A computer-assisted model for predicting probability of dying within 7 days of hospice admission in patients with terminal cancer.

Abstract:

OBJECTIVE:The aim of the present study is to compare the accuracy in using laboratory data or clinical factors, or both, in predicting probability of dying within 7 days of hospice admission in terminal cancer patients. METHODS:We conducted a prospective cohort study of 727 patients with terminal cancer. Three models for predicting the probability of dying within 7 days of hospice admission were developed: (i) demographic data and laboratory data (Model 1); (ii) demographic data and clinical symptoms (Model 2); and (iii) combination of demographic data, laboratory data and clinical symptoms (Model 3). We compared the models by using the area under the receiver operator curve using stepwise multiple logistic regression. RESULTS:We estimated the probability dying within 7 days of hospice admission using the logistic function, P = Exp(betax)/[1 + Exp(betax)]. The highest prediction accuracy was observed in Model 3 (82.3%), followed by Model 2 (77.8%) and Model 1 (75.5%). The log[probability of dying within 7 days/(1 - probability of dying within 7 days)] = -6.52 + 0.77 x (male = 1, female = 0) + 0.59 x (cancer, liver = 1, others = 0) + 0.82 x (ECOG score) + 0.59 x (jaundice, yes = 1, no = 0) + 0.54 x (Grade 3 edema = 1, others = 0) + 0.95 x (fever, yes = 1, no = 0) + 0.07 x (respiratory rate, as per minute) + 0.01 x (heart rate, as per minute) - 0.92 x (intervention tube = 1, no = 0) - 0.37 x (mean muscle power). CONCLUSIONS:We proposed a computer-assisted estimated probability formula for predicting dying within 7 days of hospice admission in terminal cancer patients.

journal_name

Jpn J Clin Oncol

authors

Chiang JK,Cheng YH,Koo M,Kao YH,Chen CY

doi

10.1093/jjco/hyp188

subject

Has Abstract

pub_date

2010-05-01 00:00:00

pages

449-55

issue

5

eissn

0368-2811

issn

1465-3621

pii

hyp188

journal_volume

40

pub_type

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