Quality of life scores: an independent prognostic variable in a general population of cancer patients receiving chemotherapy. The National Cancer Institute of Canada Clinical Trials Group.
This report examines the prognostic associations between QOL scores measured by the EORTC QLQ-C30 and survival in a large heterogeneous population of cancer patients. Eight hundred and fifty-one cancer patients who were to receive chemotherapy were enrolled in two National Cancer Institute of Canada Clinical Trials Group (NCIC CTG) antiemetic trials. All patients completed the EORTC QLQ-C30 immediately prior to their first chemotherapy. Survival data were available and obtained for 474 of 639 patients (74%). Cox's proportional hazards model was used to assess the independent impact of QOL and demographic variables on survival. Presence of metastatic disease, diagnosis of lung or ovarian cancer, ECOG performance status, global quality of life and emotional functioning were significantly associated with survival. Global QOL was predictive in all patients, in subgroups of patients with metastatic disease, with breast and lung cancer and other tumour types. In patients with low global quality of life scores, patients with low emotional functioning ratings lived longer than did patients with high emotional functioning ratings. Patients with high global QOL live significantly longer than do patients with low global QOL. The relationship between emotional functioning in patients with low global QOL and survival needs confirmation.
Dancey
J
J
National Cancer Institute of Canada Clinical Trials Group, Kingston, Canada.
Zee
B
B
Osoba
D
D
Whitehead
M
M
Lu
F
F
Kaizer
L
L
Latreille
J
J
Pater
J L
JL
D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009369:Neoplasms / Q000188:drug therapy / Q000523:psychology*; D011379:Prognosis; D016016:Proportional Hazards Models; D011788:Quality of Life; D012189:Retrospective Studies; D018709:Statistics, Nonparametric; D011795:Surveys and Questionnaires; D016019:Survival Analysis