Variation in outcome reporting in studies of fertility-sparing surgery for cervical cancer: A systematic review.

BACKGROUND: Cervical cancer affects 3197 women in the UK, and 604 000 women worldwide annually, with peak incidence seen in women between 30 and 34 years of age. For many, fertility-sparing surgery is an appealing option where possible. However, absence of large-scale data, along with a notable variation in reported outcomes in relevant studies, may undermine future efforts for consistent evidence synthesis. OBJECTIVES: To systematically review the reported outcomes measured in studies that include women who underwent fertility-sparing surgery for cervical cancer and identify whether variation exists. SEARCH STRATEGY: We searched MEDLINE, EMBASE and CENTRAL from inception to February 2019. SELECTION CRITERIA: Randomised controlled trials, cohort and observational studies, and case studies of more than ten participants from January 1990 to date. DATA COLLECTION AND ANALYSIS: Study characteristics and all reported treatment outcomes. MAIN RESULTS: A total of 104 studies with a sum of 9535 participants were identified. Most studies reported on oncological outcomes (97/104), followed by fertility and pregnancy (86/104), postoperative complications (74/104), intra-operative complications (72/104) and quality of life (5/104). There was huge variation and heterogeneity in reported outcomes, with only 12% being good quality and 87% being of poor quality. CONCLUSIONS: There is significant heterogeneity in the reported outcomes. An agreed Core Outcome Set is necessary for future studies to effectively harmonise reported outcomes that are measurable and relevant to patients, clinicians and researchers. This systematic review sets the groundwork for the development of a Core Outcome Set for fertility-sparing surgery in cervical cancer.

Preventive population genomics: The model of BRCA related cancers.

Preventive population genomics offers the prospect of population stratification for targeting screening and prevention and tailoring care to those at greatest risk. Within cancer, this approach is now within reach, given our expanding knowledge of its heritable components, improved ability to predict risk, and increasing availability of effective preventive strategies. Advances in technology and bioinformatics has made population-testing technically feasible. The BRCA model provides 30 years of insight and experience of how to conceive of and construct care and serves as an initial model for preventive population genomics. Population-based BRCA-testing in the Jewish population is feasible, acceptable, reduces anxiety, does not detrimentally affect psychological well-being or quality of life, is cost-effective and is now beginning to be implemented. Population-based BRCA-testing and multigene panel testing in the wider general population is cost-effective for numerous health systems and can save thousands more lives than the current clinical strategy. There is huge potential for using both genetic and non-genetic information in complex risk prediction algorithms to stratify populations for risk adapted screening and prevention. While numerous strides have been made in the last decade several issues need resolving for population genomics to fulfil its promise and potential for maximizing precision prevention. Healthcare systems need to overcome significant challenges associated with developing delivery pathways, infrastructure expansion including laboratory services, clinical workforce training, scaling of management pathways for screening and prevention. Large-scale real world population studies are needed to evaluate context specific population-testing implementation models for cancer risk prediction, screening and prevention.