Literature DB >> 18081735

Factors predicting survival in patients with advanced oesophageal cancer: a prospective multicentre evaluation.

H Bergquist1, A Johnsson, E Hammerlid, U Wenger, L Lundell, M Ruth.   

Abstract

BACKGROUND: Oesophageal cancer is often diagnosed at an advanced stage, with poor prognosis and severe morbidity. In majority of cases, palliative treatment is the only option available. AIM: To find factors that can predict survival for patients with incurable cancer of the oesophagus or gastro-oesophageal junction and hence aid in the choice of treatment.
METHODS: Ninety-six patients were included. Health-related quality of life questionnaires (EORTC QLQ C-30 and QLQ OES18) were administered and computerized tomography-derived size assessment of the primary tumours was performed. Univariate and multivariate Cox-regression analyses were used to determine potential predictors of survival.
RESULTS: Karnofsky Index, occurrence of metastases (M-stage), Union International Contre le Cancer-stage, computerized tomography-derived tumour size assessment and 10 of 25 scales and single items from the health-related quality of life questionnaires were found to be related to survival. In the multivariate analysis, three of the health-related quality of life questionnaire scales (physical functioning, fatigue and reflux) were found to add prognostic information to M-stage, the single strongest predictor (HR 1.9, P < 0.01).
CONCLUSION: In addition to M-stage, the outcome of health-related quality of life questionnaires can sharpen the prediction of survival in patients with advanced cancer of the oesophagus or gastro-oesophageal junction and thus aid in the choice of palliative treatment strategy.

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Mesh:

Year:  2007        PMID: 18081735     DOI: 10.1111/j.1365-2036.2007.03589.x

Source DB:  PubMed          Journal:  Aliment Pharmacol Ther        ISSN: 0269-2813            Impact factor:   8.171


  11 in total

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10.  Prognostic value of patient-reported quality of life for survival in oesophagogastric cancer: analysis from the population-based POCOP study.

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