Soil Transmitted HelminthsKAKADUNCT06055530
Evaluation of an AI-DP for STH Deworming Programs: a Study Protocol
An observational study of Soil Transmitted Helminths and Schistosomiasis Mansoni, run by Enaiblers AB.
Trial summary
The goal of this observational study is to test a new AI diagnostic tool for detection, specification and quantification of parasitic infections (Ascaris, Trichuris, hookworm and S. Mansoni) in School aged children in Ethiopia and Uganda. Read more about this study
- Who is it for?
- Ages 5 to 14 yearsHealthy volunteers can take part
- Conditions the study is for
- Soil Transmitted Helminths, Schistosomiasis Mansoni
- What is being tested?
- Artificial Intelligence Digital Pathology
- How many people
- 1,100 participants
- Where
- No sites listed yet
- Study dates
- Oct 2023to Jul 2024
- How long will I take part?
- 3 Days
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 5 to 14 years
- All sexes
- Healthy volunteers accepted
- Child
Study population: The study will focus on SAC (age 5 - 14) only, since they are the major target of large-scale deworming programs against STHs. The investigators will apply the inclusion and exclusion criteria summarized above
Who may be able to join
- Subject, male or female, is 5-14 years of age
- Parent(s)/guardian(s) of subject signed an informed consent document indicating that they understand the purpose and procedures required for the study and that they are willing to have their child participate in the study
- Subject of ≥6 (Ethiopia) /8 (Uganda) years old has assented to participate in the study*
- Subject of ≥12 years old has signed 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 (Ethiopia only)*
- Subject has provided a stool sample of minimum 5 grams
Who cannot join
- Subject has active diarrhoea (defined as the passage of 3 or more loose or liquid stools per day) at baseline or follow-up.
- Subject is experiencing a severe concurrent medical condition or has an acute medical condition
- Subject has received anthelmintic treatment within 90 days prior to the start of the study
Trial locations and contacts
No sites are listed yet.
About this study
Official title: A Comprehensive Evaluation of an Artificial Intelligence Based Digital Pathology to Monitor Large-scale Deworming Programs Against Soil-transmitted Helminths
The goal of this observational study is to test a new AI diagnostic tool for detection, specification and quantification of parasitic infections (Ascaris, Trichuris, hookworm and S. Mansoni) in School aged children in Ethiopia and Uganda. The main questions it aims to answer are:
- Diagnostic Performance of the AI tool and compare to traditional manual microscopy
- Repeatability and reproducibility of the AI tool and compare to traditional manual microscopy
- Time-to-result for the AI tool
- Cost efficiency for the AI tool and traditional manual microscopy to inform programmatic decisions.
- Usability of the AI tool
Participants will be asked to provide a stool sample for examination by the AI tool and traditional manual microscopy. Participants with a positive test result will receive the proper treatment (Deworming drug).
Read the detailed description
Manual screening of a Kato-Katz (KK) thick stool smear remains the current standard to monitor the impact of large-scale deworming programs against soil-transmitted helminths (STHs). To improve this diagnostic standard, the investigators recently designed an artificial intelligence based digital pathology system (AI-DP) for digital image capture and analysis of KK thick smears. Preliminary results of its diagnostic performance are encouraging, and a comprehensive evaluation of the AI-DP as a cost-efficient end-to-end diagnostic to inform STHs control programs against the target product profiles (TPP) of the World Health Organisation (WHO) is the next step for validation.
The study protocol describes a comprehensive evaluation of the AI-DP based on its (i) diagnostic performance, (ii) repeatability/reproducibility, (iii) time-to-result, (iv) cost-efficiency to inform large-scale deworming programs and (v) usability in both laboratory and field settings. For each of these five attributes, the investigators designed separate experiments with sufficient power to verify the non-inferiority of the AI-DP (KK2.0) over the manual screening of the KK smears (KK1.0). These experiments will be conducted in two STH endemic countries with national deworming programs (Ethiopia and Uganda), focusing on school-age children (SAC) only. Participants will be asked to provide a stool sample for examination by the AI tool and traditional manual microscopy. Participants with a positive test result will receive the proper treatment (Deworming drug).
This comprehensive and well-designed study and accompanying protocols will provide the necessary data to make an evidence-based decision on whether the AI-DP is indeed performant and a cost-efficient end-to-end diagnostic to inform large-scale deworming programs against STHs. Following the protocolized collection of high-quality data the investigators will seek approval by WHO. Through the dissemination of the methodology and statistics, the investigators hope to support additional developments in AI-DP technologies for other neglected tropical diseases in resource-limited settings.
