Jessie K Edwards1, Catherine R Lesko2, Michael E Herce3,4, Gad Murenzi5, Christella Twizere6, Patricia Lelo7, Kathryn Anastos8, Olga Tymejczyk9, Marcel Yotebieng10, Denis Nash9, Adebola Adedimeji10, Andrew Edmonds1. 1. From the Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC. 2. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. 3. Institute for Global Health and Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, NC. 4. Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia. 5. Rwanda Military Hospital, Kigali, Rwanda. 6. Centre Hospitalo, Universitaire de Kamenge, Bujumbura, Burundi. 7. Kalembelembe Pediatric Hospital, Kinshasa, Democratic Republic of the Congo. 8. Departments of Medicine and Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY. 9. Institute for Implementation Science in Population Health, City University of New York, New York, NY. 10. Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY.
Abstract
BACKGROUND: In some time-to-event analyses, it is unclear whether loss to follow up should be treated as a censoring event or competing event. Such ambiguity is particularly common in HIV research that uses routinely collected clinical data to report the timing of key milestones along the HIV care continuum. In this setting, loss to follow up may be viewed as a censoring event, under the assumption that patients who are "lost" from a study clinic immediately enroll in care elsewhere, or a competing event, under the assumption that people "lost" are out of care all together. METHODS: We illustrate an approach to address this ambiguity when estimating the 2-year risk of antiretroviral treatment initiation among 19,506 people living with HIV who enrolled in the IeDEA Central Africa cohort between 2006 and 2017, along with published estimates from tracing studies in Africa. We also assessed the finite sample properties of the proposed approach using simulation experiments. RESULTS: The estimated 2-year risk of treatment initiation was 69% if patients were censored at loss to follow up or 59% if losses to follow up were treated as competing events. Using the proposed approach, we estimated that the 2-year risk of antiretroviral therapy initiation was 62% (95% confidence interval: 61, 62). The proposed approach had little bias and appropriate confidence interval coverage under scenarios examined in the simulation experiments. CONCLUSIONS: The proposed approach relaxes the assumptions inherent in treating loss to follow up as a censoring or competing event in clinical HIV cohort studies.
BACKGROUND: In some time-to-event analyses, it is unclear whether loss to follow up should be treated as a censoring event or competing event. Such ambiguity is particularly common in HIV research that uses routinely collected clinical data to report the timing of key milestones along the HIV care continuum. In this setting, loss to follow up may be viewed as a censoring event, under the assumption that patients who are "lost" from a study clinic immediately enroll in care elsewhere, or a competing event, under the assumption that people "lost" are out of care all together. METHODS: We illustrate an approach to address this ambiguity when estimating the 2-year risk of antiretroviral treatment initiation among 19,506 people living with HIV who enrolled in the IeDEA Central Africa cohort between 2006 and 2017, along with published estimates from tracing studies in Africa. We also assessed the finite sample properties of the proposed approach using simulation experiments. RESULTS: The estimated 2-year risk of treatment initiation was 69% if patients were censored at loss to follow up or 59% if losses to follow up were treated as competing events. Using the proposed approach, we estimated that the 2-year risk of antiretroviral therapy initiation was 62% (95% confidence interval: 61, 62). The proposed approach had little bias and appropriate confidence interval coverage under scenarios examined in the simulation experiments. CONCLUSIONS: The proposed approach relaxes the assumptions inherent in treating loss to follow up as a censoring or competing event in clinical HIV cohort studies.
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