Classification Tree Analysis to Enhance Targeting for Cancer Screening Programs

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DESCRIPTION (provided by applicant): Evidence of disparities in the utilization of cancer screening tests plays a central role in the nation's total set of efforts for cancer prevention and control. The Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) are two key resources. Identifying groups in the population who are at risk of lower screening utilization typically starts with univariate analyses of associations between a set of potential covariates and utilization rates of a screening test, followed by multivariable analysis, most often using logistic regression, to determine the final set of variables that achieve statistical significance. These statistically significant variables are then translated into population groups who need targeted interventions to reduce the observed disparities. Those interventions have the objective of providing resources necessary for improving access to, and utilization of, screening tests. This proposed research is intended to examine the potential for Classification Analysis to inform the process of identifying at-risk groups for screening programs and services. Classification Analysis uses progressive segmentation of a dataset (i.e., recursive partitioning), to identify groups with higher versus lower rates on a dependent variable (e.g., cancer screening). Each of these groups is defined by a specific combination of characteristics. The Specific Aims of this two-year, secondary analysis R21 proposal are: Aim 1.) To apply classification methods to the 2006 and 2008 BRFSS, and to the 2005 and 2008 NHIS, in order to identify groups in the population at risk of lower screening utilization based on multivariable classification. Screening domains will be for breast, cervical, colorectal, and prostate cancer. Aim 2.) To examine the results obtained across classification methods, in order to better understand how best to capitalize on the potential of using classification methods to identify groups in the population at-risk of low cancer screening. Aim 3.) To use classification methods to investigate whether content from BRFSS state-optional modules can supplement information from the core BRFSS to identify groups likely to have low utilization and complex service needs. Multivariable classification of at-risk groups, informed by CTA methods, could enhance the targeting of audiences for the important pre-intervention tasks of needs assessment, barrier/facilitator identification, and marshalling the resources needed to improve the screening status of those groups. PUBLIC HEALTH RELEVANCE: National-level surveys are used to identify groups in the population who need extra resources and services in order to improve their utilization of cancer screening tests. It is important to continue to develop ways of identifying these groups, so that those at risk of low use can be targeted for screening programs and services. This research will examine how "classification analysis" methods can improve the identification of groups in the population who have low utilization of cancer screening tests (breast, colorectal, cervical, prostate).