Win Min Han1,2, Rimke Bijker1, Ezhilarasi Chandrasekaran3, Sanjay Pujari4, Oon Tek Ng5, Penh Sun Ly6, Man-Po Lee7, Kinh Van Nguyen8, Yu-Jiun Chan9, Cuong Duy Do10, Jun Yong Choi11, Romanee Chaiwarith12, Tuti Parwati Merati13, Sasisopin Kiertiburanakul14, Iskandar Azwa15, Suwimon Khusuwan16, Fujie Zhang17, Yasmin Mohamed Gani18, Junko Tanuma19, Shashikala Sangle20, Rossana Ditangco21, Evy Yunihastuti22, Jeremy Ross23, Anchalee Avihingsanon2,24. 1. Kirby Institute, UNSW, Sydney, Australia. 2. HIV-NAT, Thai Red Cross AIDS Research Centre, Bangkok, Thailand. 3. Chennai Antiviral Research and Treatment Clinical Research Site (CART CRS), VHS-Infectious Diseases Medical Centre, VHS, Chennai, India. 4. Institute of Infectious Diseases, Pune, India. 5. Tan Tock Seng Hospital, Singapore. 6. National Center for HIV/AIDS, Dermatology & STDs, Phnom Penh, Cambodia. 7. Queen Elizabeth Hospital, Hong Kong SAR. 8. National Hospital for Tropical Diseases, Hanoi, Vietnam. 9. Taipei Veterans General Hospital, Taipei, Taiwan. 10. Bach Mai Hospital, Hanoi, Vietnam. 11. Division of Infectious Diseases, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea. 12. Research Institute for Health Sciences, Chiang Mai, Thailand. 13. Faculty of Medicine Udayana University & Sanglah Hospital, Bali, Indonesia. 14. Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand. 15. University Malaya Medical Centre, Kuala Lumpur, Malaysia. 16. Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand. 17. Beijing Ditan Hospital, Capital Medical University, Beijing, China. 18. Hospital Sungai Buloh, Sungai Buloh, Malaysia. 19. National Center for Global Health and Medicine, Tokyo, Japan. 20. BJ Government Medical College and Sassoon General Hospital, Pune, India. 21. Research Institute for Tropical Medicine, Muntinlupa City, Philippines. 22. Faculty of Medicine Universitas Indonesia-Dr. Cipto Mangunkusumo General Hospital, Jakarta, Indonesia. 23. TREAT Asia, amfAR-The Foundation for AIDS Research, Bangkok, Thailand; and. 24. Tuberculosis Research Unit, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Abstract
BACKGROUND: We validated the Data collection on Adverse events of anti-HIV Drugs (D:A:D) full-risk and short-risk score models for chronic kidney disease (CKD) in the Asian HIV cohorts. SETTINGS: A validation study among people living with HIV (PLHIV) aged ≥18 years among the cohorts in the Asia-Pacific region. METHODS: PLHIV with a baseline estimated glomerular filtration rate > 60 mL/min/1.73 m were included for validation of the D:A:D CKD full version and short version without cardiovascular risk factors. Those with <3 estimated glomerular filtration rate measurements from baseline or previous exposure to potentially nephrotoxic antiretrovirals were excluded. Kaplan-Meier methods were used to estimate the probability of CKD development. The area under the receiver operating characteristics was also used to validate the risk score. RESULTS: We included 5701 participants in full model {median 8.1 [interquartile range (IQR) 4.8-10.9] years follow-up} and 9791 in short model validation [median 4.9 (IQR 2.5-7.3) years follow-up]. The crude incidence rate of CKD was 8.1 [95% confidence interval (CI): 7.3 to 8.9] per 1000 person-years in the full model cohort and 10.5 (95% CI: 9.6 to 11.4) per 1000 person-years in the short model cohort. The progression rates for CKD at 10 years in the full model cohort were 2.7%, 8.9%, and 26.1% for low-risk, medium-risk, and high-risk groups, and 3.5%, 11.7%, and 32.4% in the short model cohort. The area under the receiver operating characteristics for the full-risk and short-risk score was 0.81 (95% CI: 0.79 to 0.83) and 0.83 (95% CI: 0.81 to 0.85), respectively. CONCLUSION: The D:A:D CKD full-risk and short-risk score performed well in predicting CKD events among Asian PLHIV. These risk prediction models may be useful to assist clinicians in identifying individuals at high risk of developing CKD.
BACKGROUND: We validated the Data collection on Adverse events of anti-HIV Drugs (D:A:D) full-risk and short-risk score models for chronic kidney disease (CKD) in the Asian HIV cohorts. SETTINGS: A validation study among people living with HIV (PLHIV) aged ≥18 years among the cohorts in the Asia-Pacific region. METHODS: PLHIV with a baseline estimated glomerular filtration rate > 60 mL/min/1.73 m were included for validation of the D:A:D CKD full version and short version without cardiovascular risk factors. Those with <3 estimated glomerular filtration rate measurements from baseline or previous exposure to potentially nephrotoxic antiretrovirals were excluded. Kaplan-Meier methods were used to estimate the probability of CKD development. The area under the receiver operating characteristics was also used to validate the risk score. RESULTS: We included 5701 participants in full model {median 8.1 [interquartile range (IQR) 4.8-10.9] years follow-up} and 9791 in short model validation [median 4.9 (IQR 2.5-7.3) years follow-up]. The crude incidence rate of CKD was 8.1 [95% confidence interval (CI): 7.3 to 8.9] per 1000 person-years in the full model cohort and 10.5 (95% CI: 9.6 to 11.4) per 1000 person-years in the short model cohort. The progression rates for CKD at 10 years in the full model cohort were 2.7%, 8.9%, and 26.1% for low-risk, medium-risk, and high-risk groups, and 3.5%, 11.7%, and 32.4% in the short model cohort. The area under the receiver operating characteristics for the full-risk and short-risk score was 0.81 (95% CI: 0.79 to 0.83) and 0.83 (95% CI: 0.81 to 0.85), respectively. CONCLUSION: The D:A:D CKD full-risk and short-risk score performed well in predicting CKD events among Asian PLHIV. These risk prediction models may be useful to assist clinicians in identifying individuals at high risk of developing CKD.
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