article: Intervention guidelines against Schistosoma mansoni are based on the Kato-Katz technique. However, Kato-Katz thick smears show low sensitivity, especially for light-intensity infections. The point-of-care circulating cathodic antigen (POC-CCA) is a promising rapid diagnostic test detecting antigen output of living worms in urine and results are reported as trace, 1+, 2+, and 3+. The use of POC-CCA for schistosomiasis mapping, control, and surveillance requires translation of the Kato-Katz prevalence thresholds into POC-CCA relative treatment cut-offs. Furthermore, the infection status of egg-negative but antigen-positive individuals and the intensity-dependent sensitivity of POC-CCA should be estimated to determine its suitability for verification of disease elimination efforts. We used data from settings in Africa and the Americas characterized by a wide range of S. mansoni endemicity. We estimated infection intensity-dependent sensitivity and specificity of each test at the unit of the individual, using a hierarchical Bayesian egg-count model that removes the need to define a ‘gold’ standard applied to data with multiple Kato-Katz thick smears and POC-CCA urine cassette tests. A simulation study was carried out based on the model estimates to assess the relation of the two diagnostic tests for different endemicity scenarios. POC-CCA showed high specificity (> 95%), and high sensitivity (> 95%) for moderate and heavy infection intensities, and moderate sensitivity (> 75%) for light infection intensities, and even for egg-negative but antigen-positive infections. A 10% duplicate slide Kato-Katz thick smear prevalence corresponded to a 15–40% prevalence of ≥ trace-positive POC-CCA, and 10–20% prevalence of ≥ 1+ POC-CCA. The prevalence of ≥ 2+ POC-CCA corresponded directly to single slide Kato-Katz prevalence for all prevalence levels. The moderate sensitivity of POC-CCA, even for very light S. mansoni infections where the sensitivity of Kato-Katz is very low, and the identified relationship between Kato-Katz and POC-CCA prevalence thresholds render the latter diagnostic tool useful for surveillance and initial estimation of elimination of S. mansoni. For prevalence below 10% based on a duplicate slide Kato-Katz thick smear, we suggest using POC-CCA including trace results to evaluate treatment needs and propose new intervention thresholds that need to be validated in different settings.
  Schistosomiasis is a neglected tropical disease (NTD) caused by parasitic flatworms of the genus Schistosoma that require freshwater snails as intermediate hosts to complete their life cycle [1]. Currently, around 250 million people are infected, primarily school-aged children in rural areas of sub-Saharan Africa, and, to a lesser extent in Southeast Asia, and the Americas, causing an estimated 2. 1 million disability-adjusted life years (DALYs) in 2016 [2,3]. There are six species infecting humans, of which Schistosoma haematobium, S. japonicum, and S. mansoni are the most common ones [1]. This study discusses the diagnosis of S. mansoni whose adult stage live in pairs within the mesenteric venules. Experiments in mice showed that female worms shed in the order of several hundred eggs daily with a large variability. Eggs are either trapped in the intestines and liver causing inflammatory reactions, or are excreted through feces continuing the life cycle [4]. Morbidity, among others, includes anemia, growth stunting, impaired cognition, increased susceptibility to other infections (e. g. , HIV), and severe pathologies of the liver and spleen [1,5–7]. The World Health Organization (WHO) has articulated a road-map for morbidity control, and elimination of the disease in suitable settings, by 2025 based on preventive chemotherapy using praziquantel administered to school-aged children and other high-risk communities, control of intermediate host snails, and behavioral and environmental changes [8,9]. To achieve these goals, intervention guidelines were set that define the communities requiring preventive chemotherapy and treatment frequency. Enacting these guidelines requires estimates of the disease prevalence, which are obtained from survey data. Transmission levels may vary over short geographic scales (2–5 km), and thus, having the ability to sample large numbers of communities with rapid, low cost, and sensitive tests are critical for efficient and effective disease control [10–12]. Infections with S. mansoni can be diagnosed using various techniques to detect eggs in stool. The most widely used method is the Kato-Katz technique based on a thick smear, usually with a volume equivalent to 41. 