ArticlePLoS neglected tropical diseases2019
A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.
Article in PLoS neglected tropical diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- On the usage of artificial intelligence in leprosy care: A systematic literature review.PLoS computational biology · 2025Pooled it
- Development and validation of a machine learning approach for screening new leprosy cases based on the leprosy suspicion questionnaire.Scientific reports · 2025Article
- Molecular Detection ofTropical medicine and infectious disease · 2025Review
- Artificial intelligence in assisting pathogenic microorganism diagnosis and treatment: a review of infectious skin diseases.Frontiers in microbiology · 2024Review
- Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review.Journal of clinical medicine · 2023Review
- High seropositivity against NDO-LID in a group of household contacts of leprosy patients. Are we close to leprosy elimination in Colombia?Pathogens and global health · 2023Observational
- Leprosy among new child cases in China: Epidemiological and clinical analysis from 2011 to 2020.PLoS neglected tropical diseases · 2023Article
- Prediction of the occurrence of leprosy reactions based on Bayesian networks.Frontiers in medicine · 2023Article
- Interplay among differential exposure toFrontiers in immunology · 2023Article
- ELISA Test Based on the Phenolic Glycolipid-I (PGL-I) ofPathogens (Basel, Switzerland) · 2022Article
- Community intervention programmes with people affected by leprosy: Listening to the voice of professionals.PLoS neglected tropical diseases · 2022Article
- Leprosy: A Review of Epidemiology, Clinical Diagnosis, and Management.Journal of tropical medicine · 2022Review
- RLEP LAMP for the laboratory confirmation of leprosy: towards a point-of-care test.BMC infectious diseases · 2021Article
- Blood RNA signature RISK4LEP predicts leprosy years before clinical onset.EBioMedicine · 2021Article
- Leprosy Screening Based on Artificial Intelligence: Development of a Cross-Platform App.JMIR mHealth and uHealth · 2021Article
- Serum IgA Antibodies Specific toFrontiers in medicine · 2021Article
- Functional biomarker signatures of circulating T-cells and its association with distinct clinical status of leprosy patients and their respective household contacts.Infectious diseases of poverty · 2020Article
- Leprosy surveillance study in a highly endemic Brazilian area using leprosy specific serologic tests and IFNγ whole blood assay.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2020Article
- Prospects for new leprosy diagnostic tools, a narrative review considering ELISA and PCR assays.Revista da Sociedade Brasileira de Medicina Tropical · 2020Review
- Genomic Characterization ofFrontiers in microbiology · 2020Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly detection of Mycobacterium leprae is a key strategy for disrupting the transmission chain of leprosy and preventing the potential onset of physical disabilities. Clinical diagnosis is essential, but some of the presented symptoms may go unnoticed, even by specialists. In areas of greater endemicity, serological and molecular tests have been performed and analyzed separately for the follow-up of household contacts, who are at high risk of developing the disease. The accuracy of these tests is still debated, and it is necessary to make them more reliable, especially for the identification of cases of leprosy between contacts. We proposed an integrated analysis of molecular and serological methods using artificial intelligence by the random forest (RF) algorithm to better diagnose and predict new cases of leprosy.
methodsThe study was developed in Governador Valadares, Brazil, a hyperendemic region for leprosy. A longitudinal study was performed, including new cases diagnosed in 2011 and their respective household contacts, who were followed in 2011, 2012, and 2016. All contacts were diligently evaluated by clinicians from Reference Center for Endemic Diseases (CREDEN-PES) before being classified as asymptomatic. Samples of slit skin smears (SSS) from the earlobe of the patients and household contacts were collected for quantitative polymerase chain reaction (qPCR) of 16S rRNA, and peripheral blood samples were collected for ELISA assays to detect LID-1 and ND-O-LID.
resultsThe statistical analysis of the tests revealed sensitivity for anti-LID-1 (63.2%), anti-ND-O-LID (57.9%), qPCR SSS (36.8%), and smear microscopy (30.2%). However, the use of RF allowed for an expressive increase in sensitivity in the diagnosis of multibacillary leprosy (90.5%) and especially paucibacillary leprosy (70.6%). It is important to report that the specificity was 92.5%.
conclusionThe proposed model using RF allows for the diagnosis of leprosy with high sensitivity and specificity and the early identification of new cases among household contacts.
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