- Being tested
- Artificial Intelligence Digital Pathology
- Keywords
- Artificial Intelligence Digital Pathology, Diagnostic Performance, Usability, Repeatability, Cost Efficiency
- Medical subject headings
- Schistosomiasis mansoni
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence Digital PathologyDiagnostic test
Also called Kato-Katz 2.0
School aged children will be asked to leave a stool sample. The samples will be prepared with the Kato-Katz method and scanned and processed by an artificial intelligence digital pathology system to determine the infection level of soil transmitted helminths and schistosomiasis. The samples will also be analyzed by a human microscopist for comparison.
| Study group | Role | What they receive |
|---|---|---|
| School aged children in Ethiopia | A number of school aged children in Ethiopia from 5-7 different schools in the Jimma region. Receives: Diagnostic Test: Artificial Intelligence Digital Pathology | |
| School aged children in Uganda | A number of school aged children from Uganda. Children from 5-7 different schools will be in the group. Receives: Diagnostic Test: Artificial Intelligence Digital Pathology |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic performance, P1.1-2
the clinical sensitivity of Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0) to detect low, moderate and heavy intensity infections of Ascaris, Trichuris and hookworms
Measured: up to 10 months
Diagnostic Performance P1.3-4
The clinical specificity of Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0) to detect low, moderate and heavy intensity infections of Ascaris, Trichuris and hookworms
Measured: up to 10 months
Repeatability and Reproducibility Performance P2
The repeatability and the reproducibility of the scanning process, the AI verification process, the Kato-Katz 2.0 (KK2.0) system as a whole and the manual counting by a microscopist (Kato-Katz 1.0 (KK1.0)).
Measured: up to 10 months
Time to Result P3
Time to result for the artificial intelligence digital pathology diagnostic (Kato-Katz 2.0 (KK2.0)) result.
Measured: up to 10 months
Cost Efficiency P4.1
The total survey cost to reliably inform a stop decision to the program for Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0).
Measured: up to 10 months
Cost Efficiency P4.2
The total survey cost to reliably inform a declaration that STH are eliminated as a public health problem for Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0).
Measured: up to 10 months
Usability observation P5
The ease-of-use of the complete AI-DP work process for the identified end-users assessed by observations of user groups and user interviews.
Measured: up to 10 months
Secondary outcomes (17)
Diagnostic performance S1.1
the clinical sensitivity and specificity of Kato-Katz 2.0 (KK2.0)KK2.0 and Kato-Katz 1.0 (KK1.0) to detect infections of S. Mansoni
Measured: up to 10 months
Diagnostic performance S1.2
The detection limit that yields a positive test result for both Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0) and Ascaris, Trichuris, hookworm and S. Mansoni separately
Measured: up to 10 months
Diagnostic performance S1.3
The egg recovery rate of KK1.0 and Kato-Katz 2.0 (KK2.0) when compared to the ground truth for Ascaris, Trichuris, hookworms and S. mansoni
Measured: up to 10 months
Diagnostic performance S1.4
the clinical sensitivity and clinical specificity of the AI-DP when the AI verification process is simplified (only objects for which the AI is uncertain) or even omitted
Measured: up to 10 months
Repeatability and Reproducibility Performance S2.1
the agreement between repeated egg counts for Ascaris, Trichuris and S. mansoni
Measured: up to 10 months
Repeatability and Reproducibility Performance S2.2
the repeatability and reproducibility in test results when the AI verification process is simplified (only objects for which the AI is uncertain)
Measured: up to 10 months
Time to Result S3.1
time for participant registration using Electronic Data Capture (EDC) tools and quick response (QR) code printing
Measured: up to 10 months
Time to Result S3.2
the correlation between time-to-result and Ascaris, Trichuris and S. mansoni egg counts recorded by Kato-Katz 2.0 (KK2.0)
Measured: up to 10 months
Time to Result S3.3
time-to-result of the AI-DP when the AI verification process is simplified (only objects for which the AI is uncertain) or even omitted
Measured: up to 10 months
Cost Efficiency S4.1
the total survey cost to make reliable program decisions on the frequency of large-scale deworming programs for Kato-Katz 2.0 (KK2.0) and KK1.0
Measured: up to 10 months
Cost Efficiency S4.2
the total survey cost to reliably monitor the therapeutic drug efficacy of anthelmintic against STHs for Kato-Katz 2.0 (KK2.0)
Measured: up to 10 months
Cost Efficiency S4.3
the total survey cost to make reliable program decisions on the frequency of large-scale deworming programs for Kato-Katz 2.0 (KK2.0) when the AI verification process is simplified (only objects for which the AI is uncertain) or even omitted
Measured: up to 10 months
Cost Efficiency S4.4
the required performance of AI to make reliable program decisions on the frequency of large-scale deworming programs for Kato-Katz 2.0 (KK2.0)
Measured: up to 10 months
Cost Efficiency S4.5
the optimal set-up for Kato-Katz 2.0 (KK2.0) (sample throughput; number of AI-DP devices; number of operators) to inform large-scale deworming programs when deployed in a fully equipped laboratory and M\&E setting
Measured: up to 10 months
Usability observation S5.1
identification of barriers for a successful outcome of the complete work process with the AI-DP device by the identified end-users
Measured: up to 10 months
Usability observation S5.2
The task completion time for novel users of the AI-DP device
Measured: up to 10 months
Usability observation S5.3
Outcome rates (Success/failure) for novel users of the AI-DP device.
