TY - JOUR
T1 - Development of Frail RISC-HIV
T2 - A Risk Score for Predicting Frailty Risk in the Short-term for Care of People with HIV
AU - Ruderman, Stephanie A.
AU - Nance, Robin M.
AU - Drumright, Lydia N.
AU - Whitney, Bridget M.
AU - Hahn, Andrew W.
AU - Ma, Jimmy
AU - Haidar, Lara
AU - Eltonsy, Sherif
AU - Mayer, Kenneth H.
AU - Eron, Joseph J.
AU - Greene, Meredith
AU - Mathews, William C.
AU - Webel, Allison
AU - Saag, Michael S.
AU - Willig, Amanda L.
AU - Kamen, Charles
AU - McCaul, Mary
AU - Chander, Geetanjali
AU - Cachay, Edward
AU - Lober, William B.
AU - Pandya, Chintan
AU - Cartujano-Barrera, Francisco
AU - Kritchevsky, Stephen B.
AU - Austad, Steven N.
AU - Landay, Alan
AU - Kitahata, Mari M.
AU - Crane, Heidi M.
AU - Delaney, Joseph A.C.
N1 - Publisher Copyright:
© 2023 Lippincott Williams and Wilkins. All rights reserved.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - Objective:Frailty is common among people with HIV (PWH), so we developed frail risk in the short-term for care (RISC)-HIV, a frailty prediction risk score for HIV clinical decision-making.Design:We followed PWH for up to 2 years to identify short-term predictors of becoming frail.Methods:We predicted frailty risk among PWH at seven HIV clinics across the United States. A modified self-reported Fried Phenotype captured frailty, including fatigue, weight loss, inactivity, and poor mobility. PWH without frailty were separated into training and validation sets and followed until becoming frail or 2 years. Bayesian Model Averaging (BMA) and five-fold-cross-validation Lasso regression selected predictors of frailty. Predictors were selected by BMA if they had a greater than 45% probability of being in the best model and by Lasso if they minimized mean squared error. We included age, sex, and variables selected by both BMA and Lasso in Frail RISC-HIV by associating incident frailty with each selected variable in Cox models. Frail RISC-HIV performance was assessed in the validation set by Harrell's C and lift plots.Results:Among 3170 PWH (training set), 7% developed frailty, whereas among 1510 PWH (validation set), 12% developed frailty. BMA and Lasso selected baseline frailty score, prescribed antidepressants, prescribed antiretroviral therapy, depressive symptomology, and current marijuana and illicit opioid use. Discrimination was acceptable in the validation set, with Harrell's C of 0.76 (95% confidence interval: 0.73-0.79) and sensitivity of 80% and specificity of 61% at a 5% frailty risk cutoff.Conclusions:Frail RISC-HIV is a simple, easily implemented tool to assist in classifying PWH at risk for frailty in clinics.
AB - Objective:Frailty is common among people with HIV (PWH), so we developed frail risk in the short-term for care (RISC)-HIV, a frailty prediction risk score for HIV clinical decision-making.Design:We followed PWH for up to 2 years to identify short-term predictors of becoming frail.Methods:We predicted frailty risk among PWH at seven HIV clinics across the United States. A modified self-reported Fried Phenotype captured frailty, including fatigue, weight loss, inactivity, and poor mobility. PWH without frailty were separated into training and validation sets and followed until becoming frail or 2 years. Bayesian Model Averaging (BMA) and five-fold-cross-validation Lasso regression selected predictors of frailty. Predictors were selected by BMA if they had a greater than 45% probability of being in the best model and by Lasso if they minimized mean squared error. We included age, sex, and variables selected by both BMA and Lasso in Frail RISC-HIV by associating incident frailty with each selected variable in Cox models. Frail RISC-HIV performance was assessed in the validation set by Harrell's C and lift plots.Results:Among 3170 PWH (training set), 7% developed frailty, whereas among 1510 PWH (validation set), 12% developed frailty. BMA and Lasso selected baseline frailty score, prescribed antidepressants, prescribed antiretroviral therapy, depressive symptomology, and current marijuana and illicit opioid use. Discrimination was acceptable in the validation set, with Harrell's C of 0.76 (95% confidence interval: 0.73-0.79) and sensitivity of 80% and specificity of 61% at a 5% frailty risk cutoff.Conclusions:Frail RISC-HIV is a simple, easily implemented tool to assist in classifying PWH at risk for frailty in clinics.
KW - HIV
KW - aging
KW - frailty
KW - prediction
KW - risk score
UR - http://www.scopus.com/inward/record.url?scp=85152174692&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85152174692&partnerID=8YFLogxK
U2 - 10.1097/QAD.0000000000003501
DO - 10.1097/QAD.0000000000003501
M3 - Article
C2 - 36723488
AN - SCOPUS:85152174692
SN - 0269-9370
VL - 37
SP - 967
EP - 975
JO - AIDS
JF - AIDS
IS - 6
ER -