Predicting life expectancy in patients with metastatic cancer receiving palliative radiotherapy: The TEACHH model

Authors

  • Monica S. Krishnan MD,

    Corresponding author
    1. Harvard Radiation Oncology Program, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts
    • Corresponding author: Monica S. Krishnan, MD, Department of Radiation Oncology, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02155; Fax: (617) 582 6037; mkrishnan@lroc.harvard.edu

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  • Zachary Epstein-Peterson BS,

    1. Harvard Medical School, Boston, Massachusetts
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  • Yu-Hui Chen MD, MPH,

    1. Department of Radiation Oncology, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts
    2. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
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  • Yolanda D. Tseng MD,

    1. Harvard Radiation Oncology Program, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts
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  • Alexi A. Wright MD,

    1. Harvard Medical School, Boston, Massachusetts
    2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
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  • Jennifer S. Temel MD,

    1. Department of Medical Oncology, Massachusetts General Hospital, Boston, Massachusetts
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  • Paul Catalano ScD,

    1. Department of Radiation Oncology, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts
    2. Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts
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  • Tracy A. Balboni MD, MPH

    1. Department of Radiation Oncology, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts
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  • Presented as an oral presentation at the 54th Annual Meeting of the American Society for Radiation Oncology; October 28-31, 2012; Boston, MA.

Abstract

BACKGROUND

Predicting life expectancy (LE) in patients with metastatic cancer who are receiving palliative therapies is a difficult task. The purpose of the current study was to develop a LE prediction model among patients receiving palliative radiotherapy (RT) that identifies those patients with short (< 3 months) and long (> 1 year) LEs.

METHODS

The records of 862 patients with metastatic cancer receiving palliative RT at the Dana-Farber/Brigham and Women's Cancer Center between June 2008 and July 2011 were retrospectively reviewed. Cox proportional hazards models were used to evaluate established and potential clinical predictors of LE to construct a model predicting LE of < 3 months and > 1 year.

RESULTS

The median survival was 5.6 months. On multivariate analysis, factors found to be significantly associated with a shorter LE were cancer type (lung and other vs breast and prostate), older age (> 60 years vs ≤ 60 years), liver metastases, Eastern Cooperative Oncology Group performance status (2-4 vs 0-1), hospitalizations within 3 months before palliative RT (0 vs ≥ 1), and prior palliative chemotherapy courses (≥ 2 vs 0-1). Patients were divided into 3 groups with distinct median survivals: group A (those with 0-1 risk factors), 19.9 months (95% confidence interval [95% CI, 13.9 months-31.1months]); group B (those with 2-4 risk factors), 5.0 months (95% CI, 4.3 months -5.6 months); and group C (those with 5-6 risk factors), 1.7 months (95% CI, 1.2 months-2.1 months).

CONCLUSIONS

The TEACHH model (type of cancer, Eastern Cooperative Oncology Group performance status, age, prior palliative chemotherapy, prior hospitalizations, and hepatic metastases) divides patients receiving palliative RT into 3 distinct LE groups at clinically informative extremes of the LE spectrum. It holds promise to assist radiation oncologists in tailoring palliative therapies to a patient's LE. Cancer 2014;120:134–141. © 2013 American Cancer Society.

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