Is there evidence that we should screen the general population for Lynch syndrome with genetic testing? A systematic...

The emerging dual imperatives of personalized medicine and technologic advances make population screening for preventable conditions resulting from genetic alterations a realistic possibility. Lynch syndrome is a potential screening target due to its prevalence, penetrance, and the availability of well-established, preventive interventions. However, while population screening may lower incidence of preventable conditions, implementation without evidence may lead to unintentional harms. We examined the literature to determine whether evidence exists that screening for Lynch-associated mismatch repair (MMR) gene mutations leads to improved overall survival, cancer-specific survival, or quality of life. Documenting evidence and gaps is critical to implementing genomic approaches in public health and guiding future research.

Our 2014-2015 systematic review identified studies comparing screening with no screening in the general population, and controlled studies assessing analytic validity of targeted next-generation sequencing, and benefits or harms of interventions or screening. We conducted meta-analyses for the association between early or more frequent colonoscopies and health outcomes.

Twelve studies met our eligibility criteria. No adequate evidence directly addressed the main question or the harms of screening in the general population. Meta-analyses found relative reductions of 68% for colorectal cancer incidence (relative risk: 0.32, 95% confidence interval: 0.23-0.43, three cohort studies, 590 participants) and 78% for all-cause mortality (relative risk: 0.22, 95% confidence interval: 0.09-0.56, three cohort studies, 590 participants) for early or more frequent colonoscopies among family members of people with cancer who also had an associated MMR gene mutation.

Inadequate evidence exists examining harms and benefits of population-based screening for Lynch syndrome. Lack of evidence highlights the need for data that directly compare benefits and harms.