Principles and reality of proton therapy treatment allocation

Justin E. Bekelman, David A. Asch, Zelig Tochner, Joseph Friedberg, David J. Vaughn, Ellen Rash, Kevin Raksowski, Stephen M. Hahn

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Purpose To present the principles and rationale of the Proton Priority System (PROPS), a priority points framework that assigns higher scores to patients thought to more likely benefit from proton therapy, and the distribution of PROPS scores by patient characteristics Methods and Materials We performed multivariable logistic regression to evaluate the association between PROPS scores and receipt of proton therapy, adjusted for insurance status, gender, race, geography, and the domains that inform the PROPS score. Results Among 1529 adult patients considered for proton therapy prioritization during our Center's ramp-up phase of treatment availability, PROPS scores varied by age, diagnosis, site, and other PROPS domains. In adjusted analyses, receipt of proton therapy was lower for patients with non-Medicare relative to Medicare health insurance (commercial vs Medicare: adjusted odds ratio [OR] 0.47, 95% confidence interval [CI] 0.34-0.64; managed care vs Medicare: OR 0.40, 95% CI 0.28-0.56; Medicaid vs Medicare: OR 0.24, 95% CI 0.13-0.44). Proton Priority System score and age were not significantly associated with receipt of proton therapy. Conclusions The Proton Priority System is a rationally designed and transparent system for allocation of proton therapy slots based on the best available evidence and expert opinion. Because the actual allocation of treatment slots depends mostly on insurance status, payers may consider incorporating PROPS, or its underlying principles, into proton therapy coverage policies.

Original languageEnglish
Pages (from-to)499-508
Number of pages10
JournalInternational Journal of Radiation Oncology Biology Physics
Volume89
Issue number3
DOIs
StatePublished - Jul 1 2014

Keywords

  • Adult
  • Age Factors
  • Aged
  • Algorithms
  • Cancer Care Facilities
  • Female
  • Humans
  • Insurance Coverage/statistics & numerical data
  • International Classification of Diseases
  • Logistic Models
  • Male
  • Medicare/statistics & numerical data
  • Middle Aged
  • Neoplasms/classification
  • Patient Selection
  • Philadelphia
  • Proton Therapy/statistics & numerical data
  • Racial Groups
  • Sex Factors
  • United States

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