TAILIEUCHUNG - Polygenic risk prediction models for colorectal cancer: A systematic review

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. | Sassano et al. BMC Cancer 2022 22 65 https s12885-021-09143-2 RESEARCH Open Access Polygenic risk prediction models for colorectal cancer a systematic review Michele Sassano1 Marco Mariani1 Gianluigi Quaranta1 2 Roberta Pastorino2 and Stefania Boccia1 2 Abstract Background Risk prediction models incorporating single nucleotide polymorphisms SNPs could lead to individual- ized 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 accu- racy 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 pre- diction. 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 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 and no correlation between the number of SNPs and AUC improvement p . Pooled AUC improvement was 95 CI 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

• Y khoa - Dược
• BMC Cancer
• Colorectal cancer
• Prediction models
• Single nucleotide polymorphisms
• Genetic risk score
• Meta analysis
• Cancer patient pathways
• Lung cancer
• Breast cancer
• Prostate cancer
• Ovarian cancer
• Cancer detection
• Ovarian cancer symptoms
• Ovarian cancer signs
• Ovarian cancer tests
• Cancer biomarkers
• Pediatric cancer
• Familial cancer predisposition
• Hereditary cancer syndrome
• Genetic cancer susceptibility
• Advanced cancer
• Biliary tract cancer
• Multimodal intervention
• Pancreatic cancer
• Physical activity
• Breast cancer screening
• Familial breast cancer
• Young breast cancer survivors
• High risk relatives
• Randomized trial
• Childhood cancer
• Childhood cancer survivor
• Thyroid cancer screening
• Secondary cancer
• Cancer screening
• Community awareness
• Cancer education
• Cervical cancer
• Prior cancer
• Cancer survivors
• Cancer registry
• Second cancer
• Surgical oncology
• Cancer imaging
• Radiation oncologists
• Medical oncologists
• Oesophagogastric cancer
• Liver cancer
• Hepatobiliary cancer
• Multidisciplinary rehabilitation
• EGFR mutation
• Family history of cancer
• Inherited susceptibility
• Cancer predisposition genes
• Lung cancer aetiology
• Cancer stem cells
• Oct4 overexpressing lung cancer
• Human lung cancer xenograft model
• Disease free survivals
• Cancer hallmarks
• Cancer genesis
• Defiant disease
• Mutational signature
• Cancer diagnosis
• Cancer genomics
• Molecular medicine
• Whole genome sequencing
• Cancer susceptibility gene
• Breast cancer prognosis
• Next generation sequencing
• Quality of care
• Quality indicators
• Shifting cancer care
• German cancer society
• Colorectal cancer screening
• Stomach cancer screening
• Lung cancer survivor
• Physician recommendation
• Total number of lymph nodes
• Lymph node ratio
• Left colon cancer
• Right colon cancer
• Overall survival
• Cumulative incidence
• Esophageal cancer
• Head and neck cancer
• Metachronous cancer
• Young onset
• Reproductive cancer
• Risk factor
• Early detection of cancer
• Gastric cancer incidence
• Population based specialized registry
• Gastric cancer survival
• Gastric cancer clinical characteristics
• Gastric cancer pathological characteristics
• Lung Cancer Screening
• Racial disparities
• Lung Cancer diagnosis
• Screening adherence
• Second primary colorectal cancer
• Standardized incidence ratio
• Left sided colon cancer
• Right sided colon cancer
• Quality of cancer care
• Population based study