Impact of BMI and Gender on Outcomes in DLBCL Patients Treated with R-CHOP: A Pooled Study from the LYSA
Table 3
Statistical analysis for OS and PFS in the global population.
PFS
OS
Univariate analysis
BMI (<18.5/18.5–25/>25)* >25 versus ≤25 <18.5 versus ≥18.5
HR = 1.1 95% CI (0.94–1.37)
HR = 0.9 95% CI (0.53–1.57)
HR = 1.18 95% CI (0.95–1.46)
HR = 0.86 95% CI (0.47–1.59)
Gender (male versus female)
HR = 1.237 95% CI (1.025–1.493)
.218 95% CI (0.985–1.505)
aaIPI (2-3 versus 0-1)
HR = 1.967 95% CI (1.62–2.38)
HR = 2.407 95% CI (1.92–3.01)
Age (≥60 y versus <60)
HR = 1.61 95% CI (1.207–2.148)
HR = 2.021 95% CI (1.409–2.898)
Cox model
BMI > 25 versus normal
HR = 1.097 95% CI (0.56–2.11)
HR = 0.917 95% CI (0.4162.00)
BMI < 18.5 versus normal
HR = 1.16 95% CI (0.86–1.55)
HR = 1.394 95% CI (1.00–1.94)
Gender (male versus female)
HR = 1.226 95% CI (0.93–1.61)
HR = 1.342 95% CI (0.97–1.84)
Age (≥60 y versus <60)
HR = 1.096 95% CI (0.79–1.51)
HR = 1.215 95% CI (0.81–1.80)
aaIPI (>1 versus 0-1)
HR = 1.926 95% CI (1.55–2.38)
HR = 2.287 95% CI (1.78–2.93)
BMI and gender
HR = 0.716 95% CI (0.21–2.36)
HR = 1.055 95% CI (0.29–3.76)
The test was performed using the 3 BMI classes: <18.5, 18.5–25, and >25. When 16.5 and 30 were used as the cut-offs, BMI had no impact on OS or PFS ( and 0.71, resp.). In a Cox regression model including BMI, gender, age, aaIPI score, and the interaction between BMI and gender as covariables, a high aaIPI score was the only factor associated with a worse PFS and OS. Low BMI significantly impacted OS but not PFS.
