Objective: To evaluate the change in categories of risk of death by adding D-dimer to conventional mortality risk factors. Design: Cohort study. Methods: Data on HIV-infected participants receiving standard combination antiretroviral therapy in two clinical trials (Evaluation of Subcutaneous Proleukin in a Randomized International Trial and Strategic Management of antiretroviral therapy), who had baseline D-dimer measured, were randomly split into two equal training and a validation datasets. A multivariable survival model was built using the training dataset and included only conventional mortality risk factors measured at baseline. D-dimer was added to create the comparison model. The level of reclassification of mortality risk, for those with at least 5-years of follow-up, was then assessed by tabulating mortality risk defined as low (≤2% predicted rate), moderate (2-5%) or high (>5%). Reclassification analyses were then repeated on the validation dataset. Results: The analysis population at baseline had a mean age of 43 years, median CD4 cell count of 535cells/μl (IQR: 420-712), and 83% had HIV RNA of at least 500copies/ml. In the training dataset (n=1946, 8939 person-years), there were 83 deaths at a rate of 0.93 per 100 person-years. Addition of D-dimer to the reference model resulted in 6% or fewer (P>0.05) being correctly reassigned, either up or down, to a new risk category, in both, training and validation datasets. The integrated discrimination improvement in training and validation datasets was 0.60% (P=0.084) and 0.45% (P=0.168), respectively. Conclusion: In this relatively well population, at the given risk cutoffs, D-dimer appeared to only modestly improve the discernment of risk. Risk reclassification provides a method for assessing the clinical utility of biomarkers in HIV cohort studies.
- cohort analysis
- net reclassification improvement
- risk assessment