Development and validation of a prediction tool to support engagement in HIV care among young people ages 10–24 years in Kenya

Kate Wilson, Kawango Agot, Jessica Dyer, Jacinta Badia, James Kibugi, Risper Bosire, Jillian Neary, Irene Inwani, Kristin Beima-Sofie, Seema Shah, Nahida Chakhtoura, Grace John-Stewart and Pamela Kohler

PLOS ONE, 2023, vol. 18, issue 6, 1-17

Abstract: Introduction: Loss to follow-up (LTFU) among adolescents and young adults living with HIV (AYALWH) is a barrier to optimal health and HIV services. We developed and validated a clinical prediction tool to identify AYALWH at risk of LTFU. Methods: We used electronic medical records (EMR) of AYALWH ages 10 to 24 in HIV care at 6 facilities in Kenya and surveys from a subset of participants. Early LTFU was defined as >30 days late for a scheduled visit in the last 6 months, which accounts for clients with multi-month refills. We developed a tool combining surveys with EMR (‘survey-plus-EMR tool’), and an ‘EMR-alone’ tool to predict high, medium, and low risk of LTFU. The survey-plus-EMR tool included candidate sociodemographics, partnership status, mental health, peer support, any unmet clinic needs, WHO stage, and time in care variables for tool development, while the EMR-alone included clinical and time in care variables only. Tools were developed in a 50% random sample of the data and internally validated using 10-fold cross-validation of the full sample. Tool performance was evaluated using Hazard Ratios (HR), 95% Confidence Intervals (CI), and area under the curve (AUC) ≥ 0.7 for good performance and ≥0.60 for modest performance. Results: Data from 865 AYALWH were included in the survey-plus-EMR tool and early LTFU was (19.2%, 166/865). The survey-plus-EMR tool ranged from 0 to 4, including PHQ-9 ≥5, lack of peer support group attendance, and any unmet clinical need. High (3 or 4) and medium (2) prediction scores were associated with greater risk of LTFU (high, 29.0%, HR 2.16, 95%CI: 1.25–3.73; medium, 21.4%, HR 1.52, 95%CI: 0.93–2.49, global p-value = 0.02) in the validation dataset. The 10-fold cross validation AUC was 0.66 (95%CI: 0.63–0.72). Data from 2,696 AYALWH were included in the EMR-alone tool and early LTFU was 28.6% (770/2,696). In the validation dataset, high (score = 2, LTFU = 38.5%, HR 2.40, 95%CI: 1.17–4.96) and medium scores (1, 29.6%, HR 1.65, 95%CI: 1.00–2.72) predicted significantly higher LTFU than low-risk scores (0, 22.0%, global p-value = 0.03). Ten-fold cross-validation AUC was 0.61 (95%CI: 0.59–0.64). Conclusions: Clinical prediction of LTFU was modest using the surveys-plus-EMR tool and the EMR-alone tool, suggesting limited use in routine care. However, findings may inform future prediction tools and intervention targets to reduce LTFU among AYALWH.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0286240

DOI: 10.1371/journal.pone.0286240

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