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10.1200/CCI-25-00132

http://scihub22266oqcxt.onion/10.1200/CCI-25-00132
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41348989!?!41348989

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pmid41348989      JCO+Clin+Cancer+Inform 2025 ; 9 (?): e2500132
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  • Development of a Composite Measure to Identify Priority Areas of Need for Cancer Screening Interventions #MMPMID41348989
  • Karp DN; Hamade K; McNair CM; Leader AE
  • JCO Clin Cancer Inform 2025[Dec]; 9 (?): e2500132 PMID41348989show ga
  • PURPOSE: Cancer centers and health systems are tasked with deciding where to deploy community interventions to reduce the burden of cancer within their catchment areas. Few methods exist to prioritize communities in a systematic manner, considering features of individuals, populations, systems, and policies. We developed a geographically informed index to prioritize census tracts based on community need, with an initial focus on identifying communities in need of breast cancer screening (BCS) interventions. METHODS: This study used publicly available data to select variables known to be associated with disparities in BCS rates. Variables were identified from five categories: economic stability, education access and quality, neighborhood and built environment, social and community context, and health status and health care access and quality. Data were analyzed at the census tract level across the Sidney Kimmel Comprehensive Cancer Center catchment (N = 1,216). Principal component analysis was applied to 23 variables, and five principal components were selected to construct a composite measure using a weighted sum. The resulting index values were used to stratify the data set for further analysis and mapped for visualization. RESULTS: The analysis produced the Community Need Priority Index (CNPI)-BCS, with values ranging from 0 to 1 (mean, 0.259; standard deviation [SD], 0.161). The top quintile (Q5, n = 243) represented the highest-need communities. Q5 tracts were primarily concentrated in Philadelphia, Camden, and Delaware counties. Philadelphia County had the highest average (mean, 0.364; SD, 1.78) and the most tracts in the top quintile (45%, n = 175). Montgomery county had the lowest average (mean, 0.169; SD, 0.092). CONCLUSION: This novel methodological approach considered the complex nature of multiple, intersectional barriers to good health to identify priority areas of need within cancer center catchment areas.
  • |*Breast Neoplasms/diagnosis/epidemiology[MESH]
  • |*Early Detection of Cancer/methods[MESH]
  • |*Health Priorities[MESH]
  • |*Neoplasms/diagnosis/epidemiology[MESH]
  • |Female[MESH]
  • |Health Services Accessibility[MESH]
  • |Healthcare Disparities[MESH]
  • |Humans[MESH]


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