ArticlePreventive medicine reports2021
Novel mapping methods to describe utilization of free breast cancer screening from a state program.
Article in Preventive medicine reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Utilization and outcomes of serial cervical cancer screening in a National Breast and Cervical Cancer Early Detection Program (NBCCEDP) in a non-Medicaid expansion state.Cancer causes & control : CCC · 2025Article
- Estimating uninsured and underinsured women eligible for Minnesota's Breast Cancer Screening Program.Cancer causes & control : CCC · 2024Article
- Breast Cancer Champions: a peer-to-peer education and mobile mammography program improving breast cancer screening rates for women of African heritage.Cancer causes & control : CCC · 2023Article
- Estimating Uninsured and Underinsured Women Eligible for Minnesota's Breast Cancer Screening Program.Research square · 2023Article
- The effect of pre-aggregation scale on spatially adaptive filters.Spatial and spatio-temporal epidemiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
introductionThe National Breast and Cervical Cancer Early Detection Program (NBCCEDP) is a cancer screening program whose mission is to reduce cancer morbidities for uninsured and underinsured women. A primary activity is to connect women to breast cancer screening. The eligible population and utilization of NBCCEDP screening services have never been quantified at a sub-state level, which hampers effective program evaluation. Here, the Minnesota NBCCEDP, "Sage", serves as a case study to demonstrate novel spatial analysis methods that depict variation of screening rates at the local level.
methodsWomen who received breast cancer screening through Sage between 2011 and 2015 were geocoded (N = 74,712 screenings); analysis occurred between 2017 and 2019. We determine an eligible population using a synthetic population dataset that provides geographic residence and demographic information. We introduce a novel spatial analysis technique, spatially adaptive filters (SAFs), to create a utilization map of Sage breast screening services by Minnesota women.
resultsBetween 2011 and 2015, an average of 36,979 women per year were eligible for NBCCEDP breast cancer screening services, representing 3% of the Minnesota female population 40 and older. For Minnesota NBCCEDP eligible women, the state average breast cancer screening utilization rate was 37.2%, but varied considerably by local regions within the state (range 0% to 131%, SD = 18.7%).
conclusionsThis geospatial model estimated screening service utilization at the local level and enables Minnesota's Sage program to target specific areas they have yet to reach. Similar programs could employ this model to direct program activities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.