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

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–31.1 months]); 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.

Impact of Radiation Therapy on Aggressive Care and Quality of Life Near Death

“…1 Krishnan et al studied 862 patients who received palliative RT to identify better predictors of life-expectancy. 21 ECOG PS (2–4 versus 0–1) was one of several significant predictors of poor prognosis in their study (life-expectancy < 3 months). In the present cohort, we found beneficial effects of RT for patients with good PS regardless of the accuracy of their prognoses.…”

Trend in and Correlates of Undergoing Radiotherapy in Taiwanese Cancer Patients' Last Month of Life

“…Administrative datasets lack detailed clinical information, preventing us from distinguishing between palliative and curative EOL radiotherapy intent and ascertaining how treatment was delivered, e.g., radiation dose, fraction, and duration; thus, it was difficult to determine whether treatment was clinically appropriate. We cannot exclude the possibility that our results are partly attributable to unmeasured patient characteristics, e.g., preferences and expectations for radiotherapy 44 and extent of symptom distress; physician attitudes towards 45 and incentives for providing radiotherapy; and hospital microclimates or cultures, regional density of radiation oncologists, 15 should target hospitals and physicians with a tendency to aggressively treat cancer patients at EOL to help physicians in these hospitals use available validated tools 46 to facilitate accurate prognostic estimates and carefully evaluate the effectiveness of EOL radiotherapy. Providing radiotherapy tailored to patients' needs for symptom management and life expectancy will maximize the benefits of radiotherapy not only to relieve symptom distress and improve cancer patients' quality of life at EOL, but also to avoid unnecessary EOL radiotherapy and health care spending when benefit of symptom relief could not be reasonably expected, thus preventing suffering and making EOL cancer care sustainable.…”

Agreement in the assessment of metastatic spine disease using scoring systems

“…Moreover, some features of the modified Bauer and Tomita scoring systems may be criticized; for instance, while it is widely accepted that the origin of the primary tumor is the most important prognostic factor for survival [5,7], these scoring systems do not explicitly consider all subtypes of cancer which can cause spinal metastases [2,27]. However, this study did not focus on assessing the validity of the Tomita or modified Bauer scoring systems as a tool for identifying the most effective treatment for each patient, or on measuring the improvements in clinical results generated by their use, as other prognostic factors may be valid [27,28]. This study focused on assessing the degree of agreement when using these scoring systems.…”