To work towards reaching the WHO goal of eliminating soil-transmitted helminth (STH) infections as a public health problem, the total number of children receiving anthelmintic drugs has strongly increased over the past few years. However, as drug pressure levels rise, the development of anthelmintic drug resistance (AR) is more and more likely to appear. Currently, any global surveillance system to monitor drug efficacy and the emergence of possible AR is lacking. Consequently, it remains unclear to what extent the efficacy of drugs may have dropped and whether AR is already present. The overall aim of this study is to recommend the best diagnostic methods to monitor drug efficacy and molecular markers to assess the emergence of AR in STH control programs. A series of drug efficacy trials will be performed in four STH endemic countries with varying drug pressure (Ethiopia and Brazil: low drug pressure, Lao PDR: moderate drug pressure and Tanzania: high drug pressure). These trials are designed to assess the efficacy of a single oral dose of 400 mg albendazole (ALB) against STH infections in school-aged children (SAC) by microscopic (duplicate Kato-Katz thick smear, Mini-FLOTAC and FECPAKG2) and molecular stool-based diagnostic methods (quantitative PCR (qPCR) ). Data will be collected on the cost of the materials used, as well as the time required to prepare and examine stool samples for the different diagnostic methods. Following qPCR, DNA samples will also be submitted for pyrosequencing to assess the presence and prevalence of single nucleotide polymorphisms (SNPs) in the β-tubulin gene. These SNPs are known to be linked to AR in animal STHs. The results obtained by these trials will provide robust evidence regarding the cost-efficiency and diagnostic performance of the different stool-based diagnostic methods for the assessment of drug efficacy in control programs. The assessment of associations between the frequency of SNPs in the β-tubulin gene and the history of drug pressure and drug efficacy will allow the validation of these SNPs as a marker for AR in human STHs. The trial was retrospectively registered the 7th of March 2018 on Clinicaltrials. gov (ID: NCT03465488).
Currently, the reduction in number of eggs excreted in stool after drug administration (egg reduction rate, ERR) is the recommended method for monitoring the efficacy of anthelmintic drugs against STHs [27]. In contrast to other available assays, it allows for the assessment of the efficacy of any drug against all STHs [28–31]. Today, a variety of egg counting methods have been recommended by WHO for the assessment of drug efficacy [27], of which Kato-Katz thick smear is the most commonly applied. Egg counting still requires a minimum amount of laboratory equipment and experienced laboratory technicians to ensure quality of the data obtained [22,24,32]. Furthermore, it is essential that samples are analysed quickly after collection to ensure the visualisation of hookworm eggs and that results are adequately analysed, applying the most appropriate summary statistics [15,27] and are then reported to the responsible authorities. There is often limited availability of laboratory capacity and a poor reporting of the results obtained. This prompts the need for an improved diagnostic method that enables (i) egg counts to be performed without the use of a microscope, (ii) automated egg counting, and (iii) submission of results from remote locations via the internet for quality control of egg counts, analysis and reporting. Such a method would eliminate the need for a microscope or highly skilled technicians/clinicians or administrators while providing and centralizing drug efficacy results. A method that largely meets this target product profile is the FECPAKG2 platform. Recently, it has been launched as a complete remote-location diagnostic method for sheep/cattle farmers and their veterinarians to assess the intensity of helminth infections and efficacy of drugs [33]. The platform accumulates helminth eggs into one microscopic view after which digital images are taken [34]. Images are stored by the associated software and can be uploaded to a remote server when an Internet connection is available. Later, a web-based laboratory technician can count the eggs visible in the images, after which the results are returned to the user by e-mail. The FECPAKG2 platform thus potentially eliminates the need for skilled technicians on-site. The online software allows easy access for quality control of egg counting and the production of standardized analysis and reports. More importantly, it opens the door to automated egg counting by egg recognition software [35]. Recently, Ayana