Challenges With Colorectal Cancer Family History Assessment-Motivation to Translate Polygenic Risk Scores Into Practice

Family History of Colorectal Cancer and the Risk of Colorectal Neoplasia: A Systematic Review and Meta-Analysis

INTRODUCTION

Although there is enough pooled evidence supporting the positive association between family history of colorectal cancer (CRC) in first-degree relatives (FDRs) and the risk of CRC, synthesized data on its association with the risk of other colorectal neoplasia are lacking. Therefore, we aimed to systematically assess this issue.

METHODS

We searched PubMed, Web of Science, and Embase from database inception through May 9, 2024, to identify observational studies investigating the association between family history of CRC in FDRs and the risk of colorectal neoplasia (excepting CRC). Adenoma, nonadvanced adenoma (NAA), advanced adenoma (AA), and advanced neoplasia (AN) were further chosen as main outcomes because of data availability. Random-effects model was used for data synthesis. Subgroup meta-analyses were performed to evaluate the robustness of results.

RESULTS

Of 5,172 initial records screened, 75 studies (with 931,515 participants) were identified for analysis. Family history of CRC in FDRs was associated with increased risk of adenoma (pooled odds ratio [OR] 1.67, 95% confidence interval [CI] 1.46-1.91), NAA (pooled OR 1.35, 95% CI 1.21-1.51), AA (pooled OR 1.66, 95% CI 1.46-1.88), and AN (pooled OR 1.58, 95% CI 1.44-1.73). The positive associations persisted in all examined subgroups. The risk of adenoma (pooled OR 4.18, 95% CI 1.76-9.91), AA (pooled OR 2.42, 95% CI 1.72-3.40), and AN (pooled OR 2.00, 95% CI 1.68-2.38) was more evident among individuals with 2 or more affected FDRs.

DISCUSSION

Family history of CRC is associated with increased risk of adenoma, NAA, AA, and AN totally, and in all available subgroups. The findings further strengthen the necessity and importance of an intensified screening strategy for individuals with a positive family history of CRC, which is very useful for related health resource allocation and policymaking.

Cost-effectiveness of population-wide genomic screening for Lynch Syndrome and polygenic risk scores to inform colorectal cancer screening

PURPOSE

Genomic screening to identify individuals with Lynch Syndrome (LS) and those with a high polygenic risk score (PRS) promises to personalize colorectal cancer (CRC) screening. Understanding its clinical and economic impact is needed to inform screening guidelines and reimbursement policies.

METHODS

We developed a Markov model to simulate individuals over a lifetime. We compared LS+PRS genomic screening with standard of care (SOC) for a cohort of US adults at age 30. The Markov model included health states of no CRC, CRC stages (A-D), and death. We estimated incidence, mortality, and discounted economic outcomes of the population under different interventions.

RESULTS

Screening 1000 individuals for LS+PRS resulted in 1.36 fewer CRC cases and 0.65 fewer deaths compared with SOC. The incremental cost-effectiveness ratio was $124,415 per quality-adjusted life year; screening had a 69% probability of being cost-effective using a willingness-to-pay threshold of $150,000/quality-adjusted life year . Setting the PRS threshold at the 90th percentile of the LS+PRS screening program to define individuals at high risk was most likely to be cost-effective compared with 95th, 85th, and 80th percentiles.

CONCLUSION

Population-level LS+PRS screening is marginally cost-effective, and a threshold of 90th percentile is more likely to be cost-effective than other thresholds.

Advancing early onset colorectal cancer research: research advocacy, health disparities, and scientific imperatives

Early onset colorectal cancer (EOCRC) emerged as the fourth foremost contributor to cancer-related mortality among both genders in the late 1990s. Presently, EOCRC (<50) ranks as the leading cause of cancer mortality in men and the second leading cause in women within the United States. Similar trends are now also evident globally, particularly in developed countries. Furthermore, there is strong evidence confirming that health disparities persist in the diagnosis and treatment of EOCRC, with signs indicating that these gaps may worsen in specific cases. These alarming trends highlight the critical need for research to inform evidence-based interventions to reduce the burden of EOCRC globally. Fight Colorectal Cancer (Fight CRC) is the leading patient advocacy group in the United States providing information on colon and rectal cancer research, prevention, treatment, and policy. It is the opinion of Fight CRC that an international, coordinated effort with the medical, research, scientific, advocacy, industry and funding community is needed to advance impactful research. Fight CRC, in partnership with José Perea, MD, PhD, of the Institute of Biomedical Research of Salamanca (IBSAL) in Spain, and partners, are working together to address this global phenomenon and are presenting a multi-faceted research approach to move the field forward.

