ArticleBMC medical informatics and decision making2026
Development and validation of a nomogram model for predicting negative/indeterminate HIV-1 antibody confirmation: a strategy to streamline the diagnostic pathway.
Article in BMC medical informatics and decision making, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThe 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.
methodsA 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.
resultsMultivariate 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.
conclusionsThe 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 registrationNot applicable.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.