Literature DB >> 23935016

A Markov multistate analysis of the relationship between performance status and death among an ambulatory population of cancer patients.

Rinku Sutradhar1, Lisa Barbera.   

Abstract

BACKGROUND: The relationship between performance status and death among cancer patients has been of increasing interest over the past years. However, few studies have implemented statistical models that adequately capture the longitudinal nature of performance status assessments collected under intermittent observation. AIM: The main research aims were to examine the association between performance status and death and to determine the probability of deterioration in performance status over time.
DESIGN: This was a population-based longitudinal study among adult outpatients diagnosed with cancer. Throughout their observation period, all patients were repeatedly assessed for performance status using an 11-point scale with a score of 100 being the best, 10 being the worst and 0 representing death. A Markov multistate model accounting for intermittent observation was implemented in which each score represented a distinct state in the model.
RESULTS: The cohort consisted of 27,739 patients with over 157,000 assessments. The rate of transition to death increases with a quadratic trend as performance status declines. The 1-month and 3-month probability of deterioration also increases with a quadratic trend as performance status declines. The relative rate of transition to death decreases as we compare lower scores (relative rate = 2.20 for comparing scores 90 vs 100 and relative rate = 1.23 for comparing scores 10 vs 20).
CONCLUSION: There is a significant relationship between performance status and rate of transition to death. The Markov multistate model provides a comprehensive understanding of the shape of this relationship, which facilitates the interpretation of performance status and provides strength in its use as a prognostic tool in a clinical setting.

Entities:  

Keywords:  Markov multistate model; Palliative performance score; extended Cox model; intermittent observation; quadratic regression; rate of transition

Mesh:

Year:  2013        PMID: 23935016     DOI: 10.1177/0269216313499059

Source DB:  PubMed          Journal:  Palliat Med        ISSN: 0269-2163            Impact factor:   4.762


  2 in total

1.  Variations in intensity of end-of-life cancer therapy by cancer type at a Canadian tertiary cancer centre between 2003 and 2010.

Authors:  Petra Grendarova; Aynharan Sinnarajah; Theresa Trotter; Cynthia Card; Jackson S Y Wu
Journal:  Support Care Cancer       Date:  2015-03-07       Impact factor: 3.603

2.  Quantifying Dynamic Flow of Emergency Department (ED) Patient Managements: A Multistate Model Approach.

Authors:  Chung-Hsien Chaou; Te-Fa Chiu; Shin-Liang Pan; Amy Ming-Fang Yen; Shu-Hui Chang; Petrus Tang; Chao-Chih Lai; Ruei-Fang Wang; Hsiu-Hsi Chen
Journal:  Emerg Med Int       Date:  2020-12-03       Impact factor: 1.112

  2 in total

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