ABSTRACT
BACKGROUND: Black individuals in the United States (US) have a higher incidence of and mortality from colorectal cancer (CRC) compared to other racial groups, and CRC is the second leading cause of death among Hispanic/Latino populations in the US. Patient navigation is an evidence-based approach to narrow inequities in cancer screening among Black and Hispanic/Latino patients. Despite this, limited healthcare systems have implemented patient navigation for screening at scale. METHODS: We are conducting a stepped-wedge cluster randomized trial of 15 primary care clinics with six steps of six-month duration to scale a patient navigation program to improve screening rates among Black and Hispanic/Latino patients. After six months of baseline data collection with no intervention we will randomize clinics, whereby three clinics will join the intervention arm every six months until all clinics cross over to intervention. During the intervention roll out we will conduct training and education for clinics, change infrastructure in the electronic health record, create stakeholder relationships, assess readiness, and deliver iterative feedback. Framed by the Practical, Robust Implementation Sustainment Model (PRISM) we will focus on effectiveness, reach, provider adoption, and implementation. We will document adaptations to both the patient navigation intervention and to implementation strategies. To address health equity, we will engage multilevel stakeholder voices through interviews and a community advisory board to plan, deliver, adapt, measure, and disseminate study progress. Provider-level feedback will include updates on disparities in screening orders and completions. DISCUSSION: Primary care clinics are poised to close disparity gaps in CRC screening completion but may lack an understanding of the magnitude of these gaps and how to address them. We aim to understand how to tailor a patient navigation program for CRC screening to patients and providers across diverse clinics with wide variation in baseline screening rates, payor mix, proximity to specialty care, and patient volume. Findings from this study will inform other primary care practices and health systems on effective and sustainable strategies to deliver patient navigation for CRC screening among racial and ethnic minorities. TRIAL REGISTRATION: NCT06401174.
ABSTRACT
SUMMARY: Copy number variants (CNVs) are a major source of genetic variation. Comparing CNVs between samples is important in elucidating their potential effects in a wide variety of biological contexts. HD-CNV (hotspot detector for copy number variants) is a tool for downstream analysis of previously identified CNV regions from multiple samples, and it detects recurrent regions by finding cliques in an interval graph generated from the input. It creates a unique graphical representation of the data, as well as summary spreadsheets and UCSC (University of California, Santa Cruz) Genome Browser track files. The interval graph, when viewed with other software or by automated graph analysis, is useful in identifying genomic regions of interest for further study. AVAILABILITY AND IMPLEMENTATION: HD-CNV is an open source Java code and is freely available, with tutorials and sample data from http://daleylab.org. CONTACT: jcamer7@uwo.ca