et al. (in press) [36] modified and optimized a FECPAKG2 protocol for the detection and quantification of human STH eggs in stool. However, it remains unclear whether it provides equivalent ERR results to those obtained by diagnostic methods recommended by WHO, and whether it would result in more efficient use of financial and technical resources under field conditions. From a research perspective, there is a growing interest to apply quantitative polymerase chain reaction (qPCR) for the assessment of drug efficacy. In contrast to the egg counting methods, qPCR can differentiate the different hookworm species, and thus allow evaluation of BZ efficacy against the different hookworm species [37,38]. This is of particular interest given that there could be differential susceptibility towards BZ drugs among hookworm species, and that there is increasing evidence of zoonotic transmission of Ancylostoma ceylanicum between dogs and humans [39–42]. Although studies have linked amount of DNA with egg output [37,43], to date, qPCR has not yet been applied for the assessment of drug efficacy. Early detection of BZ resistance is essential to anticipate the efficacy of drugs in STH control programs, as it is more difficult to mitigate the spread of AR when the initial frequency is already high [44]. However, both in vivo (e. g. ERR) and in vitro assays (e. g. egg hatch assay) lack the sensitivity to detect the emergence of AR at an early stage. For example, in animals ERR was only able to detect AR when the proportion of resistant STHs exceeded 25% [45], a proportion that may impede mitigating the spread of AR. A more sensitive alternative is a molecular test based on resistance-associated mutations in targeted genes. Due to the unfortunate and costly experiences of AR in veterinary medicine, BZ resistance has been researched in detail in animal STHs, providing strong evidence of molecular markers associated with BZ resistance. An overview of the markers for BZ resistance in animal STH is provided by Von Samson-Himmelstjerna et al. , [46]. Generally, BZ resistance in animal STHs is caused by single nucleotide polymorphisms (SNPs) in the gene encoding β-tubulin at codons 167 (TTC to TAC), 198 (GAA to GCA) or 200 (TTC to TAC), but the relative association of these SNPs with BZ resistance varies considerably across animal STH species [47–49]. Various methodologies to detect and quantify these SNPs in animal STH have been developed through an international Consortium for Anthelmintic Resistance SNPs (CARS), [50] of which some have now also been developed and applied for human STHs [29,30,51–53]. The few studies assessing SNPs in human STHs suggest that (i) polymorphisms are predominantly found in codon 200, and (ii) that resistance-associated mutations increased after drug administration (seen for T. trichiura), (iii) but that there was no clear association with reduced drug efficacy. However, the results should be interpreted with caution. First, they were based on a small number of participants (ranging from 3 to 31 participants) across a limited number of geographical areas (Kenya, Haiti, Panama and Tanzania). Second, STH data were collected applying a variety of study methodologies. For example, the samples originated from a wide range spectrum of the population (pre-SAC, SAC and adults) and were examined applying different egg counting methods (Kato-Katz thick smear, McMaster egg counting method and FLOTAC), which makes comparison across studies difficult. Most technologies to assess SNPs linked to BZ resistance are only available in well-equipped laboratories. Recently, Rashwan et al. , [54] published a loop-mediated isothermal amplification (LAMP) assay for the assessment of β-tubulin polymorphisms in human STHs. Due to its simplicity, ruggedness and low cost, LAMP could provide major advantages in detecting AR on-site. However, the method needs to be further validated on field samples. Another strategy to further reduce the operational costs is to apply a pooled examination strategy. Examination of pooled stool has already proved to allow for reduction in technical and financial resources for other egg counting methods such as Kato-Katz thick smear [55]. The overall aim of this study is to recommend the best diagnostic methods to monitor drug efficacy and status of AR in STH programs. These will then be applied in work package 2 (the establishment of a surveillance system to monitor the global patterns of drug efficacy and emergence of AR in STH programs). The specific objectives are to: Assess equivalence of ERRs measured by Kato-Katz thick smear, Mini-FLOTAC and FECPAKG2 Assess the diagnostic performance of Kato-Katz thick smear, Mini-FLOTAC, FECPAKG2 