scholarly journals Risk prediction models for colorectal cancer: A Scoping review

2018 ◽  
Vol 4 (2) ◽  
pp. 56
Author(s):  
Yasara Manori Samarakoon ◽  
Arunasalam Pathmeswaran ◽  
Nalika Sepali Gunawardena
BMC Cancer ◽  
2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Michele Sassano ◽  
Marco Mariani ◽  
Gianluigi Quaranta ◽  
Roberta Pastorino ◽  
Stefania Boccia

Abstract Background Risk prediction models incorporating single nucleotide polymorphisms (SNPs) could lead to individualized prevention of colorectal cancer (CRC). However, the added value of incorporating SNPs into models with only traditional risk factors is still not clear. Hence, our primary aim was to summarize literature on risk prediction models including genetic variants for CRC, while our secondary aim was to evaluate the improvement of discriminatory accuracy when adding SNPs to a prediction model with only traditional risk factors. Methods We conducted a systematic review on prediction models incorporating multiple SNPs for CRC risk prediction. We tested whether a significant trend in the increase of Area Under Curve (AUC) according to the number of SNPs could be observed, and estimated the correlation between AUC improvement and number of SNPs. We estimated pooled AUC improvement for SNP-enhanced models compared with non-SNP-enhanced models using random effects meta-analysis, and conducted meta-regression to investigate the association of specific factors with AUC improvement. Results We included 33 studies, 78.79% using genetic risk scores to combine genetic data. We found no significant trend in AUC improvement according to the number of SNPs (p for trend = 0.774), and no correlation between the number of SNPs and AUC improvement (p = 0.695). Pooled AUC improvement was 0.040 (95% CI: 0.035, 0.045), and the number of cases in the study and the AUC of the starting model were inversely associated with AUC improvement obtained when adding SNPs to a prediction model. In addition, models constructed in Asian individuals achieved better AUC improvement with the incorporation of SNPs compared with those developed among individuals of European ancestry. Conclusions Though not conclusive, our results provide insights on factors influencing discriminatory accuracy of SNP-enhanced models. Genetic variants might be useful to inform stratified CRC screening in the future, but further research is needed.


2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Krasimira Aleksandrova ◽  
Robin Reichmann ◽  
Mazda Jenab ◽  
Sabina Rinaldi ◽  
Rudolf Kaaks ◽  
...  

Abstract Background Colorectal cancer represents a major public health concern and there is a worrying tendency of increasing incidence rates among younger people in the last decades. Risk stratification of high-risk individuals may aid targeted disease prevention. We therefore aimed to evaluate the predictive value of a wide range of lifestyle and biomarker variables using data within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods A range of lifestyle, anthropometric and dietary variables in 329,885 participants in the EPIC cohort were evaluated as potential predictors for risk of colorectal cancer over 10 years. Biomarker measurements of 41 parameters were available for 1,320 CRC cases and 1,320 controls selected using incidence density matching. Best sets of predictors were selected using elastic net regularization with bootstrapping. Random survival forest was applied as a novel technique to validate the set of selected predictors taking variable interactions into account. Results The results suggested a set of lifestyle factors including age, waist circumference, height, smoking, alcohol consumption, physical activity, vegetables, dairy products, processed meat, and sugar and confectionary that showed good discrimination (Harrell's C-index: 0.710) and excellent calibration. The analyses further revealed a set of biomarkers that increased the predictive performance beyond age, sex and lifestyle factors. Conclusions Risk prediction models based on lifestyle and biomarker data may prove useful in the identification of individuals at high risk for colorectal cancer. Key messages Risk prediction models incorporating lifestyle and biomarker data could contribute to developing strategies for targeted colorectal cancer prevention.


2011 ◽  
Vol 21 (3) ◽  
pp. 398-410 ◽  
Author(s):  
Aung Ko Win ◽  
Robert J. MacInnis ◽  
John L. Hopper ◽  
Mark A. Jenkins

2015 ◽  
Vol 9 (1) ◽  
pp. 13-26 ◽  
Author(s):  
Juliet A. Usher-Smith ◽  
Fiona M. Walter ◽  
Jon D. Emery ◽  
Aung K. Win ◽  
Simon J. Griffin

2020 ◽  
Vol 122 (10) ◽  
pp. 1572-1575
Author(s):  
J. A. Usher-Smith ◽  
A. Harshfield ◽  
C. L. Saunders ◽  
S. J. Sharp ◽  
J. Emery ◽  
...  

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Tom G. S. Williams ◽  
Joaquín Cubiella ◽  
Simon J. Griffin ◽  
Fiona M. Walter ◽  
Juliet A. Usher-Smith

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e23025-e23025
Author(s):  
Shabbir M.H. Alibhai ◽  
Patrick Jung ◽  
Zuhair Alam ◽  
Lily Yeung ◽  
Uzair Malik ◽  
...  

e23025 Background: Older adults with cancer are at increased risk of delirium given their advanced age, multiple comorbidities and medications, prevalence of cognitive impairment, and possibly cancer treatment. Awareness of such risks and interventions to prevent or treat delirium is important to clinicians and to provide high quality care. However, there is scant published information on the risks of delirium with chemotherapy or evidence-based approaches to prevent or treat it. We performed a scoping review to summarize the available evidence. Methods: We conducted a scoping review using the framework of Arksey and O’Malley. We systematically searched peer-reviewed journal articles in English, French, and German from Medline, Embase, PsychINFO, CINAHL Plus, and Cochrane Central from inception until January 2017 to identify studies that examined delirium in patients receiving chemotherapy. We also attempted to identify any studies that reported on multivariable delirium risk prediction models and any clinical trials that examined prevention or treatment of delirium. Article titles and abstracts as well as full text articles were reviewed using Covidence software by two or more reviewers independently. Similarly, data extraction was performed by two independent reviewers. Results: A total of 21,678 titles and abstracts were screened, and 1,166 full-text articles were reviewed. Nineteen articles with varying study designs (retrospective administrative databases to clinical trials) reported on delirium using an acceptable diagnostic standard. Sample sizes varied from 15 to over 21,000. No one tumour site or treatment protocol constituted the majority of studies. The incidence of delirium ranged from 0 to 51% (mean 13.5%). The time course of delirium relative to the cycle of chemotherapy was inconsistently reported. No studies reported on risk prediction models for delirium, and no intervention studies to prevent or treat delirium were identified. An additional 109 studies reported on outcomes that could be part of the delirium syndrome but did not meet even our broad inclusion criteria (e.g. cognitive disturbance). Conclusions: Delirium may occur in over 1 in 8 older adults receiving chemotherapy, although there were substantial limitations in reported studies. This scoping review highlights the dearth of knowledge in the area, particularly for risk factors, prevention, and treatment, and emphasizes the need for high-quality studies examining these important outcomes in the oncology setting.


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