Measured: up to 10 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Sep 2023
- Study startOct 2023 (estimated)
- Primary completionDec 2023 (estimated)
- Study completionJul 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Soil Transmitted HelminthsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,100 participants (estimated)
- Target duration
- 3 Days
Sponsor and investigators
- Lead sponsor
- Enaiblers AB
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Jimma University, Ministry of Health, Uganda, University Ghent
- Responsible party
- Sponsor
- Investigators
- Bruno Levecke, PhD, Study director, University GhentZeleke Mekonnen, PhD, Principal investigator, Jimma UniversityNarcis Kabatereine, PhD, Principal investigator, Ministry of Health, Uganda
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06055530
- Sponsor's protocol ID
- EN-2023-CT001
- Other IDs
- 76906491
- Acronym
- KAKADU
- Status last verified
- Sep 2023
- First submitted
- 15 Sep 2023
- Last updated
- 2 Oct 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: The investigators do not intend to share individual participant data (IPD).
Publications
Ward PK, Roose S, Ayana M, Broadfield LA, Dahlberg P, Kabatereine N, Kazienga A, Mekonnen Z, Nabatte B, Stuyver L, Velde FV, Hoecke SV, Levecke B. A comprehensive evaluation of an artificial intelligence based digital pathology to monitor large-scale deworming programs against soil-transmitted helminths: A study protocol. PLoS One. 2024 Oct 28;19(10):e0309816. doi: 10.1371/journal.pone.0309816. eCollection 2024.
PubMed 39466830
Study at a glance
From the registry record, last updated by the sponsor on 2 Oct 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Comprehensive Evaluation of an Artificial Intelligence Based Digital Pathology to Monitor Large-scale Deworming Programs Against Soil-transmitted Helminths
- ClinicalTrials.gov ID
- NCT06055530
- Acronym / sponsor ID
- KAKADU / EN-2023-CT001
- Keywords
- Artificial Intelligence Digital Pathology, Diagnostic Performance, Usability, Repeatability, Cost Efficiency
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,100 participants (estimated)
- Lead sponsor
- Enaiblers ABIndustry (pharma, biotech, devices)
- Collaborators
- Jimma University, Ministry of Health, Uganda, University Ghent
- Study start
- Oct 2023 (estimated)
- Primary completion
- Dec 2023 (estimated)
- Study completion
- Jul 2024 (estimated)
- First posted
- 26 Sep 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this observational study is to test a new AI diagnostic tool for detection, specification and quantification of parasitic infections (Ascaris, Trichuris, hookworm and S. Mansoni) in School aged children in Ethiopia and Uganda. The main questions it aims to answer are:
- Diagnostic Performance of the AI tool and compare to traditional manual microscopy
- Repeatability and reproducibility of the AI tool and compare to traditional manual microscopy
- Time-to-result for the AI tool
- Cost efficiency for the AI tool and traditional manual microscopy to inform programmatic decisions.
- Usability of the AI tool
Participants will be asked to provide a stool sample for examination by the AI tool and traditional manual microscopy. Participants with a positive test result will receive the proper treatment (Deworming drug).
Detailed description
Manual screening of a Kato-Katz (KK) thick stool smear remains the current standard to monitor the impact of large-scale deworming programs against soil-transmitted helminths (STHs). To improve this diagnostic standard, the investigators recently designed an artificial intelligence based digital pathology system (AI-DP) for digital image capture and analysis of KK thick smears. Preliminary results of its diagnostic performance are encouraging, and a comprehensive evaluation of the AI-DP as a cost-efficient end-to-end diagnostic to inform STHs control programs against the target product profiles (TPP) of the World Health Organisation (WHO) is the next step for validation.
