"Cancer Center Catchment Area Assessment"-Letter.

Abstract

We thank Leader and colleagues (1) for the first published article that explores the geographic coverage of U.S.-based cancer centers’ catchment areas. The use of county-level data and aggregated cancer statistics provides some insights regarding coverage of the U.S. population by cancer centers; however, more granular data are required for a fuller understanding of coverage gaps, as mentioned in the article. We share two relevant observations here.First, the study found gaps in coverage in some states with rural populations but results also showed that most of the counties with balanced or overcoverage (population density overlay score > = 0) belong to the lower quintiles of population density, suggesting that the use of population density may downplay the challenges that come with reaching rural populations (2). Conversely, 48 of the 50 most densely populated counties exhibited undercoverage (population density overlay score < 0). As with the oversimplification of coverage in rural counties, using population density to assess coverage in densely populated and diverse catchment areas is not sufficient to fully characterize the reach of cancer centers, where neighborhood data are required.Similarly, the need for cancer incidence and mortality data disaggregated by race/ethnicity, sexual orientation, and gender identity (3) is generally recognized but still lacking. In our own analysis of the Centers for Disease Control 2014–2018 county-level combined data that were used in the study (excluded counties in Kansas and Minnesota for which data were not available), we found, for example, that 2,335 U.S. counties were missing all-site incidence data for Asian/Pacific Islanders, and, when available, data for Asians and Pacific Islanders were aggregated despite disaggregation being the minimum standard for all Federal reporting purposes (4). We noted that 145 of these 2,335 counties are in the highest quartile of Asian American population size (mean Asian American population size: 3,702) and 141 of these counties are in the highest quartile of Native Hawaiian and Pacific Islander (NHPI) population size (mean NHPI population size: 345; ref. 5). The discrepancy was largest among American Indian/Alaska Native (AIAN): there were 2,462 counties without all-site incidence data specific for this group, even for 285 counties belonging to the highest quartile of AIAN population size (mean AIAN population size: 2,020). If our aim is to be able to measure potential future impact on our catchment area, we first have to advocate for the disaggregation of cancer data for minority populations who have been invisible in these data.No disclosures were reported.This work is supported by Cedars-Sinai Medical Center.