Breast Cancer Incidence Among Asian American Women in New York City: Disparities in Screening and Presentation. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Asian American (AsAm) women have some of the lowest rates of up-to-date breast cancer screening, and lack of disaggregated racial/ethnic data can mask disparities. We evaluated presentation patterns among AsAms at two hospitals with distinct communities: New York Presbyterian-Queens (NYPQ), in Flushing, Queens and Weill Cornell Medical Center (WCM), on the Upper East Side (UES) neighborhood of Manhattan. PATIENTS AND METHODS: Patients with newly diagnosed breast cancer between January 2019 and December 2022 were identified using a prospective database and clinical data collected. Patients were categorized as self-reported Asian versus Non-Asian. The Asian group was disaggregated as Chinese-Asian versus Other-Asian. Physician workforce data were obtained from public records. RESULTS: A total of 3546 patients (1162 NYPQ, 2384 WCM) were included. More NYPQ patients identified as Asian compared with WCM (49 vs. 14%, p < 0.001). Asian patients were mostly East Asian Chinese (NYPQ 61%, WCM 53%). More Chinese patients at NYPQ reported Chinese as their preferred language (81 vs. 33%, p < 0.001). Greatest differences of screen-detected disease frequency were seen between NYPQ and WCM Chinese patients (75 vs. 59%, p < 0.001). Eighty percent of NYPQ Chinese patients presented with stage 0/I disease versus 69% at WCM (p = 0.007), a difference not observed between Other-Asian patients (75% NYPQ, 68% WCM, p = 0.095). 3% of UES physicians versus 16% in Flushing reported speaking Chinese. CONCLUSIONS: Chinese patients residing in a neighborhood with more Chinese-speaking physicians more frequently presented with screen-detected, early-stage breast cancer. Stage distribution differences were not apparent among the aggregated pool of Other-Asian patients, suggesting cancer disparities may be masked when ethnic groups are studied in aggregate.

publication date

  • December 6, 2023

Research

keywords

  • Breast Neoplasms

Identity

Digital Object Identifier (DOI)

  • 10.1245/s10434-023-14640-8

PubMed ID

  • 38055093