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. 2010 May;40(5):449-55.
doi: 10.1093/jjco/hyp188. Epub 2010 Jan 22.

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

Jui-Kun Chiang  1 , Yu-Hsiang Cheng, Malcolm Koo, Yee-Hsin Kao, Ching-Yu Chen
Affiliations

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

Jui-Kun Chiang et al. Jpn J Clin Oncol. 2010 May.

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.

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Figures

Figure 1.
Figure 1.
The Kaplan–Meier survival curve.
Figure 2.
Figure 2.
The receiver operating characteristic curve of three computer-assisted estimated probability models for prediction dying within 7 days of hospice admission in terminal cancer patients: Model 1, laboratory data and demographic data; Model 2, clinical factors and demographic data; Model 3, clinical factors, laboratory data and demographic data.
See this image and copyright information in PMC

References

    1. Miller SC, Kinzbrunner B, Pettit P, Williams JR. How does the timing of hospice referral influence hospice care in the last days of life? J Am Geriatr Soc. 2003;51:798–806. - PubMed
    1. Bradley EH, Prigerson H, Carlson MDA, Cherlin E, Johnson-Hurzeler R, Kasl SV. Depression among surviving caregivers: does length of hospice enrollment matter? Am J Psychiatry. 2004;161:2257–62. - PubMed
    1. Christakis NA, Iwashyna TJ. Impact of individual and market factors on the timing of initiation of hospice terminal care. Med Care. 2000;38:528–41. - PubMed
    1. Tang ST, Chen ML, Huang EW, Koong SL, Lin GL, Hsiao SC. Hospice utilization in Taiwan by cancer patients who died between 2000 and 2004. J Pain Symptom Manage. 2007;33:446–53. - PubMed
    1. National Hospice and Palliative Care Organization. NHPCO's 2008 Facts and Figures: Hospice Care in America. http://www.nhpco.org/files/public/Statistics_Research/NHPCO_facts-and-fi.... (22 July 2009, date last accessed)

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