7 mg [13]. Of note, the Kato-Katz technique has been used to define intervention thresholds for preventive chemotherapy [14]. While fecal egg detection techniques have generally high specificity, they suffer from low sensitivity, especially for light-intensity infections, which lead to underestimation of community prevalence and burden [15,16]. To reduce the diagnostic error, repeated sampling of stool and preparation of multiple Kato-Katz thick smears from a single stool specimen is recommended, which is impractical and expensive for disease control purposes [17]. Furthermore, Kato-Katz detects only infections with mature, egg-shedding worms. To overcome these shortcomings, novel techniques that are not based on egg detection are required. A promising candidate is a test that detects a specific antigen in urine; the point-of-care circulating cathodic antigen (POC-CCA) [18]. Diagnosis takes about 20 min and the outcome is reported semi-quantitatively; namely, trace, 1+, 2+, and 3+, although interpretation may depend on the laboratory technician. Systematic reviews estimate the sensitivity to be around 90%. POC-CCA classifies individuals as positive that were classified as negative by Kato-Katz due to its low sensitivity for light infection intensities. Hence, the specificity of POC-CCA is underestimated when Kato-Katz is considered as diagnostic ‘gold’ standard [19,20]. Colley et al. performed regression analysis to estimate the relation between POC-CCA and single Kato-Katz thick smears and indicated the need for further investigation to determine how it depends on different sampling schemes and levels of endemicity [21]. Converting Kato-Katz prevalence thresholds from existing treatment guidelines into POC-CCA analogues requires information on the variation of the sensitivity of POC-CCA with infection intensity. Moreover, the prevalence of egg-negative but antigen- or worm-positive infections and its influence on the prevalence measured by POC-CCA in comparison with Kato-Katz testing has to be evaluated. In this study, we addressed the aforementioned issues using pairs of data with simultaneous testing of fecal samples by Kato-Katz and urine samples by POC-CCA from various settings in Africa and the Americas, characterized by a wide range of endemicity levels. We developed a model which infers on the infection intensity-dependent sensitivity profile of POC-CCA for semi-quantitative test results without using an artificial ‘gold’ standard. Additionally, we estimated the specificity of POC-CCA and the prevalence of egg-negative/antigen-positive infections. Model outputs were employed in a simulation study to obtain insights on the relation between measured Kato-Katz and POC-CCA prevalence, assuming a range of scenarios with various infection intensities and prevalence of egg-negative infections. Our findings translate Kato-Katz based S. mansoni prevalence thresholds put forth in the current WHO intervention guidelines into POC-CCA prevalence and enable the latter diagnostic approach for mapping, disease control, and surveillance.
  The data included in this study were published elsewhere or are currently in the process of being published [21–31]. Hence, ethics approval, written informed consent procedures, and treatment of infected individuals are given in the respective studies where the original data were or are being published. We analyzed a suite of 30 datasets with simultaneous Kato-Katz and POC-CCA results available at individual level. A description of the data related to Kato-Katz and POC-CCA results is given in Tables 1 and 2, respectively. The data were grouped in four categories depending on their characteristics. In particular, a number of datasets (group 1) from Cameroon, Côte d’Ivoire, Ethiopia, Kenya, and Uganda have at least duplicate Kato-Katz readings on two different days and at least one POC-CCA urine cassette test result. These datasets were used in the most complex egg-count model to estimate infection intensity-dependent sensitivity of both diagnostic methods and can be found in S2 Table. Data from Ecuador and Ethiopia with binary Kato-Katz results (i. e. , egg-positive or egg-negative; group 2) were collected at locations known to be non-endemic and therefore include information about the specificity of POC-CCA. Datasets from Burundi, Côte d’Ivoire, Rwanda, and South Sudan, with only duplicate Kato-Katz slides from one stool sample (group 3) did not provide information on the day-to-day variation. Datasets from Egypt (group 4) with single Kato-Katz readings of binary outcome were collected from locations with very low transmission. Data from groups 3 and 4 were used in the simulation study. The Kato-Katz results were available either as binary or egg-count measurements. Hence, we developed separate but interlinked Bayesian hierarchical models for each type of data to include all available information in the evaluation of POC-CCA. Using the parameter estimates described in our statistical model, we simulated single and duplicate slide Kato-Katz thick smears and POC-CCA prevalences under 84 different scenarios. The simulations were carried out with a large number of individuals per scenario to avoid variations due to sampling. We assumed a wide range of egg-positive infections (i. e. , 5%, 10%, 20%, 30%, 50%, and 70%) to mimic different endemicity scenarios. Prevalence of egg-negative infections was varied independently from the egg-positive prevalence and assumed to be 5%, 10%, 20%, and 30%. Mean infection intensity of an egg-positive infected individual was set to 50 EPG, 100 EPG, 200 EPG, and 400 EPG.
