A computer-assisted model for predicting probability of dying within 7 days of hospice admission in patients with terminal cancer.
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.
Chiang
Jui-Kun
JK
Department of Family Medicine, Tainan Municipal Hospital, Tainan 70173, Taiwan.
Cheng
Yu-Hsiang
YH
Koo
Malcolm
M
Kao
Yee-Hsin
YH
Chen
Ching-Yu
CY
D000328:Adult; D000368:Aged; D003936:Diagnosis, Computer-Assisted; D005260:Female; D017051:Hospice Care; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000175:diagnosis* / Q000628:therapy; D010166:Palliative Care; D010347:Patient Care Planning; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D012720:Severity of Illness Index; D016019:Survival Analysis; D013624:Taiwan