Location, race and insurance status play key role in early-stage versus late-stage cancer diagnosis

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Location, race and insurance status play key role in early-stage versus late-stage cancer diagnosis
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Location, race and insurance status play a significant part in the odds of a patient being diagnosed with early-stage or late-stage cancer, according to a detailed medical records analysis of more than 94,000 patients with cancer by researchers at the Johns Hopkins Bloomberg School of Public Health and the Johns Hopkins Kimmel Cancer Center.

May 22 2024Johns Hopkins Medicine Location, race and insurance status play a significant part in the odds of a patient being diagnosed with early-stage or late-stage cancer, according to a detailed medical records analysis of more than 94,000 patients with cancer by researchers at the Johns Hopkins Bloomberg School of Public Health and the Johns Hopkins Kimmel Cancer Center.

Previous studies showed that patients who do not receive their first treatment at a CCC experience worse cancer outcomes. Investigators including Michael Desjardins, Ph.D., an assistant research professor of epidemiology and a core faculty member at the Spatial Science for Public Health Center at the Bloomberg School of Public Health; Frank Curriero, Ph.D., professor of epidemiology and director of the Spatial Science for Public Health Center; and William Nelson, M.D., Ph.D.

Non-Hispanic Black patients had higher odds of receiving a late-stage cancer diagnosis compared to average, even if they lived close to the Kimmel Cancer Center. That finding aligns with a body of work that finds lower odds of cancer survival for non-Hispanic Black patients, and it suggests that accessibility to health care is more complex than geographic distance alone.

Moving forward, we need to ask patients why they choose a particular cancer center for a diagnosis or a treatment. Maybe they can't afford the treatment at a certain location, or maybe they are seeking a specific late-stage cancer treatment. There are a lot of nuances we have to try to understand by combining spatial data sets with qualitative surveys."

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