A standardized algorithm for determining the underlying cause of death in HIV infection as AIDS or non-AIDS related: results from the EuroSIDA study

• Published in: HIV clinical trials Vol. 12; no. 2; p. 109
• Main Authors: Kowalska, Justyna D, Mocroft, Amanda, Ledergerber, Bruno, Florence, Eric, Ristola, Matti, Begovac, Josip, Sambatakou, Helen, Pedersen, Court, Lundgren, Jens D, Kirk, Ole
• Format: Journal Article
• Language: English
• Published: England 01-04-2011
• Subjects: Acquired Immunodeficiency Syndrome - mortality; Algorithms; Cause of Death; CD4 Lymphocyte Count; HIV-1; Humans; Prospective Studies
• ISSN: 1528-4336
• DOI: 10.1310/hct1202-109

Analyzing changes in causes of death over time is essential for understanding the emerging trends in HIV population mortality, yet data on cause of death are often missing. This poses analytic limitations, as does the changing approach in data collection by longitudinal studies, which are a natural consequence of an increased awareness and knowledge in the field. To monitor and analyze changes in mortality over time, we have explored this issue within the EuroSIDA study and propose a standardized protocol unifying data collected and allowing for classification of all deaths as AIDS or non-AIDS related, including events with missing cause of death.
Several classifications of the underlying cause of death as AIDS or non-AIDS related within the EuroSIDA study were compared: central classification (CC-reference group) based on an externally standardised method (the CoDe procedures), local cohort classification (LCC) as reported by the site investigator, and 4 algorithms (ALG) created based on survival times after specific AIDS events.
A total of 2,783 deaths occurred, 540 CoDe forms were collected, and 488 were used to evaluate agreements. The agreement between CC and LCC was substantial (κ = 0.7) and the agreement between CC and ALG was moderate (κ < 0.6). Consequently, a stepwise algorithm was derived prioritizing CC over LCC and, in patients with no information available, best-fit ALG. Using this algorithm, 1,332 (47.9%) deaths were classified as AIDS and 1,451 (52.1%) as non-AIDS related.
Our proposed stepwise algorithm for classifying deaths provides a valuable tool for future research, however validation in another setting is warranted.