and qPCR Assess the costs linked with assessing drug efficacy by Kato-Katz thick smear, Mini-FLOTAC and FECPAKG2 Provide proof-of-principle for qPCR to assess intensity of infection and drug efficacy Assess associations between frequency of SNPs linked to BZ resistance measured by pyrosequencing and history of drug pressure and drug efficacy Compare pyrosequencing and LAMP for the assessment of SNPs linked to BZ resistance Assess pooling samples as a cost-saving strategy to determine infection intensity (qPCR) and frequency of SNPs linked to BZ resistance (pyrosequencing and LAMP) The Starworms protocol has been reviewed and approved by the Institutional Review Board (IRB) of the faculty of medicine of Ghent University, Belgium (Ref. No B670201627755). The trial protocol was subsequently also reviewed and approved by the IRBs associated with each trial site (Ethical Review Board of Jimma University, Jimma, Ethiopia: RPGC/547/2016; National Ethics Committee for Health Research (NECHR), Vientiane, Lao PDR: 018/NECHR; Zanzibar Health Research Council, United Republic of Tanzania: ZAMREC/0002/February/2015 and the Institutional Review Board from Centro de Pesquisas René Rachou, Belo Horizonte, Brazil: 2. 037. 205). Parent (s) /guardians of participants will sign an informed consent document indicating that they understand the purpose of and procedures required for the study and that they are willing to have their child participate in the study. If the child is ≥5 years, he/she has to orally assent in order to participate in the study. Participants of ≥12 years of age are only included if they sign an informed consent document indicating that they understand the purpose of the study and procedures required for the study and are willing to participate in the study. A series of drug efficacy trials will be performed in four STH endemic countries (Brazil, Ethiopia, Lao PDR and Tanzania). These trials will be designed to assess the efficacy of a single oral dose of 400 mg ALB against STH infections in SAC by a variety of stool-based diagnostic methods. At the start of each trial, schools will be visited by the local principal investigator (PI) and a team of field officers, who will explain the planned trial and sampling method to the parents and teachers and the children. At baseline, SAC will be asked to provide a fresh stool sample. All children that meet all inclusion criteria and none of the exclusion criteria (see Table 1) will be enrolled in the study. They will be treated with a single oral dose of 400 mg ALB under supervision. The ALB to be used in the different studies is manufactured by GlaxoSmithKline and donated to WHO and originates from the same production batch (Batch Nr: 335726). All collected stool samples will be processed to determine the fecal egg counts (FECs; expressed in eggs per gram of stool (EPG) ) for each STH using Kato-Katz thick smear (single and duplicate), Mini-FLOTAC and FECPAKG2. During baseline evaluation, only stool samples found to contain at least 13 eggs on duplicate Kato-Katz or at least 15 eggs on Mini-FLOTAC for at least one of the three STHs will be preserved for further molecular analysis. Fourteen to 21 days after drug administration, a second stool sample will be collected from all the children that were excreting eggs of any STH at baseline based on Kato-Katz thick smear and Mini-FLOTAC. Stool samples will be examined by Kato-Katz thick smear (single and duplicate), Mini-FLOTAC and FECPAKG2. All follow-up samples will be preserved for further molecular analysis. To gain insights into the operational costs for assessing drug efficacy, the time to process stool with Kato-Katz thick smear, Mini-FLOTAC and FECPAKG2, and the time needed to enter data and to draft reports will be assessed. The different steps of the trials are schematized in Fig 1. The study will focus on SAC (age 5–14) since they are the major target of PC programs targeting STH, and they usually represent the group with highest worm burdens for A. lumbricoides and T. trichiura [56]. This study will be conducted in Ethiopia, Tanzania, Lao PDR and Brazil. The selection of these sites is based on their experience in assessing drug efficacy [13,15], evaluating the performance of diagnostic methods [57–59] and the availability of well-equipped diagnostic facilities and skilled personnel, and PC history (Table 2). A sample size was calculated to test the alternative hypothesis that FECPAKG2, Mini-FLOTAC and single Kato-Katz thick smear provide equivalent drug efficacy results measured by ERRs compared to a duplicate Kato-Katz thick smear. Given the differences in drug efficacy of ALB across the STH species [15,21] (Ascaris: ~99%, hookworms: ~96%, Trichuris: ~65%), a level of equivalence that is acceptable for Trichuris may not be acceptable for Ascaris. Therefore, a species-specific level of equivalence was used. For Ascaris the level of equivalence was set at 2. 