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J Oncol Pract. 2014 May;10(3):e175-81. doi: 10.1200/JOP.2013.001143. Epub 2014 Mar 18.

Can patient comorbidities be included in clinical performance measures for radiation oncology?

Author information

  • 1American College of Radiology Clinical Research Center, Philadelphia, PA; Boston Medical Center/Boston University School of Medicine, Boston, MA; The University of Texas MD Anderson Cancer Center, Houston, TX; Valley Radiotherapy Associates at Center for Radiation Therapy, Beverly Hills, CA; and Medical College of Wisconsin, Milwaukee, WI Jowen24@outlook.com.
  • 2American College of Radiology Clinical Research Center, Philadelphia, PA; Boston Medical Center/Boston University School of Medicine, Boston, MA; The University of Texas MD Anderson Cancer Center, Houston, TX; Valley Radiotherapy Associates at Center for Radiation Therapy, Beverly Hills, CA; and Medical College of Wisconsin, Milwaukee, WI.

Abstract

PURPOSE:

Patient comorbidities may affect the applicability of performance measures that are inherent in multidisciplinary cancer treatment guidelines. This article describes the distribution of common comorbid conditions by disease site and by patient and facility characteristics in patients who received radiation therapy as part of treatment for cancer of the breast, cervix, lung, prostate, and stomach, and investigates the association of comorbidities with treatment decisions.

MATERIALS AND METHODS:

Stratified two-stage cluster sampling provided a random sample of radiation oncology facilities. Eligible patients were randomly sampled from each participating facility for each disease site, and data were abstracted from medical records. The Adult Comorbidity Evaluation Index (ACE-27) was used to measure comorbid conditions and their severity. National estimates were calculated using SUDAAN statistical software.

RESULTS:

Multivariable logistic regression models predicted the dependent variable "treatment changed or contraindicated due to comorbidities." The final model showed that ACE-27 was highly associated with change in treatment for patients with severe or moderate index values compared to those with none or mild (P < .001). Two other covariates, age and medical coverage, had no (age) or little (medical coverage) significant contribution to predicting treatment change in the multivariable model. Disease site was associated with treatment change after adjusting for other covariates in the model.

CONCLUSIONS:

ACE-27 is highly predictive of treatment modifications for patients treated for these cancers who receive radiation as part of their care. A standardized tool identifying patients who should be excluded from clinical performance measures allows more accurate use of these measures.

Copyright © 2014 by American Society of Clinical Oncology.

PMID:
24643573
[PubMed - indexed for MEDLINE]
PMCID:
PMC4018459
Free PMC Article
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