Can subjective global assessment of nutritional status predict survival in XXXX ?

@entity1 @entity43 @entity5
BACKGROUND: Malnutrition is a significant problem in @entity1 with @entity43 . The goal of this study was to investigate the prognostic role of Subjective Global Assessment (SGA) in @entity1 with @entity43 treated in an integrative @entity5 treatment setting. METHODS: We evaluated a case series of 132 @entity43 @entity1 treated at Cancer Treatment Centers of America(R) from Jan 2001 to May 2006. SGA was used to assess nutritional status at baseline. Using SGA, @entity1 were classified as well nourished (SGA A), moderately malnourished (SGA B) or severely malnourished (SGA C). Kaplan Meier method was used to calculate survival. Cox proportional hazard models were constructed to evaluate the prognostic effect of SGA independent of other factors. RESULTS: Of 132 @entity1 , 24 were newly diagnosed while 108 had received prior treatment. 15 had stage I disease at diagnosis, 8 stage II, 85 stage III and 17 stage IV. The median age at presentation was 54.4 years (range 25.5 - 82.5 years). 66 @entity1 were well-nourished (SGA A), 35 moderately malnourished (SGA B) and 31 severely malnourished (SGA C). Well nourished @entity1 had a median survival of 19.3 months (95% CI: 14.1 to 24.5), moderately malnourished 15.5 months (95% CI: 5.8 to 25.1), and severely malnourished 6.7 months (95% CI: 4.1 to 9.3); the difference being statistically significant (p = 0.0003). Multivariate Cox modeling, after adjusting for stage at diagnosis and prior treatment history found that moderately malnourished and severely malnourished status were associated with a relative risk of 2.1 (95% CI: 1.2 to 3.6, p = 0.008) and 3.4 (95% CI: 1.9 to 5.8, p < 0.001) respectively as compared to well nourished status. CONCLUSION: Univariate and multivariate survival analyses found that low SGA scores (i.e. well-nourished status) are associated with better survival outcomes. This study lends support to the role of aggressive nutritional intervention in improving @entity1 outcomes in @entity5 care.
