This prospective study aimed to develop an individualized prognostic tool for predicting the survival probability at any given point for a hospice patient with advanced cancer. A total of 286 patients with advanced cancer were included in the study. Median observational time was 18 days (range: 1 to 60 days). Cox proportional hazards regression analysis revealed that faster heart rate (hazard ratio [HR]=1.01), jaundice (HR=2.32), poorer performance status (HR=2.01), and antifungal treatment (HR=1.62) were independent predictors of shorter survival time. Patients with infections who received aminoglycoside treatments (HR=0.45) were associated with longer survival times. Based on this model, we could construct a covariate-adjusted individualized survival curve for a given patient according to his or her clinical condition. This user-friendly tool for estimating the survival probability of patients with advanced cancer in hospice settings could facilitate clinical decision making and medical care planning.
GwilliamB., KeeleyV., ToddC.Prognosticating in patients with advanced cancer — observational study comparing the accuracy of clinicians’ and patients’ estimates of survival.Ann Oncol2012; 24(2): 482–488. doi: 10.1093/annonc/mds341.
2.
GlareP., ChristakisN.Predicting survival in patients with advanced disease. In: HanksG., ChernyN.I., ChristakisN.A., editors. Oxford textbook of palliative medicine.4th ed.Oxford: Oxford University Press; 2010.
GlareP., VirikK., JonesM.A systematic review of physicians’ survival predictions in terminally ill cancer patients.BMJ2003; 327(7408): 195–198.
5.
HuiD., KilgoreK., NguyenL.The accuracy of probabilistic versus temporal clinician prediction of survival for patients with advanced cancer: a preliminary report.Oncologist2011; 16(11): 1642–1648. doi: 10.1634/theoncologist.2011-0173.
6.
PirovanoM., MaltoniM., NanniO.A new palliative prognostic score: a first step for the staging of terminally ill cancer patients. Italian Multicenter and Study Group on Palliative Care.J Pain Symptom Manage1999; 17(4): 231–239.
7.
MoritaT., TsunodaJ., InoueS.The Palliative Prognostic Index: a scoring system for survival prediction of terminally ill cancer patients.Support Care Cancer1999; 7(3): 128–133.
8.
ChuangR.B., HuW.Y., ChiuT.Y.Prediction of survival in terminal cancer patients in Taiwan: constructing a prognostic scale.J Pain Symptom Manage2004; 28(2): 115–122.
9.
AndersonF., DowningG.M., HillJ.Palliative Performance Scale (PPS): a new tool.J Palliat Care1996; 12(1): 5–11.
10.
BozcukH., KoyuncuE., YildizM.A simple and accurate prediction model to estimate the intrahospital mortality risk of hospitalised cancer patients.Int J Clin Pract2004; 58(11): 1014–1019.
11.
ReubenD.B., MorV., HirisJ.Clinical symptoms and length of survival in patients with terminal cancer.Arch Intern Med1988; 148(7): 1586–1591.
12.
ChiangJ.K., LaiN.S., WangM.H.A proposed prognostic 7-day survival formula for patients with terminal cancer.BMC Public Health2009; 9: 365. doi: 10.1186/1471-2458-9-365.
13.
StoneP.C., LundS.Predicting prognosis in patients with advanced cancer.Ann Oncol2007; 18(6): 971–976.
14.
GailM.H., BrintonL.A., ByarD.P.Projecting individualized probabilities of developing breast cancer for white females who are being examined annually.J Natl Cancer Inst1989; 81(24): 1879–1886.
15.
National Cancer Institute.The Breast Cancer Risk Assessment Tool.Bethesda (MD): National Cancer Institute; 2011. Accessed February 20, 2013. www.cancer.gov/bcrisktool/
16.
ShariatS.F., WalzJ., RoehrbornC.G.External validation of a biomarker-based preoperative nomogram predicts biochemical recurrence after radical prostatectomy.J Clin Oncol2008; 26(9): 1526–1531. doi: 10.1200/JCO.2007.12.4669.
17.
IasonosA., SchragD., RajG.V.How to build and interpret a nomogram for cancer prognosis.J Clin Oncol2008; 26(8): 1364–1370. doi: 10.1200/JCO.2007.12.9791.
18.
WangS.J., LemieuxA., Kalpathy-CramerJ.Nomogram for predicting the benefit of adjuvant chemoradiotherapy for resected gallbladder cancer.J Clin Oncol2011; 29(35): 4627–4632. doi: 10.1200/JCO.2010.33.8020.
19.
ValentiniV., van StiphoutR.G., LammeringG.Nomograms for predicting local recurrence, distant metastases, and overall survival for patients with locally advanced rectal cancer on the basis of European randomized clinical trials.J Clin Oncol2011; 29(23): 3163–3172. doi: 10.1200/JCO.2010.33.1595.
20.
WeiserM.R., GonenM., ChouJ.F.Predicting survival after curative colectomy for cancer: individualizing colon cancer staging.J Clin Oncol2011; 29(36): 4796–4802. doi: 10.1200/JCO.2011.36.5080.
21.
ChiangJ.K., ChengY.H., KooM.A computer-assisted model for predicting probability of dying within 7 days of hospice admission in patients with terminal cancer.Jpn J Clin Oncol2010; 40(5): 449–455. doi: 10.1093/jjco/hyp188.
22.
WhiteP.H., KuhlenschmidtH.L., VancuraB.G.Antimicrobial use in patients with advanced cancer receiving hospice care.J Pain Symptom Manage2003; 25(5): 438–443.
23.
ChiuT.Y., HuW.Y., ChuangR.B.Nutrition and hydration for terminal cancer patients in Taiwan.Support Care Cancer2002; 10(8): 630–636.
24.
ReinboltR.E., ShenkA.M., WhiteP.H.Symptomatic treatment of infections in patients with advanced cancer receiving hospice care.J Pain Symptom Manage2005; 30(2): 175–182.
GailM.H., CostantinoJ.P., PeeD.Projecting individualized absolute invasive breast cancer risk in African American women.J Natl Cancer Inst2007; 99(23): 1782–1792.
29.
ParkY., FreedmanA.N., GailM.H.Validation of a colorectal cancer risk prediction model among white patients age 50 years and older.J Clin Oncol2009; 27(5): 694–698. doi: 10.1200/JCO.2008.17.4813.
30.
StoneP., KellyL., HeadR.Development and validation of a prognostic scale for use in patients with advanced cancer.Palliat Med2008; 22(6): 711–717. doi: 10.1177/0269216308095200.
31.
KaoY.H., ChenC.N., ChiangJ.K.Predicting factors in the last week of survival in elderly patients with terminal cancer: a prospective study in southern Taiwan.J Formos Med Assoc2009; 108(3): 231–239. doi: 10.1016/S0929-6646(09)60057-7.
32.
ClaytonJ., FardellB., Hutton-PottsJ.Parenteral antibiotics in a palliative care unit: prospective analysis of current practice.Palliat Med2003; 17(1): 44–48.
33.
RaijmakersN.J., van ZuylenL., CostantiniM.Artificial nutrition and hydration in the last week of life in cancer patients. A systematic literature review of practices and effects.Ann Oncol2011; 22(7): 1478–1486. doi: 10.1093/annonc/mdq620.
