Evidence map›Paper›PMID 42410424›Full record

ArticleBMC women's health2026

Clinical evaluation of Candida albicans enolase 1 as a novel biomarker for vulvovaginal candidiasis: a pilot study demonstrating rule-out capability.

Hanbing Meng, Huimin Xing, Qingqing Sun, Fang Li, Zhengxin He

Abstract read
In one paragraph

Article in BMC women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Hanbing Meng *Basic medical laboratory, Bethune International Peace Hospital, No. 398 Zhongshan West Road, Shijiazhuang, Hebei, 050082, P.R. China.
Huimin Xing *Obstetrics and Gynecology Department, Shijiazhuang Maternity & Child Healthcare Hospital, No. 396 South Youyi Street, Shijiazhuang, 050091, China.
Qingqing SunBasic medical laboratory, Bethune International Peace Hospital, No. 398 Zhongshan West Road, Shijiazhuang, Hebei, 050082, P.R. China.
Fang LiDepartment of Laboratory Medicine, Bethune International Peace Hospital, No. 398 Zhongshan West Road, Shijiazhuang, Hebei, 050082, P.R. China.
Zhengxin HeBasic medical laboratory, Bethune International Peace Hospital, No. 398 Zhongshan West Road, Shijiazhuang, Hebei, 050082, P.R. China. hezx1979@126.com.ORCID 0000-0002-8642-2866

Funding

Natural Science Foundation of Hebei province, China C2021505001
6 · The paper itself

Abstract

purposeVulvovaginal candidiasis (VVC) affects approximately 75% of women during their lifetime, yet current diagnostic methods have limitations. This pilot study evaluated Candida albicans enolase 1 (CaEno1) as a diagnostic biomarker for C. albicans-associated VVC, with a view to informing future point-of-care test (POCT) development.

methodsA total of 131 vaginal secretion samples were collected from patients presenting with vulvovaginal symptoms at a gynecology department. Samples underwent routine microscopic examination, fungal culture, and CaEno1 detection using a previously developed double-antibody sandwich ELISA (DAbS-ELISA) with sensitivity of 0.33 ng/mL. ROC curve analysis determined optimal diagnostic performance parameters.

resultsAmong 131 samples, 33 (25.2%) showed positive fungal growth, with C. albicans predominating (72.7% of positive cultures). CaEno1 levels were significantly higher in C. albicans-positive samples compared to negative samples (Mann-Whitney U test, P < 0.0001). ROC analysis yielded an area under the curve of 0.727 (95% CI: 0.613-0.842). At an optimal cutoff value of 0.052 optical density units at 450 nm (OD450), the assay demonstrated 70.8% sensitivity, 78.5% specificity, 42.5% positive predictive value (PPV), and 92.3% negative predictive value (NPV).

conclusionThis study provides the first clinical evidence that CaEno1 can be detected in vaginal secretions and suggests potential rule-out utility for Candida-associated VVC in settings where C. albicans predominates. The favorable NPV observed in this cohort supports its potential use as a screening tool in comparable clinical settings, though cross-reactivity with non-albicans species warrants cautious interpretation alongside clinical findings.

Indexed as

Candida albicansCandidiasis, VulvovaginalPhosphopyruvate HydrataseAdultBiomarkersEnzyme-Linked Immunosorbent AssayFemaleHumansPilot ProjectsROC CurveSensitivity and SpecificityVaginaBiomarkersPhosphopyruvate HydrataseBiomarkerCandida albicans enolase 1DiagnosisELISAFungal cultureVvulvovaginal candidiasis

Identifiers

PMID42410424
PMCPMC13428439

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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.