ArticleCancer research communications2022
Delineation of Cancer Service Areas Anchored by Major Cancer Centers in the United States.
Article in Cancer research communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 8 citations in OpenAlex.
- Geospatial Analysis of Commission on Cancer-Accredited Centers Within Cancer Care Utilization-Based Catchment Areas.JCO clinical cancer informatics · 2025Article
- Application of Community Detection Methods to Identify Emergency General Surgery-Specific Regional Networks.JAMA network open · 2024Article
- Measuring Spatial Access of Vulnerable Population to HIV Testing Facilities in the Baton Rouge Metropolitan Statistical Area, Louisiana.AIDS and behavior · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Defining a reliable geographic unit pertaining to cancer care is essential in its assessment, planning, and management. This study aims to delineate and characterize the cancer service areas (CSA) accounting for the presence of major cancer centers in the United States. We used the Medicare enrollment and claims from January 1, 2014 to September 30, 2015 to build a spatial network from patients with cancer to cancer care facilities that provided inpatient and outpatient care of cancer-directed surgery, chemotherapy, and radiation. After excluding those without clinical care or outside of the United States, we identified 94 NCI-designated and other academic cancer centers from the members of the Association of American Cancer Institutes. By explicitly incorporating existing specialized cancer referral centers, we refined the spatially constrained Leiden method that accounted for spatial adjacency and other constraints to delineate coherent CSAs within which the service volumes were maximal but minimal between them. The derived 110 CSAs had a high mean localization index (LI; 0.83) with a narrow variability (SD = 0.10). The variation of LI across the CSAs was positively associated with population, median household income, and area size, and negatively with travel time. Averagely, patients traveled less and were more likely to receive cancer care within the CSAs anchored by cancer centers than their counterparts without cancer centers. We concluded that CSAs are effective in capturing the local cancer care markets in the United States. They can be used as reliable units for studying cancer care and informing more evidence-based policy. Significance: Using the most refined network community detection method, we can delineate CSAs in a more robust, systematic, and empirical manner that incorporates existing specialized cancer referral centers. The CSAs can be used as a reliable unit for studying cancer care and informing more evidence-based policy in the United States. The cross-walk tabulation of ZIP code areas, CSAs, and related programs for CSAs delineation are disseminated for public access.
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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.