Table 6.
Studies examining risk-stratified guidelines and evidence-based recommendations
| Author(s) | Study design | Country | Recommendations |
|---|---|---|---|
| Avital et al. (2013) | Evidence-based guidelines | US | Race, SES and family history are important for future bowel screening risk stratification research |
| Jenkins et al. (2018) | Literature review | Australia | Separates screening guidance into the following categories: (1) Average-risk recommended screening every two years by iFOBT age 50–74 years; (2) moderate-risk due to family history recommended biennial iFOBT screening from age 40–49 years then colonoscopy every five years from age 50–74 years; (3) High-risk recommended biennial iFOBT from age 35–44 years then colonoscopy every five years from age 45 to 74 years |
| Geneve et al. (2019) | Commentary | US | Ethnicity should be included in risk-stratified bowel screening guidelines |
| Parkin et al. (2018) | Evidence-based guidelines | US | Individuals with a family history of CRC will need to start screening at an earlier age on the basis of category of risk |
| Imperiale and Monahan (2020) | Literature review | US | Future research should focus on validation of risk prediction models, conducting impact analyses via RCTs, and seek to understand patient/provider attitudes toward risk prediction models and how such tools are able to be integrated into health care systems |
| Sung et al. (2015) | Delphi study | Multi-country (14 Asian countries) | A risk-stratified scoring system is recommended for selecting high-risk patients for colonoscopy |
| Tejpar (2005) | Commentary | Belgium | Recommends early bowel screening for those with an elevated risk of CRC due to family history |
| Zali et al. (2016) | Mixed-methods | Multi-country (Canada, Australia and US) | Screening guidelines needs to be implemented into clinical practice to provide patient-specific advice on risk-based bowel screening |
| Bortniker and Anderson (2015) | Literature review | US | Current models have made some progress in discriminating high-risk groups, but work remains to be done to improve to improve the validity of them |
| Cooper et al. (2016) | Literature review | UK | Risk scoring systems based on a combination of FIT and other risk factors have been shown to improve the sensitivity of the predictive model |
| Huang et al. (2017) | Commentary | China |
Four recommendations: (1) The discriminatory capacity of predictive models needs to be enhanced and externally validated; (2) The development of affordable non-invasive biomarkers should be an important focus; (3) In order for risk-based screening to be efficient, the effectiveness and sustainability of health education about the various risk factors for CRC should be enhanced in order to heighten community awareness. Acceptability, perception, attitude, and satisfaction of risk-based screening should also be evaluated; (4) Cost-effectiveness analyses are needed in different settings |
| Hull (2020) | Commentary | Multi-country |
Five research priorities: (1) external validation of CRC risk prediction models; (2) evaluate risk prediction models on clinical decision-making and patient outcomes in multiple settings; (3) acceptability and feasibility of risk-stratified approaches to patents and healthcare practitioners; (4) modelling of optimal service delivery for screening and surveillance; (5) Artificial Intelligence and machine learning is needed to link large datasets to derive clinically useful prediction models |
| Lansdorp-Vogelaar (2021) | Literature review | Multi-country | Future research should investigate acceptability of risk-stratified screening as well as impact on costs and organisation. ‘Low hanging fruit’ include basing risk stratification on readily available information e.g. FIT. IT systems will need to be developed in a modular way |
| Lin (2012) | Literature review | Multi-country | Family history should be considered for more ‘aggressive’ screening regimes as there is a wealth of evidence on this and it appears to be cost-effective. Compliance with current guidelines is sub-optimal and may be affected by under-reporting |
| Wong et al. (2015) | Literature review | Multi-country | Future research should focus on external validation of the existing scoring systems, especially among populations with different characteristics. Current risk scoring systems could be refined by including genomics and other biomarkers such as genetic risk scores calculated using SNPs |
| Cenin et al. (2017) | Literature review | Australia | Evidence suggests that a risk-stratified approached which incorporate family history, age, gender, lifestyle, socioeconomic status and genetic profiling could improve CRC risk prediction |
| Fletcher (2008) | Commentary | US | Expert groups recommend that family history should be taken into account when choosing the age at which screening begins, the screening test, and the interval between tests. However, these recommendations are based on relatively weak evidence. In any case, family history of colorectal cancer is often not recorded in the medical record nor used in screening decisions |