Information on Genetic Variants Does Not Increase Identification of Individuals at Risk of Esophageal Adenocarcinoma Compared to Clinical Risk Factors

Kunzmann, Andrew T.; Cañadas-Garre, Marisa; Thrift, Aaron P.; McMenamin, Úna C.; Johnston, Brian T.; Cardwell, Christopher; Anderson, Lesley A.; Spence, Andrew; Lagergren, Jesper; Xie, Shao-Hua; Smyth, Laura; McKnight, Amy Jayne; Coleman, Helen

doi:10.1053/j.gastro.2018.09.038

Cited by 17 publications

(16 citation statements)

References 14 publications

(21 reference statements)

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“…Earlier tumor detection, particularly among individuals at high absolute risk, has the potential to reduce the mortality from this cancer. A few risk stratification models have been developed for esophageal adenocarcinoma and Barrett esophagus, showing promising performance (47)(48)(49)(50)(51). These models mainly combine clinical and lifestyle risk factors, which are easily captured through questionnaires or medical records, while genetic biomarkers have thus far not improved the identification of high-risk individuals (50).…”

Section: Discussionmentioning

confidence: 99%

Circulating Levels of Inflammatory and Metabolic Biomarkers and Risk of Esophageal Adenocarcinoma and Barrett Esophagus: Systematic Review and Meta-analysis

Xie

Rabbani

Ness-Jensen

et al. 2020

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Associations between circulating levels of obesity-related biomarkers and risk of esophageal adenocarcinoma and Barrett esophagus have been reported, but the results are inconsistent. A literature search until October 2018 in MEDLINE and EMBASE was performed. Pooled ORs with 95% confidence intervals (CI) were estimated for associations between 13 obesity-related inflammatory and metabolic biomarkers and risk of esophageal adenocarcinoma or Barrett esophagus using random effect meta-analyses. Among 7,641 studies, 19 were eligible for inclusion (12 cross-sectional, two nested case-control, and five cohort studies). Comparing the highest versus lowest categories of circulating biomarker levels, the pooled ORs were increased for leptin (OR, 1.68; 95% CI, 0.95-2.97 for Barrett esophagus), glucose (OR, 1.12; 95% CI, 1.03-1.22 for esophageal adenocar-cinoma), insulin (OR, 1.47; 95% CI, 1.06-2.00 for Barrett esophagus), C-reactive protein (CRP; OR, 2.06; 95% CI, 1.28-3.31 for esophageal adenocarcinoma), IL6 (OR, 1.50; 95% CI, 1.03-2.19 for esophageal adenocarcinoma), and soluble TNF receptor 2 (sTNFR-2; OR, 3.16; 95% CI, 1.76-5.65 for esophageal adenocarcinoma). No associations were identified for adiponectin, ghrelin, insulin-like growth factor 1, insulin-like growth factor-binding protein 3, triglycerides, IL8, or TNFa. Higher circulating levels of leptin, glucose, insulin, CRP, IL6, and sTNFR-2 may be associated with an increased risk of esophageal adenocarcinoma or Barrett esophagus. More prospective studies are required to identify biomarkers that can help select high-risk individuals for targeted prevention and early detection.

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Section: Discussionmentioning

confidence: 99%

Circulating Levels of Inflammatory and Metabolic Biomarkers and Risk of Esophageal Adenocarcinoma and Barrett Esophagus: Systematic Review and Meta-analysis

Xie

Rabbani

Ness-Jensen

et al. 2020

Cancer Epidemiology, Biomarkers &Amp; Prevention

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“…Risk models incorporating both genetic and nongenetic factors have previously been developed for predicting risks of various cancers. However, recent studies from our working group and others have found that adding inherited genetic information to a risk model using only clinical and lifestyle factors did not improve discriminatory ability for predicting oesophageal cancer development in the general population . Future research should assess whether or not genetic factors or somatic mutations may improve discrimination in the setting of neoplastic progression in Barrett's oesophagus patients.…”

Section: Discussionmentioning

confidence: 88%

External validation of a model to determine risk of progression of Barrett’s oesophagus to neoplasia

