Can patient satisfaction with quality of life predict survival in advanced colorectal cancer?

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

MATERIALS AND

METHODS

A consecutive case series of 177 cases of histologically confirmed colorectal cancer treated at Cancer Treatment Centers of America at Midwestern Regional Medical Center between April 2001 and November 2004. The quality of life index (QLI) was utilized to assess patient satisfaction with QoL. QLI measures global QoL and the QoL in four major subscales: health and physical functioning, social and economic, psychological/spiritual, and family. All scores range from 0 to 30 with higher scores indicating a better QoL. 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 177 patients, 46 were newly diagnosed and 131 have treatment history. The median age was 53 years (range 25-85 years). Eight patients had stage I disease, 16 had stage II, 51 had stage III, and 77 had stage IV. Health and physical subscale was significantly associated with survival (p=0.0003), with the median survival for low scores being 8.3 and 20.6 months for high scores. Health and physical subscale was found to be predictive of survival independent of the effects of tumor stage at diagnosis and treatment history.

CONCLUSIONS

We found that baseline patient satisfaction with QoL, as measured by the QLI, provides useful prognostic information in patients with colorectal cancer independent of tumor stage at diagnosis and treatment history. While these findings require further investigation in large patient cohorts, they may have important implications for patient stratification in clinical trials and aid in clinical decision-making.