Validation of the palliative performance scale in the acute tertiary care hospital setting

J Palliat Med. 2007 Feb;10(1):111-7. doi: 10.1089/jpm.2006.0125.


Background: Physicians are often asked to prognosticate patient survival. However, prediction of survival is difficult, particularly with critically ill and dying patients within the hospitals. The Palliative Performance Scale (PPS) was designed to assess functional status and measure progressive decline in palliative care patients, yet it has not been validated within hospital health care settings.

Objective: This study explores the application of the PPS for its predictive ability related to length of survival. Other variables examined were correlates of symptom distress in a tertiary academic setting.

Methods: Patients were assigned a score on the PPS ranging from 0% to 100% at initial consultation. Standardized symptom assessments were carried out daily, and survival was determined by medical record review and search of the National Death Index.

Results: Of 261 patients seen since January 2002, 157 had cancer and 104 had other diagnoses. PPS scores ranged from 10% to 80% with 92% of the scores between 10% and 40%. Survival ranged from 0 to 30 months, with a median of 9 days. By 90 days, 83% of patients had died. Proportional hazards regression estimates showed that a 10% decrement in PPS score was associated with a hazard ratio of 1.65 (95% confidence interval [CI]: 1.42-1.92). Proportional odds regression models showed that a lower PPS was significantly associated with higher levels of dyspnea.

Conclusion: The PPS correlated well with length of survival and with select symptom distress scores. We consider it to be a useful tool in predicting outcomes for palliative care patients.

Publication types

  • Validation Study

MeSH terms

  • Activities of Daily Living*
  • Critical Illness / classification*
  • Disease Progression*
  • Female
  • Humans
  • Karnofsky Performance Status*
  • Male
  • Middle Aged
  • North Carolina
  • Palliative Care / methods*
  • Prognosis
  • Proportional Hazards Models
  • Prospective Studies
  • Survival Analysis
  • Terminally Ill / classification*