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Purpose <p>High-grade gliomas (HGG; WHO III/IV) are among the most devastating intracranial malignancies, and outcomes may be associated with demographic, biological and environmental factors. Although research exists on the association of sociodemographic background with outcomes, the literature lacks data on the effect of sociodemographic background on clinical presentation. In this study, we aimed to examine race- and ethnicity-related differences in HGG presentation and diagnosis.</p> Methods <p>We conducted a chart review of patients treated for HGG between 2015 and 2021 at three high-volume academic medical centers. A total of 314 patients were analyzed. 173 White patients were included along with 144 non-White patients, comprising of Asian (16%), Black (26%), Hispanic (9%), and other/declined (50%) race. Statistical analysis was carried out using GraphPad Prism.</p> Results <p>On multivariate analysis, White race was significantly associated with a later age at diagnosis independent of IDH1 status. White patients were more likely to present with a cognitive deficit (42.3% vs. 21.1%; <i>p</i> = 0.02*), while less likely to present with midline shift (32.5% vs. 49.3%; <i>p</i> = 0.004**) and mass effect on imaging (59.8% vs. 76.1%; <i>p</i> = 0.003***). Additionally, Black patients were more likely to present with syncope (15.8% vs. 2.3% [<i>n</i> = 107]; <i>p</i> = 0.04*) and Hispanic patients were more likely to present with seizure (35.7% vs. 15.9% [<i>n</i> = 110]; <i>p</i> = 0.03*).</p> Conclusion <p>White race appears to be independently associated with a later age at diagnosis of HGG. Furthermore, Black and Hispanic patients are more likely to present with severe, life-threatening symptoms. Large-scale studies are needed to elucidate race-based differences in HGG presentation to effectively predict outcomes.</p>

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The impact of sociodemographic background on clinical presentation of high-grade gliomas: a multi-institutional retrospective analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月25日

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  • Sayak R. Ghosh,
  • Anne R. Lally,
  • Isabella L. Pecorari,
  • Joshua Reynolds,
  • Alexander Ledet,
  • Sabrina Begley,
  • Elizabeth Juarez Diaz,
  • Eric Zhu,
  • Karan Joseph,
  • Kyle McGeehan MPhil,
  • Michael Schulder,
  • Tanner Johanns,
  • Yonah C. Ziemba,
  • Vijay Agarwal

摘要

Purpose

High-grade gliomas (HGG; WHO III/IV) are among the most devastating intracranial malignancies, and outcomes may be associated with demographic, biological and environmental factors. Although research exists on the association of sociodemographic background with outcomes, the literature lacks data on the effect of sociodemographic background on clinical presentation. In this study, we aimed to examine race- and ethnicity-related differences in HGG presentation and diagnosis.

Methods

We conducted a chart review of patients treated for HGG between 2015 and 2021 at three high-volume academic medical centers. A total of 314 patients were analyzed. 173 White patients were included along with 144 non-White patients, comprising of Asian (16%), Black (26%), Hispanic (9%), and other/declined (50%) race. Statistical analysis was carried out using GraphPad Prism.

Results

On multivariate analysis, White race was significantly associated with a later age at diagnosis independent of IDH1 status. White patients were more likely to present with a cognitive deficit (42.3% vs. 21.1%; p = 0.02*), while less likely to present with midline shift (32.5% vs. 49.3%; p = 0.004**) and mass effect on imaging (59.8% vs. 76.1%; p = 0.003***). Additionally, Black patients were more likely to present with syncope (15.8% vs. 2.3% [n = 107]; p = 0.04*) and Hispanic patients were more likely to present with seizure (35.7% vs. 15.9% [n = 110]; p = 0.03*).

Conclusion

White race appears to be independently associated with a later age at diagnosis of HGG. Furthermore, Black and Hispanic patients are more likely to present with severe, life-threatening symptoms. Large-scale studies are needed to elucidate race-based differences in HGG presentation to effectively predict outcomes.