Latent Class Analysis: Insights about design and analysis of schistosomiasis diagnostic studies

Sampling is decisive to determination of Leishmania (Viannia) species

BACKGROUND

Accuracy of molecular tools for the identification of parasites that cause human cutaneous leishmaniasis (CL) could largely depend on the sampling method. Non-invasive or less-invasive sampling methods such as filter paper imprints and cotton swabs are preferred over punch biopsies and lancet scrapings for detection methods of Leishmania based on polymerase chain reaction (PCR) because they are painless, simple, and inexpensive, and of benefit to military and civilian patients to ensure timely treatment. However, different types of samples can generate false negatives and there is a clear need to demonstrate which sample is more proper for molecular assays.

METHODOLOGY

Here, we compared the sensitivity of molecular identification of different Leishmania (Viannia) species from Peru, using three types of sampling: punch biopsy, filter paper imprint and lancet scraping. Different composite reference standards and latent class models allowed to evaluate the accuracy of the molecular tools. Additionally, a quantitative PCR assessed variations in the results and parasite load in each type of sample.

PRINCIPAL FINDINGS

Different composite reference standards and latent class models determined higher sensitivity when lancet scrapings were used for sampling in the identification and determination of Leishmania (Viannia) species through PCR-based assays. This was consistent for genus identification through kinetoplastid DNA-PCR and for the determination of species using FRET probes-based Nested Real-Time PCR. Lack of species identification in some samples correlated with the low intensity of the PCR electrophoretic band, which reflects the low parasite load in samples.

CONCLUSIONS

The type of clinical sample can directly influence the detection and identification of Leishmania (Viannia) species. Here, we demonstrated that lancet scraping samples consistently allowed the identification of more leishmaniasis cases compared to filter paper imprints or biopsies. This procedure is inexpensive, painless, and easy to implement at the point of care and avoids the need for anesthesia, surgery, and hospitalization and therefore could be used in resource limited settings for both military and civilian populations.

Bayesian diagnostic test evaluation and true prevalence estimation of malnutrition in gastric cancer patients

BACKGROUND & AIMS

Malnutrition is prevalent among gastric cancer (GC) patients, necessitating early assessment of nutritional status to guide monitoring and interventions for improved outcomes. We aim to evaluate the accuracy and prognostic capability of three nutritional tools in GC patients, providing insights for clinical implementation.

METHODS

The present study is an analysis of data from 1308 adult GC patients recruited in a multicenter from July 2013 to July 2018. Nutritional status was assessed using Nutritional Risk Screening 2002 (NRS-2002), Patient-Generated Subjective Global Assessment (PG-SGA) and Global Leadership Initiative on Malnutrition (GLIM) criteria. Bayesian latent class model (LCM) estimated the malnutrition prevalence of GC patients, sensitivity and specificity of nutritional tools. Cox regression model analyzed the relationship between nutritional status and overall survival (OS) in GC patients.

RESULTS

Among 1308 GC patients, NRS-2002, PG-SGA, and GLIM identified 50.46%, 76.76%, and 68.81% as positive, respectively. Bayesian LCM analysis revealed that PG-SGA had the highest sensitivity (0.96) for malnutrition assessment, followed by GLIM criteria (0.78) and NRS-2002 (0.65). Malnutrition or being at risk of malnutrition were identified as independent prognostic factors for OS. Use any of these tools improved survival prediction in TNM staging system.

CONCLUSION

PG-SGA is the most reliable tool for diagnosing malnutrition in GC patients, whereas NRS-2002 is suitable for nutritional screening in busy clinical practice. Given the lower sensitivity of NRS-2002, direct utilization of GLIM for nutritional assessment may be necessary. Each nutritional tool should be associated with a specific course of action, although further research is needed.

Reproducibility matters: intra- and inter-sample variation of the point-of-care circulating cathodic antigen test in two Schistosoma mansoni endemic areas in Uganda

Over 240 million people are infected with schistosomiasis. Detecting Schistosoma mansoni eggs in stool using Kato-Katz thick smears (Kato-Katzs) is highly specific but lacks sensitivity. The urine-based point-of-care circulating cathodic antigen test (POC-CCA) has higher sensitivity, but issues include specificity, discrepancy between batches and interpretation of trace results. A semi-quantitative G-score and latent class analyses making no assumptions about trace readings have helped address some of these issues. However, intra-sample and inter-sample variation remains unknown for POC-CCAs. We collected 3 days of stool and urine from 349 and 621 participants, from high- and moderate-endemicity areas, respectively. We performed duplicate Kato-Katzs and one POC-CCA per sample. In the high-endemicity community, we also performed three POC-CCA technical replicates on one urine sample per participant. Latent class analysis was performed to estimate the relative contribution of intra- (test technical reproducibility) and inter-sample (day-to-day) variation on sensitivity and specificity. Within-sample variation for Kato-Katzs was higher than between-sample, with the opposite true for POC-CCAs. A POC-CCA G3 threshold most accurately assesses individual infections. However, to reach the WHO target product profile of the required 95% specificity for prevalence and monitoring and evaluation, a threshold of G4 is needed, but at the cost of reducing sensitivity. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.

