Associations between continuous variables were assessed using Spearman rank correlation test. Paired t-tests were used to assess differences in ALC and RDW values before vs. after initiation of treatments. Survival analysis methods, including log-rank tests and Cox proportional hazard models, were used to assess mortality across biomarker levels while adjusting for covariates of interest. Cut points for RDW and ALC in survival analyses (1.2 k/cmm for ALC and 14.5% for RDW) were based upon prior cohort survival analyses14 (link),15 (link). All pvalues presented are two-sided and unadjusted. Statistical analyses were performed using SPSS for Windows v. 27.0 (IBM Corp, Armonk, New York) and R Statistical Software v 4.0.5 (R Core Team, Vienna, Austria).
Protocol detail
Survival Analysis of Biomarkers in Clinical Cohorts
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Other organizations : Case Western Reserve University, Geriatric Research Education and Clinical Center, MetroHealth Medical Center
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Variable analysis
independent variables
- ALC (Absolute Lymphocyte Count)
- RDW (Red Cell Distribution Width)
- Mortality
- Covariates of interest
- The independent variables were ALC and RDW, which were assessed for their association with the dependent variable of mortality.
- The study used cut-points for ALC (1.2 k/cmm) and RDW (14.5%) to categorize the independent variables for the survival analysis.
- The study also adjusted for 'covariates of interest' in the survival analysis, which can be considered control variables.
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