ArticleSSM - population health2020
Towards precision public health: Geospatial analytics and sensitivity/specificity assessments to inform liver cancer prevention.
Article in SSM - population health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Neighborhood Factors Related to Cancer Screening in Texas: A Spatioecological Study.American journal of preventive medicine · 2025Article
- Reducing Breast Cancer Disparities with Precision Public Health: A New Strategy to Improve Prevention and Advance Health Equity in Delaware Hotspots.Delaware journal of public health · 2024Article
- A Novel Approach for Conducting a Catchment Area Analysis of Breast Cancer by Age and Stage for a Community Cancer Center.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024Article
- Effect of neighborhood and individual-level socioeconomic factors on breast cancer screening adherence in a multi-ethnic study.BMC public health · 2024Article
- Data-driven insights into neighborhood adherence to cancer prevention guidelines in Philadelphia.PloS one · 2024Article
- Tools to Measure the Impact of Structural Racism and Discrimination on Gastrointestinal and Hepatology Disease Outcomes: A Scoping Review.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2023Article
- Actionable Solutions to Achieve Health Equity in Chronic Liver Disease.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2023Review
- Data Science and Precision Oncology Nursing: Creating an Analytic Ecosystem to Support Personalized Supportive Care across the Trajectory of Illness.Seminars in oncology nursing · 2023Article
- Feasibility of visualizing cancer incidence data at sub-county level: Findings from 21 National Program of Cancer Registries.Spatial and spatio-temporal epidemiology · 2023Article
- The Geographic Context of Racial Disparities in Aggressive Endometrial Cancer Subtypes: Integrating Social and Environmental Aspects to Discern Biological Outcomes.International journal of environmental research and public health · 2022Article
- Racial disparities in triple negative breast cancer: toward a causal architecture approach.Breast cancer research : BCR · 2022Article
- Investigating Health Context Using a Spatial Data Analytical Tool: Development of a Geospatial Big Data Ecosystem.JMIR medical informatics · 2022Article
- A Population Health Assessment in a Community Cancer Center Catchment Area: Triple-Negative Breast Cancer, Alcohol Use, and Obesity in New Castle County, Delaware.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022Article
- Spatial epidemiologic analysis of the liver cancer and gallbladder cancer incidence and its determinants in South Korea.BMC public health · 2021Article
- Modeling Community Health with Areal Data: Bayesian Inference with Survey Standard Errors and Spatial Structure.International journal of environmental research and public health · 2021Article
- Effect of Neighborhood and Individual-Level Socioeconomic Factors on Colorectal Cancer Screening Adherence.International journal of environmental research and public health · 2021Article
- Liver Cancer Incidence and Area-Level Geographic Disparities in Pennsylvania-A Geo-Additive Approach.International journal of environmental research and public health · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
objectivesLiver cancer (LC) continues to rise, partially due to limited resources for prevention. To test the precision public health (PPH) hypothesis that fewer areas in need of LC prevention could be identified by combining existing surveillance data, we compared the sensitivity/specificity of standard recommendations to target geographic areas using U.S. Census demographic data only (percent (%) Hispanic, Black, and those born 1950-1959) to an alternative approach that couples additional geospatial data, including neighborhood socioeconomic status (nSES), with LC disease statistics.
methodsPennsylvania Cancer Registry data from 2007-2014 were linked to 2010 U.S. Census data at the Census tract (CT) level. CTs in the top 80th percentile for 3 standard demographic variables, %Hispanic, %Black, %born 1950-1959, were identified. Spatial scan statistics (SatScan) identified CTs with significantly elevated incident LC rates (p-value<0.05), adjusting for age, gender, diagnosis year. Sensitivity, specificity, and positive predictive value (PPV) of a CT being located in an elevated risk cluster and/or testing positive/negative for at least one standard variable were calculated. nSES variables (deprivation, stability, segregation) significantly associated with LC in regression models (p < 0.05) were systematically evaluated for improvements in sensitivity/specificity.
results9,460 LC cases were diagnosed across 3,217 CTs. 1,596 CTs were positive for at least one of 3 standard variables. 5 significant elevated risk clusters (CTs = 402) were identified. 324 CTs were positive for a high risk cluster AND standard variable (sensitivity = 92%; specificity = 37%; PPV = 17.4%). Incorporation of 3 new nSES variables with one standard variable (%Black) further improved sensitivity (93%), specificity (62.9%), and PPV (26.3%).
conclusionsWe introduce a quantitative assessment of PPH by applying established sensitivity/specificity assessments to geospatial data. Coupling existing disease cluster and nSES data can more precisely identify intervention targets with a liver cancer burden than standard demographic variables. Thus, this approach may inform prioritization of limited resources for liver cancer prevention.
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.