5-point percentage, for hookworms and Trichuris the level of equivalence was set at 5. 0 and 10 point percentage, respectively. Both type I and II errors were set at 0. 05. To calculate the corresponding sample size for each of the STH species, we performed a simulation study. This simulation study considered (i) variation in ERR and baseline FECs across and within STH species, (ii) variation in FECs introduced by the egg counting process, (iii) the paired ERR results across egg count methods, and (iv) a post-hoc correction for a pair-wise comparison. Based on the simulation, at least 110,100 and 12 complete cases are required for Trichuris, hookworm and Ascaris, respectively. A detailed description of the sample size calculation is available in the supplementary information (S1 Info). We will provide participants with a container for the collection of stool samples. The samples will be collected and stored in cooler boxes with ice-packs, which will then be transported to the laboratory at the respective study site for further analysis. Upon arrival in the laboratory, samples will be thoroughly homogenized using a wooden spatula to obtain a more homogeneous distribution of STH eggs in the stool [60]. A detailed standard operating procedure (SOP) on sample homogenisation is available in the supplementary information (S2 Info). To make objective estimates of the costs associated with the different diagnostic methods, we will collect data on the cost of the materials used as well as the time required to prepare and examine stool samples for the different stool-based diagnostic methods. Detailed pricing information for the list of materials needed to perform Kato-Katz thick smear and Mini-FLOTAC will be obtained from the local PI. The costs for the materials needed for the FECPAKG2 method will be obtained from the manufacturer (Techion Group Ltd.) and is expected to be the same for all four study sites. A list of materials included in the cost calculation for the Kato-Katz thick smear and Mini-FLOTAC method is provided in S11 Info. The costs associated with molecular analysis of the samples will include the cost for preservation and shipment of the stool samples as well as the laboratory materials used to perform DNA extractions and qPCR. Timers will be provided to each laboratory technician to measure the time needed to perform the different steps of each of the diagnostic methods. For all egg counting methods, the time taken to complete each step will be measured. In addition, the time needed for data entry and drafting a report will be recorded. The protocols of the egg counting methods include more details on the different timing steps (S3–S5, S8 and S10 Info). All data collected during the studies will be recorded in specifically designed record forms (S12 Info). The original results written down on the paper documents will be scanned and stored digitally. This data will later be entered into customized Excel-files by two separate individuals (S13–S15 Info). After completion of the data entry, the files of both data entry clerks will be compared for discrepancies (S16 Info). Potential mismatches will be highlighted and the true values verified using the scanned original record form. The PIs from each site are responsible for acquiring ethical approval by their local Institutional Review Board (IRB) and conducting the trial procedures as described in the original study protocol and study SOPs. The studies in the different countries will be coordinated by the project PI and the Starworms Coordinating Team at Ghent University. One week prior to the start of each study, a member of the Starworms Coordinating Team will visit the study site. Local team members will be informed on the study design, familiarised with the different study documents and receive both theoretical and practical training on how to perform different egg counting methods according to the Starworms SOPs. The Starworms staff member will remain on-site for at least 7 days after the start of the trial to ensure SOP adherence and to solve any issues that might arise. After data collection and quality control, all data will be combined in a final, protected dataset for statistical analysis. After finishing work package 1, this dataset will be made available on the Starworms website (www. starworms. org). All statistical analysis will be performed in R (R Development Core Team, 2016). We will evaluate both the prevalence and intensity of