Colorectal Cancer Risk Assessment and Precision Approaches to Screening: Brave New World or Worlds Apart?

Current colorectal cancer (CRC) screening recommendations take a "one-size-fits-all" approach using age as the major criterion to initiate screening. Precision screening that incorporates factors beyond age to risk stratify individuals could improve on current approaches and optimally use available resources with benefits for patients, providers, and health care systems. Prediction models could identify high-risk groups who would benefit from more intensive screening, while low-risk groups could be recommended less intensive screening incorporating noninvasive screening modalities. In addition to age, prediction models incorporate well-established risk factors such as genetics (eg, family CRC history, germline, and polygenic risk scores), lifestyle (eg, smoking, alcohol, diet, and physical inactivity), sex, and race and ethnicity among others. Although several risk prediction models have been validated, few have been systematically studied for risk-adapted population CRC screening. In order to envisage clinical implementation of precision screening in the future, it will be critical to develop reliable and accurate prediction models that apply to all individuals in a population; prospectively study risk-adapted CRC screening on the population level; garner acceptance from patients and providers; and assess feasibility, resources, cost, and cost-effectiveness of these new paradigms. This review evaluates the current state of risk prediction modeling and provides a roadmap for future implementation of precision CRC screening.

Genetic risk, incident colorectal cancer, and the benefits of adhering to a healthy lifestyle: A prospective study using data from UK Biobank and FinnGen

Background

Genetic factors increase the individual risk of colorectal cancer (CRC); however, the extent to which a healthy lifestyle can offset increased genetic risk is unknown. This study investigated whether a healthy lifestyle is associated with lower CRC risk, regardless of genetic risk.

Methods

We recruited 390,365 participants without cancer at baseline (2006-2010) from the UK Biobank. The primary outcome was CRC incidence. A healthy lifestyle score constructed using 16 factors of six dimensions (smoking, drinking, body mass index, diet, exercise, and sleep) was categorized into three risk categories: favorable, intermediate, and unfavorable. To calculate the polygenic risk scores (PRSs) of UK Biobank participants, we extracted 454,678 single nucleotide polymorphisms (SNPs) from the UK Biobank and FinnGen Biobank after quality control. Cox proportional hazards regression was performed to evaluate the associations and was expressed as hazard ratios (HRs) with 95% confidence intervals (CIs).

Results

During a median follow-up of 10.90 years, 4,090 new CRC cases were reported in the UK Biobank. The "best-fit" PRSs were constructed using 59 SNPs based on the UK Biobank cohort and FinnGen genome-wide association study summary data (R² = 0.23%) and were divided into low (lowest quintile), intermediate (including second-fourth quintile), and high (highest quintile) genetic risk categories. The multivariate-adjusted Cox model revealed that participants with favorable lifestyles had HRs of 0.66 (95% CI = 0.60-0.72) for developing CRC vs. those with unfavorable lifestyles; low genetic risk was associated with a decreased risk of CRC (HR = 0.67, 95% CI =0.61-0.74) compared with those with high genetic risk. The HRs for low genetic risk participants with favorable lifestyles were 0.44 (95% CI =0.36-0.55) vs. participants with high genetic risk and unfavorable lifestyles. Among the participants with low, intermediate, or high genetic risk, the HRs of favorable vs. unfavorable lifestyles were 0.74, 0.64, and 0.72 (all p< 0.05).

Conclusions

Low genetic risk and a favorable lifestyle were significantly associated with a decreased risk of CRC. A favorable lifestyle was associated with a lower CRC risk, regardless of genetic risk.

Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention

Genome-wide association studies (GWASs) have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers. The genetic variants associated with a cancer can be combined into a polygenic risk score (PRS), which captures part of an individual's genetic susceptibility to cancer. Recently, PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer, which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk. In this context, we provide an overview of the major discoveries from cancer GWASs. We then review the methodologies used for PRS construction, and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors. Potential utility of PRSs in cancer risk prediction, screening, and precision prevention are illustrated. Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed.