the frequency of SNCA variation in this cohort and identified 26 subjects carrying variants of interest including duplications (n=6), deletions (n=6) and large complex likely mosaic events (n=14). No known pathogenic missense variants were identified. None of these subjects were reported to be a PD case, although it is possible that these individuals may develop PD at a later age, and whilst three had known prodromal features, these did not meet defined thresholds for being considered prodromal cases. Four of the 14 large complex carriers showed a history of blood based cancer. Overall, we identified copy number variants in the SNCA region in a large population based cohort without reported PD phenotype and symptoms. Putative mosaicism of the SNCA gene was identified, however it is unclear whether it is associated with Parkinson's disease. These individuals are potential candidates for further investigation by performing SNCA RNA and protein expression studies, as well as promising clinical trial candidates to understand how duplication carriers potentially escape PD.

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