each different STH species in each of the four different study sites. The percentage of individuals included in the different classes of infection intensity will be reported in order to assess the efficacy of the PC intervention conducted until then in eliminating STH infection of moderate and heavy intensity. We will report the efficacy of a single oral dose of 400 mg ALB separately for A. lumbricoides, T. trichiura and hookworms, and for each FEC method by means of ERR, using the formula below: ERR=100%× (arithmeticmean (FECatbaseline) −arithmeticmean (FECatfollow-up) ) / (arithmeticmean (FECatbaseline) ) A bootstrap analysis will be used to determine the corresponding 95% confidence intervals (95% CI) for each egg counting method and for the pair-wise differences in ERR across diagnostic methods. A permutation test will be used to assess the equivalence in ERR between a duplicate Kato-Katz thick smear, and a single Kato-Katz thick smear, Mini-FLOTAC and FECPAKG2. Tukey’s method will be applied for multiple comparison between methods. In addition, the agreement between a duplicate Kato-Katz thick smear and the other egg counting methods in the assignment of drug efficacy into ‘satisfactory’, ‘doubtful’ and ‘reduced’ will be evaluated by Fleiss’ kappa statistic (κFleiss). This classification of the drug efficacy will be based on the criteria recently proposed by the WHO (Table 4) [27]. The value of this statistic indicates a slight (κFleiss <0. 2), fair (0. 2 ≤ κFleiss <0. 4), moderate (0. 4 ≤ κFleiss <0. 6), substantial (0. 6 ≤ κFleiss <0. 8) and an almost perfect agreement (κFleiss ≥ 0. 8). For each diagnostic method, the sensitivity will be calculated using the combined results of the four methods (duplicate Kato-Katz thick smear, Mini-FLOTAC, FECPAKG2 and qPCR) as the diagnostic ‘gold’ standard. This means that a sample is considered positive if it tested positive on at least one of the four methods. The species specificity of all methods will be set at 100%, as indicated by the morphology of the eggs or by the species-specific primer sets used in qPCR. The corresponding 95% CI for sensitivity will be calculated separately for each diagnostic method. Differences in sensitivity between methods will be assessed by a permutation test (10,000 iterations). Tukey’s method will be applied for pair-wise comparisons between the methods. The impact of infection intensity on the sensitivity within each method will be explored by a logistic regression model, which will be fitted for each of the methods with their test result (positive/negative) as the outcome and the natural log transformed mean FEC across the three methods as covariate. The predictive power of the final models will be evaluated by the proportion of the observed outcome that was correctly predicted by the model. To this end, an individual probability >0. 5 will be set as a positive test result, and negative if different. Finally, the sensitivity for each of the pre-defined values of FEC will be calculated based on these models. For egg counting methods, the agreement in egg counts will be evaluated by permutation tests (10,000 iterations) based on (i) Pearson’s correlation coefficient and (ii) the differences in FECs. Tukey’s method will be applied for pair-wise comparisons within each STH species. For qPCR, the agreement in GE numbers and FECs obtained by duplicate Kato-Katz thick smear will be evaluated by permutation tests (10,000 iterations) based on Pearson’s correlation coefficient. Samples containing helminth eggs will be classified into low, moderate, and heavy infection intensity according to FECs obtained by duplicate Kato-Katz and following the thresholds proposed by WHO; for A. lumbricoides these are 1–4,999 EPG, 5,000–49,999 EPG, and >49,999 EPG; for T. trichiura these are 1–999 EPG, 1000–9,999 EPG, and >9,999 EPG; and for hookworm these are 1–1,999 EPG, 2,000–3,999 EPG and >3,999 EPG (WHO, 1998). For each of the other diagnostic methods, a receiver operating characteristic analysis will be performed to determine the corresponding FECs / GE numbers that allow classification of the infections into low, moderate and heavy using duplicate Kato-Katz thick smear as a reference. Finally, the proportion samples correctly classified as having a low, moderately and heavy infection intensity will be assessed separately for single Kato-Katz thick smear, Mini-FLOTAC, FECPAKG2 and qPCR. The mean time to process and examine one stool sample will be calculated for each separate egg counting method. We will also calculate the mean time needed to enter the demographic data and test results of a single subject, and the time to analyze and report the data. To reach an estimation