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May 29, 2026Journal of Clinical Oncology0 citations

Analyzing county-level factors of oncology fellowship program development from 2015-2025.

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RCRyan James CrowleyNew York UniversityJLJag S. LallyUniversity of Rochester Medical CenterDKDavid M. KlineWake Forest University

Key Points

  • The aim is to examine urban-rural trends in newly created oncology fellowship programs and identify county-level factors influencing their establishment.
  • Cross-sectional analysis involving 3,211 US counties using data from 2015 and 2025.
  • Firth’s penalized logistic regression analyzed factors affecting new oncology fellowship program establishment.
  • County metrics derived from US Census data along with physician density calculations.
  • Fellowship programs increased from 140 in 2015 to 180 in 2025, with slots growing from 521 to 773 at a rate of 25.2 new slots per year.
  • Higher household median income significantly predicted new fellowship establishment (OR 1.62, 95% CI 1.25-2.06, p < 0.001).
  • Rurality significantly predicted no fellowship establishment (OR 0.04, 95% CI 0.01-0.14, p < 0.001).

Abstract

9003 Background: In the United States (US), access to oncology care varies geographically. One factor that may contribute to regional shortages is the distribution of oncology fellowship programs. We aimed to assess urban-rural trends in newly created oncology fellowship programs and to identify county-level factors associated with a higher likelihood of gaining a new oncology fellowship program. Methods: Data on all hematology/oncology and oncology fellowship positions in 2015 and 2025 were manually extracted from National Resident Matching Program (NRMP) data. A cross-sectional analysis was performed using data from 3,211 US counties to examine program development from 2015-2025. County metrics came from US Census data and physician density was calculated using the Doctors and Clinicians national downloadable file. A model was developed using Firth’s penalized logistic regression with the following predictors using 2015 data: oncologist density per 100,000 population, median household income, percentage of population with insurance, rurality (binary with rural county coded as 1), and state-level Medicaid expansion status in 2015 (binary with expansion state coded as 1). The outcome variable was counties that gained a new oncology fellowship program (n=44). Results: In 2015, there were 140 fellowship programs in the US with 1 program in a rural county (0.6%). By 2025, there were 180 fellowship programs with 3 programs in rural counties (1.7%). The total fellowship slots grew from 521 to 773 at a rate of 25.2 new fellowship slots per year. The results from the regression model are shown in Table 1. Higher household median income significantly predicted fellowship establishment (OR 1.62, 95% CI 1.25-2.06, p-value <0.001), and rurality significantly predicted no fellowship establishment (OR 0.04, 95% CI 0.01-0.14, p-value < 0.001). Conclusions: Despite robust growth in the number of oncology fellowship programs and slots, expansion into rural and underserved areas remains disproportionately small. The majority of new programs continue to cluster in urban centers, suggesting that increases in fellowship capacity have not effectively addressed geographic disparities in care. We found that new oncology fellowship programs systematically emerge in more affluent urban counties with pre-existing oncology workforces. Strategic policy interventions including location-based incentives and rural training tracks should be considered to improve the distribution of fellowship programs. Firth logistic regression model results. Variable Odds Ratio (OR) 95% Confidence Interval P-Value Intercept 0.01 0.01-0.02 <0.001 Household Median Income 1.62 1.25-2.06 <0.001 Percentage of Population with Insurance 0.74 0.51-1.15 0.17 Oncologist Density (providers per 100,000 population) 1.18 1.05-1.29 0.02 Medicaid Expansion Status 3.13 1.57-6.55 0.001 Rurality (RUCC) 0.04 0.01-0.14 <0.001

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Cite This Study

Crowley et al. (2026) studied this question.

synapsesocial.com/papers/6a192df7fab5b468c4416f1fhttps://doi.org/10.1200/jco.2026.44.16_suppl.9003
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