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. 2006;37(1):35-44.
doi: 10.1385/IJGC:37:1:35.

Patient satisfaction with quality of life as a predictor of survival in pancreatic cancer

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Patient satisfaction with quality of life as a predictor of survival in pancreatic cancer

Christopher G Lis et al. Int J Gastrointest Cancer. 2006.

Abstract

Background: The goal of this study was to evaluate the association between patient satisfaction with quality of life (QoL) and survival in pancreatic cancer patients undergoing care in a community hospital comprehensive cancer center.

Patients and methods: A consecutive case series of 55 cases of histologically confirmed pancreatic cancer treated at Cancer Treatment Centers of America at Midwestern Regional Medical Center was studied between 04/01 and 11/04. The Quality of Life Index (QLI) was utilized to assess patient satisfaction with QoL. QLI measures global QoL as well as the QoL in four major subscales: health and physical, social and economic, psychological and spiritual, and family. All scores range from 0 to 30 with higher scores indicating a better QoL. The Kaplan-Meier method was used to calculate survival. Log-rank test was used to study the equality of survival distributions. Multivariate Cox regression analyses were then performed to evaluate the joint prognostic significance of those QoL and clinical factors that were shown to be prognostic in univariate analyses.

Results: Of the 55 patients, 28 were newly diagnosed and 27 had prior treatment history. The median age was 55 yr (range 33-74 yr). Amajority (34) had stage IV disease at diagnosis. Health and physical subscale, family subscale, and global QoL were significantly associated with survival upon univariate analysis. Health and physical subscale was marginally significant upon multivariate analysis after controlling for the effects of stage at diagnosis.

Conclusions: We found that baseline patient satisfaction with QoL, as measured by the QLI, provides useful prognostic information in patients with pancreatic cancer. While these findings require further investigation in large patient cohorts, they may have important implications for patient stratification in clinical trials, as well as aid in clinical decision-making.

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