Work

Development and validation of a nomogram model for predicting negative/indeterminate HIV-1 antibody confirmation: a strategy to streamline the diagnostic pathway

Year: 2026

Type: article

Abstract: BACKGROUND: The standard HIV diagnostic algorithm comprises sequential serological screening, confirmatory antibody testing, and nucleic acid confirmation when necessary. This multi-step process often causes diagnostic delays, particularly in cases with indeterminate or discordant results. Developing a Nomogram-based predictive tool to identify individuals at high risk of anti-HIV-1 negative or inconclusive antibody confirmation could significantly optimize testing efficiency. METHODS: A total of 2,468 individuals with HIV reactive screening results were randomly divided into a training set (70%) and a validation set (30%). In the training set, the risk factors of anti-HIV-1 negative/inconclusive results were identified by univariate and multivariate logistic regression models to construct a predictive model, and its internal stability was robustly assessed via 1,000-resample bootstrap validation. In the validation set, the Hosmer-Lemeshow test and calibration curves were used to evaluate the consistency of the model, while the receiver operating characteristic (ROC) curve was utilized to assess its discriminative ability. RESULTS: Multivariate analysis identified Gender, Education, voluntary counseling and testing (VCT), and Retesting results as independent predictors. Internal bootstrap validation confirmed excellent model stability (optimism-corrected C-index = 0.862). Furthermore, the model demonstrated good predictive performance with high discrimination ability (area under the ROC curve [AUC] = 0.874, 95% CI: 0.826-0.922) and calibration accuracy (Hosmer-Lemeshow test, P = 0.098) in the validation set. CONCLUSIONS: The nomogram accurately identifies individuals at high risk of negative/inconclusive antibody confirmation, enabling a streamlined two-step testing pathway that bypasses Western blot(WB) for selected cases. This approach reduces diagnostic delay and resource utilization while maintaining accuracy, offering a practical strategy for optimizing HIV testing services in diverse settings. TRIAL REGISTRATION: Not applicable.

Source: BMC Medical Informatics and Decision Making

DOI: 10.1186/s12911-026-03546-6