Comparisons of Medical Cost Trajectories Between Non-Hispanic Black and Non-Hispanic White Patients With Newly Diagnosed Localized Prostate Cancer

Yu Liu, Shikun Wang, Liang Li, Ying Xu, Yu Shen, Ya Chen Tina Shih

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Objectives: This study applied a recently developed statistical method to compare the mean cost trajectories between non-Hispanic White (NHW) and non-Hispanic Black (NHB) patients with localized prostate cancer conditioning on patients’ survival. Methods: In this observational study, we modeled cost trajectories of NHW and NHB patients with localized prostate cancer for 3 survival durations: 24, 48, and 72 months. We also compared the cost trajectories between NHW and NHB, stratified by comorbidities scores. Results: We find that the mean cost trajectories of NHB were significantly higher than the trajectories of NHW in the last 12 months before death, regardless of the survival duration and patients’ baseline comorbidity scores. For patients with comorbidity score ≥2, mean cost trajectories within the first year of diagnosis for NHB were significantly higher than those for NHW, except for the subgroup of patients with comorbidity 2-3 and whose survival length was 72 months. Conclusions: Our results suggested that a higher proportion of NHB patients with high comorbidity scores are likely contribute to their higher end-of-life costs than those for NHW patients. To narrow the gap in healthcare-related financial burden between NHB and NHW patients with localized prostate cancer, policy makers need to explore different strategies to better manage comorbidities.

Original languageEnglish (US)
Pages (from-to)1444-1452
Number of pages9
JournalValue in Health
Volume26
Issue number10
DOIs
StatePublished - Oct 2023

Keywords

  • chronic disease
  • healthcare costs
  • healthcare disparities

ASJC Scopus subject areas

  • Health Policy
  • Public Health, Environmental and Occupational Health

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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