Refining a non-invasive prediction model for neurosyphilis diagnosis by using immunoassay to detect serum anti-TP0435 (TP17) and TP0574 (TP47) IgG antibodies: two-centre cross-sectional retrospective study in China.

OBJECTIVES: Invasive lumbar puncture is the conventional method for diagnosing neurosyphilis (NS). We investigated a non-invasive alternative method to detect serum Treponema pallidum-specific antibodies against highly immunogenic antigens TP0171 (TP15), TP0435 (TP17), and TP0574 (TP47) by using luciferase immunosorbent assay. METHODS: A total of 816 HIV-negative patients suspected of NS from the Beijing and Guangzhou cohorts were retrospectively selected and tested for serum anti-TP15, TP17, and TP47 IgG antibodies. Two diagnostic prediction models were developed using stepwise logistic regression in the Beijing cohort, and evaluated in the Guangzhou cohort for external validation. RESULTS: Serum antibodies against TP15, TP17, and TP47 showed moderate capability for NS diagnosis in the Beijing cohort and the corresponding area under the receiver operating characteristic curves (AUCs) were 0.722 [95% confidence interval (CI): 0.680-0.762)], 0.780 (95% CI: 0.741-0.817), and 0.774 (95% CI: 0.734-0.811), respectively. An expanded NS prediction model integrated with anti-TP17 and anti-TP47 antibodies showed better performance than the base NS diagnostic model without anti-TP17 and anti-TP47 antibodies with the AUC of 0.874 (95% CI: 0.841-0.906) vs. 0.845 (95% CI: 0.809-0.881) (p = 0.007) in the development cohort, and 0.934 (95% CI: 0.909-0.960) vs. 0.877 (95% CI: 0.840-0.914) (p < 0.001) in validation cohort, respectively. Decision curve analysis revealed that the net benefit of the expanded model exceeded that of the base model when the threshold probability was between 0.10 and 0.95 in both the development and external validation cohorts. DISCUSSION: Serum antibodies against TP17 and TP47 exhibited promising diagnostic capability for NS and significantly enhanced the predictive accuracy of model for NS diagnosis. Our study highlights the potential of serum treponemal antibody detection as a non-invasive method for NS diagnosis to substitute invasive lumbar puncture in NS diagnosis.

Evaluating the clinical utility of semi-quantitative luciferase immunosorbent assay using Treponema pallidum antigens in syphilis diagnosis and treatment monitoring.

To assess the clinical applicability of a semi-quantitative luciferase immunosorbent assay (LISA) for detecting antibodies against Treponema pallidum antigens TP0171 (TP15), TP0435 (TP17), and TP0574 (TP47) in diagnosing and monitoring syphilis. LISA for detection of anti-TP15, TP17, and TP47 antibodies were developed and evaluated for syphilis diagnosis using 261 serum samples (161 syphilis, 100 non-syphilis). Ninety serial serum samples from 6 syphilis rabbit models (3 treated, 3 untreated) and 110 paired serum samples from 55 syphilis patients were used to assess treatment effects by utilizing TRUST as a reference. Compared to TPPA, LISA-TP15, LISA-TP17, and LISA-TP47 showed a sensitivity of 91.9%, 96.9%, and 98.8%, specificity of 99%, 99%, and 98%, and AUC of 0.971, 0.992, and 0.995, respectively, in diagnosing syphilis. Strong correlations (rs = 0.89-0.93) with TPPA were observed. In serial serum samples from rabbit models, significant differences in the relative light unit (RLU) were observed between the treatment and control group for LISA-TP17 (days 31-51) and LISA-TP47 (day 41). In paired serum samples from syphilis patients, TRUST titres and the RLU of LISA-TP15, LISA-TP17, and LISA-TP47 decreased post-treatment (P < .001). When TRUST titres decreased by 0, 2, 4, or ≥8-folds, the RLU decreased by 17.53%, 31.34%, 48.62%, and 72.79% for LISA-TP15; 8.84%, 17.00%, 28.37%, and 50.57% for LISA-TP17; 22.25%, 29.79%, 51.75%, and 70.28% for LISA-TP47, respectively. Semi-quantitative LISA performs well for syphilis diagnosis while LISA-TP17 is more effective for monitoring syphilis treatment in rabbit models and clinical patients.

Diagnosis of neurosyphilis in HIV-negative patients with syphilis: development, validation, and clinical utility of a suite of machine learning models.

Background: The ability to accurately identify the absolute risk of neurosyphilis diagnosis for patients with syphilis would allow preventative and therapeutic interventions to be delivered to patients at high-risk, sparing patients at low-risk from unnecessary care. We aimed to develop, validate, and evaluate the clinical utility of simplified clinical diagnostic models for neurosyphilis diagnosis in HIV-negative patients with syphilis. Methods: We searched PubMed, China National Knowledge Infrastructure and UpToDate for publications about neurosyphilis diagnostic guidelines in English or Chinese from database inception until March 15, 2023. We developed and validated machine learning models with a uniform set of predictors based on six authoritative diagnostic guidelines across four continents to predict neurosyphilis using routinely collected data from real-world clinical practice in China and the United States (through the Dermatology Hospital of Southern Medical University in Guangzhou [659 recruited between August 2012 and March 2022, treated as Development cohort], the Beijing Youan Hospital of Capital Medical University in Beijng [480 recruited between December 2013 and April 2021, treated as External cohort 1], the Zhongshan Hospital of Xiamen University in Xiamen [493 recruited between November 2005 and November 2021, treated as External cohort 2] from China, and University of Washington School of Medicine in Seattle [16 recruited between September 2002 and April 2014, treated as External cohort 3] from United States). We included all these patients with syphilis into our analysis, and no patients were further excluded. We trained eXtreme gradient boosting (XGBoost) models to predict the diagnostic outcome of neurosyphilis according to each diagnostic guideline in two scenarios, respectively. Model performance was measured through both internal and external validation in terms of discrimination and calibration, and clinical utility was evaluated using decision curve analysis. Findings: The final simplified clinical diagnostic models included neurological symptoms, cerebrospinal fluid (CSF) protein, CSF white blood cell, and CSF venereal disease research laboratory test/rapid plasma reagin. The models showed good calibration with rescaled Brier score of 0.99 (95% CI 0.98-1.00) and excellent discrimination (the minimum value of area under the receiver operating characteristic curve, 0.84; 95% CI 0.81-0.88) when externally validated. Decision curve analysis demonstrated that the models were useful across a range of neurosyphilis probability thresholds between 0.33 and 0.66 compared to the alternatives of managing all patients with syphilis as if they do or do not have neurosyphilis. Interpretation: The simplified clinical diagnostic models comprised of readily available data show good performance, are generalisable across clinical settings, and have clinical utility over a broad range of probability thresholds. The models with a uniform set of predictors can simplify the sophisticated clinical diagnosis of neurosyphilis, and guide decisions on delivery of neurosyphilis health-care, ultimately, support accurate diagnosis and necessary treatment. Funding: The Natural Science Foundation of China General Program, Health Appropriate Technology Promotion Project of Guangdong Medical Research Foundation, Department of Science and technology of Guangdong Province Xinjiang Rural Science and Technology（Special Commissioner）Project, Southern Medical University Clinical Research Nursery Garden Project, Beijing Municipal Administration of Hospitals Incubating Program.