of the total cost associated per sample, we will combine these data with the estimation of the costs of the raw materials and labour time needed to analyze a sample by each of the different methods. To calculate the costs for analysing samples a fixed rate will be used. Finally, a one-way sensitivity analysis will be performed to assess the impact of each parameter on the total cost for each diagnostic method separately. The efficacy of a single oral dose of 400 mg ALB will be reported separately for A. lumbricoides, T. trichiura and hookworms by means of genome equivalent reduction rate (GERR), using the formula below: GERR = 100% x (arithmetic mean (GE at baseline) –arithmetic mean (GE at follow-up) ) / (arithmetic mean (GE at baseline) ). The corresponding 95% CI for GERR will be determined by bootstrap analysis (10,000 iterations). A permutation test will be used to assess the equivalence in drug efficacy between a duplicate Kato-Katz thick smear by means of ERR and qPCR by means of GERR for each of the STH species separately. The same level of equivalence will be applied as described in section 4. 8. 1. In addition, the agreement between a duplicate Kato-Katz thick smear and qPCR in the assignment of drug efficacy into ‘satisfactory’, ‘doubtful’ and ‘reduced’ will be evaluated by κFleiss statistic. To assess the association between mutant SNPs linked to BZ resistance and history of drug pressure, a permutation test will be applied to evaluate differences in frequency of mutant SNPs linked to BZ in the baseline samples across the study sites. Tukey’s method will be applied for pair-wise comparisons between the study sites. To assess the association between mutant SNPs linked to BZ resistance and drug efficacy, a permutation test will be applied to evaluate any difference in frequency of mutant SNPs linked to BZ across the four levels of individual response to ALB (Table 3). Tukey’s method will be applied for pair-wise comparisons between the four levels of individual response. The sensitivity of the LAMP method to detect mutant SNPs linked to BZ resistance will be evaluated using the pyrosequencing method as the gold standard. The impact of SNP frequency on the sensitivity of LAMP will be explored by a logistic regression model with the LAMP result as outcome (negative/positive) and the frequency of SNPs linked to BZ resistance as covariate. The predictive power of the final models will be evaluated by the proportion of the observed outcome that was correctly predicted by the model. To this end, an individual probability >0. 5 will be set as a positive test result, and negative in all other cases. The sensitivity for each of the pre-defined values of FEC will be calculated based on these models. Finally, the κ-statistic will be determined to assess the agreement in the LAMP test result across the different study sites, Canada (McGill University), Ethiopia (Jimma University) and Tanzania (Public Health Laboratory—Ivo de Carneri) ). The value of this statistic indicates a slight (κ <0. 2), fair (0. 2 ≤ κ <0. 4), moderate (0. 4 ≤ κ <0. 6), substantial (0. 6 ≤ κ <0. 8) and an almost perfect agreement (κ ≥ 0. 8). For qPCR, we will apply the Pearson’s correlation coefficient to assess the agreement between the mean frequency of GE number based on the examination of individual samples and the GE based on the examination of pooled samples will be evaluated. In addition, a permutation test (10,000 iterations) will be applied to test for differences in mean GE number between the examination of individual and pooled samples. For pyrosequencing, the agreement between the mean frequency of SNPs based on the examination of individual samples and the frequency of SNPs based on the examination of pooled samples will be evaluated by the Pearson’s correlation coefficient. In addition, a permutation test will be applied to test for differences in mean frequencies between examination of individual and pooled samples. For LAMP, the κ-statistic will be determined to assess the agreement in the LAMP test results obtained by an individual and a pooled examination strategy. The impact of SNP frequency on the sensitivity of LAMP will be explored by a logistic regression model with the LAMP result as outcome (negative/positive) and the frequency of SNPs linked to BZ resistance as covariate. The predictive power of the final models will be evaluated by the proportion of the observed outcome that was correctly predicted by the model. To this end, an individual probability >0. 5 will be set as a positive test result, and negative in all other cases. The sensitivity for each of the pre-defined values of SNP frequency will be calculated based on these models.
The potential development of AR is a real threat for PC programs targeting STHs. It is facilitated by the ever-increasing quantity of anthelmintic drugs reaching at risk populations, the administration of drugs with the same mode of action at a suboptimal dose and the lack of alternative treatment options should AR eventually emerge and spread. It is therefore of paramount importance that the efficacy of the administered BZ drugs is regularly monitored. However, in order to establish a robust surveillance system to monitor drug efficacy there is a need for diagnostic methods that effectively mitigate important obstacles of performing, analysing and reporting drug efficacy surveys in resource poor settings, and a validated molecular marker to detect emergence of AR at an early stage. Based on the results from this study within the Starworms project, we aim to recommend diagnostic methods to monitor drug efficacy and molecular markers to assess the status of AR in STH control programs. We will be the first to report a comprehensive comparison of two novel egg counting methods (Mini-FLOTAC and FECPAKG2) and DNA-based methods (qPCR) with the current WHO diagnostic standard (Kato-Katz thick smear). We will not limit our comparison to the diagnostic performance but expand our analysis to compare them for the intended use-case (assessment of drug efficacy by means of egg reduction rate) and consider the associated costs and time required to perform each of the different methods. The inclusion of FECPAKG2 may create a game-changing shift in how drug efficacy can be monitored at a global scale. The online connectivity of FECPAKG2 allows easy access for quality control of egg counts and the production of standardized analysis and reports. It also opens the door to automated egg counting by egg recognition software, which when successful, could further increase throughput, reduce personnel costs and variation in egg counts between technicians or laboratories. We will provide proof-of-principle for qPCR to assess infection intensity and drug efficacy by means of GE numbers. Inclusion of qPCR will also allow for more accurate estimates of the sensitivity of the different diagnostic tests. This is of particular importance since there is no gold standard diagnostic method for STHs [67]. By standardizing the drug efficacy trials (e. g. , egg count method, follow-up period, anthelmintic drug and statistical analysis) and strategically selecting the study sites (varying drug pressure history, and hence possibly differences in drug efficacy), we hope to provide complementary insights into SNPs in the β-tubulin gene as a marker for BZ resistance in human STHs. If these SNPs play a role in AR, we expect an increase in frequency in mutant SNPs in STHs as a function of increased drug pressure history and decreased individual response to treatment. However, this molecular part of the study may face some challenges, which may impede a straightforward interpretation of the results. First, if the expected trends in SNPs are not detected, it is not possible to completely exclude them as a marker for BZ resistance. Furthermore, it could also indicate that resistance to BZ has not yet emerged, which would also jeopardize any downstream objectives (e. g. comparison of pyrosequencing and LAMP for the assessment of SNPs linked to BZ resistance and assessing pooling samples as a cost-saving strategy to determine the frequency of SNPs linked to BZ resistance). It is also important to note that any observed trends would only suggest an association rather than causal relationship. Second, it remains unclear whether we will be able to select the number of cases per level of individual response for each of the different STH species. Finally, the classification of the individual response is based on the outcome of imperfect tests (sub-optimal sensitivity), further complicating the interpretation. To conclude, the combined results of this study are expected to answer a number of outstanding questions with regards to how to best monitor drug efficacy and measure AR in populations that are being subjected to PC for STH infections. The results could be translated into novel recommendations for the scientific community on what is the best diagnostic method to assess drug efficacy in ongoing control programs and will create the basis to set up a robust surveillance system.
Soil-transmitted helminths (STHs) affect 1. 4 billion people worldwide and cause significant morbidity when the intensity of infection is high. Currently, these infections are controlled in school-aged children by preventive chemotherapy with the benzimidazole drugs albendazole (ALB) or mebendazole (MEB). However, for the success of these control programs, it is essential to keep track of the efficacy of these drugs and to screen parasite populations for a possible rise of anthelmintic resistance (AR). In this light, a series of trials will be performed to assess the efficacy of ALB treatment against STH in four endemic countries with varying drug pressure. Both microscopic and molecular stool-based diagnostic methods will be used to evaluate drug efficacy. DNA samples will also be analysed for the presence and prevalence of mutations in a gene that was previously linked to AR in animal STHs. The results of these trials will provide evidence on the efficacy of ALB, help select the optimal diagnostic method to assess drug efficacy and provide information regarding the usefulness of genetic markers for AR detection in human STHs.
invertebrates
medicine and health sciences
helminths
tropical diseases
hookworms
parasitic diseases
animals
mathematics
pharmaceutics
drug administration
neglected tropical diseases
pharmacology
extraction techniques
discrete mathematics
combinatorics
research and analysis methods
trichuris
drug efficacy evaluation
helminth infections
dna extraction
eukaryota
permutation
drug research and development
nematoda
biology and life sciences
physical sciences
drug therapy
soil-transmitted helminthiases
organisms
Comprehensive evaluation of stool-based diagnostic methods and benzimidazole resistance markers to assess drug efficacy and detect the emergence of anthelmintic resistance: A Starworms study protocol