  Our model estimates the sensitivity and specificity in relation to the ‘true’ prevalence of infection in the population. This avoids the use of a ‘gold’ standard, which does not exist. Posterior estimates of parameters that influence the sensitivity and specificity can be found in Table A in S1 Table. Based on these parameters, Fig 1 shows the infection-dependent sensitivity of POC-CCA. All three binary proxies of POC-CCA indicate a very high sensitivity for moderate and heavy infections (≥ 100 EPG). The sensitivity for light infections differ between proxies: while including trace results as positives enables detection of very light infections, considering 2+ and 3+ results as positives leads to missing of many infected individuals. The uncertainty in the estimated sensitivity is largest in the proxy considering trace results as negative (1+/2+/3+). Table 3 shows the specificity and sensitivity estimates for egg-negative infections. POC-CCA revealed very high sensitivity even for light infection intensities when trace results were interpreted as positive. Furthermore, sensitivity was above 60% for non-egg-shedding but antigen-positive individuals that apparently harbor worms. The proxy 2+ and 3+ revealed low sensitivity for egg-negative/antigen-positive individuals. Specificity is over 95% irrespective of the chosen proxy. In Fig 2 the infection intensity-dependent sensitivity of Kato-Katz for one to two slides from one to three samples are shown. Single slide Kato-Katz testing is equivalent to the 2+/3+ POC-CCA proxy with a sensitivity of 60% at 50 EPG, and 70% at 100 EPG. A single slide on two different days clearly outperforms two slides from the same sample. Taking two slides from three different samples leads essentially to perfect sensitivity for infection intensities above 50 EPG but even this extensive sampling scheme does not allow reliable detection of very light infections below 10 EPG. Table 4 shows estimates of egg-positive and egg-negative infection prevalence, mean infection intensity of an egg-positive infected individual, and mean egg count in the population. We found a wide variation in the estimates between datasets with egg-positive infection prevalence ranging from 6% to 91%, and egg-negative prevalence varying from 3% to 45%. The mean intensity of an infected individual ranged from 80 EPG to more than 500 EPG and the mean egg count in the population ranged from around 4 EPG to more than 300 EPG. There was no simple relation between the prevalence of egg-negative and egg-positive infections, the infection intensity of the infected individuals, and the total infection intensity in the population (Fig 3). However, there was evidence of a positive relation between the prevalence of egg-positive and egg-negative infections at low prevalence. Fig 4 displays the relation between the observed prevalence measured with a single Kato-Katz thick smear and POC-CCA. We observed a clear relation for each of the three proxies of POC-CCA, but there is still insufficient data to give a clear indication of the variability. The results of the simulation study (Fig 5) showed the estimated relation between single and duplicate slide Kato-Katz prevalence and POC-CCA prevalence for varying egg-positive prevalence for the 16 combinations with the four infection intensity scenarios on the x-axis and the four scenarios for the prevalence of egg-negative infections on the y-axis. For trace considered positive, the relation between POC-CCA and Kato-Katz prevalence were dependent on infection intensity and prevalence of egg-negative infections. When Kato-Katz prevalence is zero, the POC-CCA prevalence is determined by the prevalence of egg-negative infections. For low mean infection intensities, there are primarily light infections for which POC-CCA has a higher sensitivity, and hence, the slope of the relation is small. When only 2+ and 3+ readings are considered positive, the relation neither depends on the infection intensity nor on the prevalence of egg-negative infections. When trace is considered negative, there is lower variation in the Kato-Katz/POC-CCA relation. These patterns hold for both single and duplicate slide Kato-Katz with a change in the slope of the relation. Figs 6 and 7 show a scatter plot of prevalence measured by single and duplicate slide Kato-Katz, respectively, and POC-CCA for all simulation scenarios to highlight the variability present in the Kato-Katz/POC-CCA relation for each proxy. Both the prevalence of egg-negative infections and mean infection intensity are, in practice, unknown when only POC-CCA diagnostics is applied. There is large uncertainty in the estimates for the trace-positive proxy due to the dependence on unknown parameters. For the trace-negative proxy there is weaker but still considerable uncertainty. The 2+ and 3+ proxy shows close to perfect accordance with Kato-Katz and only low uncertainty. Based on the simulation scenarios, Table 5 translates single and duplicate slide Kato-Katz prevalence thresholds into POC-CCA equivalents. For trace considered positive, the variability is large because of the previously mentioned unknown number of egg-negative/antigen-positive individuals. Single slide Kato-Katz and POC-CCA prevalence are identical when 2+ and 3+ proxy is considered. Due to the uncertainty in the Kato-Katz/POC-CCA relation when trace-positive or trace-negative proxies are used, the Kato-Katz prevalence corresponds to a range of POC-CCA prevalence values which are generally higher than the Kato-Katz one. A single slide Kato-Katz prevalence of 10% corresponds to 20–40% POC-CCA prevalence when traces are considered positive and to 15–25% when traces are considered negative. For a duplicate slide Kato-Katz prevalence of 10% the equivalent ranges are 15–40% when traces are considered positive and 10–20% when traces are considered negative. When avoiding under-treatment is the priority, conservative thresholds could be defined at the lower end of each range. However, the lower end of the range corresponds to a high mean infection-intensity of an infected individual which is only a realistic scenario in a high prevalence setting. For lower prevalence, a lower mean infection intensity is a more realistic threshold. Hence, we suggest a threshold of 60% POC-CCA to be equivalent to 50% duplicate Kato-Katz, and 30% POC-CCA to be equivalent to 10% Kato-Katz to define treatment categories. Table 6 shows the WHO guidelines for S. mansoni from 2013 [8]. In addition to the threshold given for parasitological methods we added the suggested thresholds from Table 5.
  Kato-Katz prevalence can be translated to a range of POC-CCA prevalence. Choosing a single equivalent threshold can be justified for simplicity and applicability but leads to misclassification. A conservative threshold could be chosen at the lower end of the range, which ensures that there is no under-treatment but doing so would also underestimate the true prevalence of disease. Instead, we recommend a more balanced approach suggesting a threshold at the lower end of the range for high prevalence, and a more central value for lower prevalence to reflect the accompanying decrease in mean infection-intensity of the infected population. Therefore, the 10% and 50% duplicate slide Kato-Katz thresholds are to be translated to 30% and 60% POC-CCA, respectively, when traces are considered positive. Additionally, new treatment categories for scenarios close to elimination can be defined for POC-CCA at 10% and 20% roughly corresponding to 1% and 5% Kato-Katz, respectively. For a more accurate translation, which is especially useful when integrating studies based on Kato-Katz and POC-CCA diagnostics into a single analysis, we recommend recording fully semi-quantitative results and using the POC-CCA ≥ 2+ prevalence as equivalent to single slide Kato-Katz. In suspected low-endemicity settings, we recommend replacing Kato-Katz irrespective of sampling effort with the trace positive proxy of POC-CCA. This is solely based on the diagnostic accuracy determined in this study, while cost-effectiveness shall be evaluated taking into account the specific situation. The test’s sensitivity to infections with none or only erratic egg shedding, which are difficult to detect even by Kato-Katz repeated on multiple days, make it useful for surveillance in settings approaching elimination and for diagnostics on the individual level. The presented evidence suggests that the egg-negative but antigen-positive infections are real infections, and hence, it is conceivable that the current Kato-Katz based estimates for prevalence and morbidity underestimate the reality. Better tools and further studies are needed to determine worm burdens and morbidity associated with egg-negative infections.
summary: The World Health Organization (WHO) has defined goals for schistosomiasis morbidity control to be reached by 2025 that are based on preventive chemotherapy. Intervention thresholds for Schistosoma mansoni are currently defined for prevalence measured by stool microscopy using the Kato-Katz technique. However, the Kato-Katz technique shows low sensitivity, particularly for the detection of light-intensity infections. Replacing it with the semi-quantitative point-of-care circulating cathodic antigen (POC-CCA) urine cassette test requires translation of the thresholds and precise characterization of the diagnostic sensitivity and specificity. In this study, we applied a novel egg-count model to a suite of data obtained from different settings in Africa and the Americas with diverse endemicity levels. We used a simulation study to infer on the relation between Kato-Katz and POC-CCA prevalence. Based on our study, we were able to provide recommendations for POC-CCA thresholds taking into account semi-quantitative results of the test. We found that a S. mansoni prevalence of 10% based on duplicate slide Kato-Katz thick smear is equivalent to 15–40% POC-CCA prevalence when trace results are considered positive and to 10–20% POC-CCA prevalence when trace results are considered negative. Our results have important bearings for mapping, control, surveillance, and verification of elimination of intestinal schistosomiasis.
keywords: schistosoma
  invertebrates
  schistosoma mansoni
  medicine and health sciences
  body fluids
  helminths
  geographical locations
  animals
  health care
  simulation and modeling
  urine
  pharmaceutics
  africa
  morbidity
  research and analysis methods
  cameroon
  people and places
  chemotherapy
  eukaryota
  diagnostic medicine
  health statistics
  asia
  anatomy
  egypt
  physiology
  biology and life sciences
  drug therapy
  organisms
title: Translating preventive chemotherapy prevalence thresholds for Schistosoma mansoni from the Kato-Katz technique into the point-of-care circulating cathodic antigen diagnostic test