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 535 cells/μl (IQR: 420-712), and 83% had HIV RNA of at least 500 copies/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.
RCT Entities:
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-infectedparticipants 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 535 cells/μl (IQR: 420-712), and 83% had HIV RNA of at least 500 copies/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.
Authors: Frank J Palella; Rose K Baker; Anne C Moorman; Joan S Chmiel; Kathleen C Wood; John T Brooks; Scott D Holmberg Journal: J Acquir Immune Defic Syndr Date: 2006-09 Impact factor: 3.731
Authors: P A Sakkinen; E M Macy; P W Callas; E S Cornell; T E Hayes; L H Kuller; R P Tracy Journal: Am J Epidemiol Date: 1999-02-01 Impact factor: 4.897
Authors: Amanda Mocroft; Alan R Lifson; Giota Touloumi; Jacqueline Neuhaus; Zoe Fox; Adrian Palfreeman; Michael J Vjecha; Sally Hodder; Stephane De Wit; Jens D Lundgren; Andrew N Phillips Journal: Antivir Ther Date: 2011
Authors: Amanda Mocroft; Peter Reiss; Jacek Gasiorowski; Bruno Ledergerber; Justyna Kowalska; Antonio Chiesi; Jose Gatell; Aza Rakhmanova; Margaret Johnson; Ole Kirk; Jens Lundgren Journal: J Acquir Immune Defic Syndr Date: 2010-10 Impact factor: 3.731
Authors: Jason V Baker; Grace Peng; Joshua Rapkin; Donald I Abrams; Michael J Silverberg; Rodger D MacArthur; Winston P Cavert; W Keith Henry; James D Neaton Journal: AIDS Date: 2008-04-23 Impact factor: 4.177
Authors: Jeffrey A Tice; Steven R Cummings; Rebecca Smith-Bindman; Laura Ichikawa; William E Barlow; Karla Kerlikowske Journal: Ann Intern Med Date: 2008-03-04 Impact factor: 25.391
Authors: Judith J Lok; Peter W Hunt; Ann C Collier; Constance A Benson; Mallory D Witt; Amneris E Luque; Steven G Deeks; Ronald J Bosch Journal: AIDS Date: 2013-08-24 Impact factor: 4.177
Authors: Birgit Grund; Jason V Baker; Steven G Deeks; Julian Wolfson; Deborah Wentworth; Alessandro Cozzi-Lepri; Calvin J Cohen; Andrew Phillips; Jens D Lundgren; James D Neaton Journal: PLoS One Date: 2016-05-12 Impact factor: 3.240
Authors: Daniel D Murray; Kazuo Suzuki; Matthew Law; Jonel Trebicka; Jacquie Neuhaus; Deborah Wentworth; Margaret Johnson; Michael J Vjecha; Anthony D Kelleher; Sean Emery Journal: PLoS One Date: 2015-10-14 Impact factor: 3.240