Assessment of the accuracy of 11 different diagnostic tests for the detection of Schistosomiasis mansoni in individuals from a Brazilian area of low endemicity using latent class analysis

Background

Schistosomiasis is a parasitic disease associated with poverty. It is estimated that 7.1 million people are infected with Schistosoma mansoni in Latin America, with 95% of them living in Brazil. Accurate diagnosis and timely treatment are important measures to control and eliminate schistosomiasis, but diagnostic improvements are needed to detect infections, especially in areas of low endemicity.

Methodology

This research aimed to evaluate the performance of 11 diagnostic tests using latent class analysis (LCA). A cross-sectional survey was undertaken in a low endemicity area of the municipality of Malacacheta, Minas Gerais, Brazil. Feces, urine, and blood samples were collected from 400 residents older than 6 years of age, who had not been treated with praziquantel in the 12 months previous to the collection of their samples. The collected samples were examined using parasitological (Helm Test® kit Kato-Katz), nucleic acid amplification tests -NAATs (PCR, qPCR and LAMP on urine; PCR-ELISA, qPCR and LAMP on stool), and immunological (POC-CCA, the commercial anti-Schistosoma mansoni IgG ELISA kit from Euroimmun, and two in-house ELISA assays using either the recombinant antigen PPE or the synthetic peptide Smp150390.1) tests.

Results

The positivity rate of the 11 tests evaluated ranged from 5% (qPCR on urine) to 40.8% (commercial ELISA kit). The estimated prevalence of schistosomiasis was 12% (95% CI: 9-15%) according to the LCA. Among all tests assessed, the commercial ELISA kit had the highest estimated sensitivity (100%), while the Kato-Katz had the highest estimated specificity (99%). Based on the accuracy measures observed, we proposed three 2-step diagnostic approaches for the active search of infected people in endemic settings. The approaches proposed consist of combinations of commercial ELISA kit and NAATs tests performed on stool. All the approaches had higher sensitivity and specificity than the mean values observed for the 11 tests (70.4 and 89.5%, respectively).

Conclusion

We showed that it is possible to achieve high specificity and sensitivity rates with lower costs by combining serological and NAATs tests, which would assist in the decision-making process for appropriate allocation of public funding aiming to achieve the WHO target of eliminating schistosomiasis as a public health problem by 2030.

Modelling diagnostics for Echinococcus granulosus surveillance in sheep using Latent Class Analysis: Argentina as a case study

Echinococcus granulosus sensu lato is a globally prevalent zoonotic parasitic cestode leading to cystic echinococcosis (CE) in both humans and sheep with both medical and financial impacts, whose reduction requires the application of a One Health approach to its control. Regarding the animal health component of this approach, lack of accurate and practical diagnostics in livestock impedes the assessment of disease burden and the implementation and evaluation of control strategies. We use of a Bayesian Latent Class Analysis (LCA) model to estimate ovine CE prevalence in sheep samples from the Río Negro province of Argentina accounting for uncertainty in the diagnostics. We use model outputs to evaluate the performance of a novel recombinant B8/2 antigen B subunit (rEgAgB8/2) indirect enzyme-linked immunosorbent assay (ELISA) for detecting E. granulosus in sheep. Necropsy (as a partial gold standard), western blot (WB) and ELISA diagnostic data were collected from 79 sheep within two Río Negro slaughterhouses, and used to estimate individual infection status (assigned as a latent variable within the model). Using the model outputs, the performance of the novel ELISA at both individual and flock levels was evaluated, respectively, using a receiver operating characteristic (ROC) curve, and simulating a range of sample sizes and prevalence levels within hypothetical flocks. The estimated (mean) prevalence of ovine CE was 27.5% (95%Bayesian credible interval (95%BCI): 13.8%-58.9%) within the sample population. At the individual level, the ELISA had a mean sensitivity and specificity of 55% (95%BCI: 46%-68%) and 68% (95%BCI: 63%-92%), respectively, at an optimal optical density (OD) threshold of 0.378. At the flock level, the ELISA had an 80% probability of correctly classifying infection at an optimal cut-off threshold of 0.496. These results suggest that the novel ELISA could play a useful role as a flock-level diagnostic for CE surveillance in the region, supplementing surveillance activities in the human population and thus strengthening a One Health approach. Importantly, selection of ELISA cut-off threshold values must be tailored according to the epidemiological situation.