Kunzmann

Thrift

Johnston

et al. 2019

Aliment Pharmacol Ther

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Summary Background A risk prediction model containing sex, smoking history, Barrett's oesophagus length and presence of low‐grade dysplasia was found to identify individuals at a higher risk of progression to oesophageal adenocarcinoma or high‐grade dysplasia. Aim To externally validate the model predicting risk of progression from Barrett's oesophagus to neoplasia and assess the predictive utility of additional factors. Methods We conducted a retrospective cohort study among individuals from the population‐based Northern Ireland Barrett's register with a histologically confirmed diagnosis of Barrett's oesophagus (with intestinal metaplasia) between 1993 and 2005. The association between a points based model and risk of progression to high‐grade dysplasia or oesophageal adenocarcinoma until 2010 was assessed using Cox Proportional Hazards model. Model performance was assessed using area under the receiver operating characteristics curves (AUROC), sensitivity and specificity. Results We identified 1198 individuals with Barrett's oesophagus of whom 54 progressed. The model discriminated reasonably well between progressors and nonprogressors, with an AUROC of 0.70 (95% CI 0.63‐0.78). When categorised into low, intermediate and high risk groups, the AUROC was 0.68 (95% CI 0.61‐0.74). Compared to using data on dysplasia and segment length for risk stratification, the model resulted in a net reclassification improvement of 20.9%. Conclusions This external validation provides further evidence that a model based on sex, smoking, Barrett's segment length and baseline low‐grade dysplasia may help to risk stratify patients after an initial diagnosis of Barrett's oesophagus. The model also performed better than the use of low‐grade dysplasia status alone for risk‐stratification.

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“…However, prediction models with genetic information or biomarkers were identified as high risk in applicability, according to PROBAST, resulting in three models with high risk in applicability. In addition, we found that the addition of genetic risk factors to risk prediction models for esophageal cancer yielded only modest gains in discriminatory power, ranging from 0.70 (0.69–0.71) to 0.71 (0.70–0.72) in a study by Chang et al 18 and from 0.75 (0.72–0.77) to 0.75 (0.73–0.78) in a study by Dong et al 19 A study from the UK biobank 27 identified that the addition of genetic information for EAC did not improve the discriminative performance of a previous prediction model developed with five predictors routinely obtained in clinical practice. It should be carefully considered and thoroughly debated whether biomarkers and genetic information included in the prediction models of esophageal cancer are suitable and feasible to obtain when applying the model to practical situations.…”

Section: Discussionmentioning

confidence: 99%

Risk prediction models for esophageal cancer: A systematic review and critical appraisal

Sun

Cao

et al. 2021

Cancer Medicine

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Background and aims Esophageal cancer risk prediction models allow for risk‐stratified endoscopic screening. We aimed to assess the quality of these models developed in the general population. Methods A systematic search of the PubMed and Embase databases from January 2000 through May 2021 was performed. Studies that developed or validated a model of esophageal cancer in the general population were included. Screening, data extraction, and risk of bias (ROB) assessment by the Prediction model Risk Of Bias Assessment Tool (PROBAST) were performed independently by two reviewers. Results Of the 13 models included in the qualitative analysis, 8 were developed for esophageal squamous cell carcinoma (ESCC) and the other 5 were developed for esophageal adenocarcinoma (EAC). Only two models conducted external validation. In the ESCC models, cigarette smoking was included in each model, followed by age, sex, and alcohol consumption. For EAC models, cigarette smoking and body mass index were included in each model, and gastroesophageal reflux disease, uses of acid‐suppressant medicine, and nonsteroidal anti‐inflammatory drug were exclusively included. The discriminative performance was reported in all studies, with C statistics ranging from 0.71 to 0.88, whereas only six models reported calibration. For ROB, all the models had a low risk in participant and outcome, but all models showed high risk in analysis, and 60% of models showed a high risk in predictors, which resulted in all models being classified as having overall high ROB. For model applicability, about 60% of these models had an overall low risk, with 30% of models of high risk and 10% of models of unclear risk, concerning the assessment of participants, predictors, and outcomes. Conclusions Most current risk prediction models of esophageal cancer have a high ROB. Prediction models need further improvement in their quality and applicability to benefit esophageal cancer screening.

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Information on Genetic Variants Does Not Increase Identification of Individuals at Risk of Esophageal Adenocarcinoma Compared to Clinical Risk Factors

Cited by 17 publications

References 14 publications

Circulating Levels of Inflammatory and Metabolic Biomarkers and Risk of Esophageal Adenocarcinoma and Barrett Esophagus: Systematic Review and Meta-analysis

Circulating Levels of Inflammatory and Metabolic Biomarkers and Risk of Esophageal Adenocarcinoma and Barrett Esophagus: Systematic Review and Meta-analysis

External validation of a model to determine risk of progression of Barrett’s oesophagus to neoplasia

Risk prediction models for esophageal cancer: A systematic review and critical appraisal

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