The study protocol describes a comprehensive evaluation of the AI-DP based on its (i) diagnostic performance, (ii) repeatability/reproducibility, (iii) time-to-result, (iv) cost-efficiency to inform large-scale deworming programs and (v) usability in both laboratory and field settings. For each of these five attributes, the investigators designed separate experiments with sufficient power to verify the non-inferiority of the AI-DP (KK2.0) over the manual screening of the KK smears (KK1.0). These experiments will be conducted in two STH endemic countries with national deworming programs (Ethiopia and Uganda), focusing on school-age children (SAC) only. Participants will be asked to provide a stool sample for examination by the AI tool and traditional manual microscopy. Participants with a positive test result will receive the proper treatment (Deworming drug).
This comprehensive and well-designed study and accompanying protocols will provide the necessary data to make an evidence-based decision on whether the AI-DP is indeed performant and a cost-efficient end-to-end diagnostic to inform large-scale deworming programs against STHs. Following the protocolized collection of high-quality data the investigators will seek approval by WHO. Through the dissemination of the methodology and statistics, the investigators hope to support additional developments in AI-DP technologies for other neglected tropical diseases in resource-limited settings.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 3 Days
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| School aged children in Ethiopia | – | Diagnostic Test: Artificial Intelligence Digital PathologyA number of school aged children in Ethiopia from 5-7 different schools in the Jimma region. |
| School aged children in Uganda | – | Diagnostic Test: Artificial Intelligence Digital PathologyA number of school aged children from Uganda. Children from 5-7 different schools will be in the group. |
Who may qualify
- Ages
- 5 to 14 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child
- Study population
- The study will focus on SAC (age 5 - 14) only, since they are the major target of large-scale deworming programs against STHs. The investigators will apply the inclusion and exclusion criteria summarized above
Key inclusion criteria (5 listed)
- Subject, male or female, is 5-14 years of age
- Parent(s)/guardian(s) of subject signed an informed consent document indicating that they understand the purpose and procedures required for the study and that they are willing to have their child participate in the study
- Subject of ≥6 (Ethiopia) /8 (Uganda) years old has assented to participate in the study*
- Subject of ≥12 years old has signed 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 (Ethiopia only)*
- Subject has provided a stool sample of minimum 5 grams
Key exclusion criteria (3 listed)
- Subject has active diarrhoea (defined as the passage of 3 or more loose or liquid stools per day) at baseline or follow-up.
- Subject is experiencing a severe concurrent medical condition or has an acute medical condition
- Subject has received anthelmintic treatment within 90 days prior to the start of the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence Digital PathologyAlso: Kato-Katz 2.0School aged children will be asked to leave a stool sample. The samples will be prepared with the Kato-Katz method and scanned and processed by an artificial intelligence digital pathology system to determine the infection level of soil transmitted helminths and schistosomiasis. The samples will also be analyzed by a human microscopist for comparison. | Diagnostic test | School aged children in Ethiopia, School aged children in Uganda |
Primary outcome
Diagnostic performance, P1.1-2
Time frame: up to 10 months
the clinical sensitivity of Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0) to detect low, moderate and heavy intensity infections of Ascaris, Trichuris and hookworms
Diagnostic Performance P1.3-4
Time frame: up to 10 months
The clinical specificity of Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0) to detect low, moderate and heavy intensity infections of Ascaris, Trichuris and hookworms
Repeatability and Reproducibility Performance P2
Time frame: up to 10 months
The repeatability and the reproducibility of the scanning process, the AI verification process, the Kato-Katz 2.0 (KK2.0) system as a whole and the manual counting by a microscopist (Kato-Katz 1.0 (KK1.0)).
Time to Result P3
Time frame: up to 10 months
Time to result for the artificial intelligence digital pathology diagnostic (Kato-Katz 2.0 (KK2.0)) result.
Cost Efficiency P4.1
Time frame: up to 10 months
The total survey cost to reliably inform a stop decision to the program for Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0).
Cost Efficiency P4.2
Time frame: up to 10 months
The total survey cost to reliably inform a declaration that STH are eliminated as a public health problem for Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0).
Usability observation P5
Time frame: up to 10 months
The ease-of-use of the complete AI-DP work process for the identified end-users assessed by observations of user groups and user interviews.
17 secondary outcomes
Diagnostic performance S1.1
Time frame: up to 10 months
Diagnostic performance S1.2
Time frame: up to 10 months
Diagnostic performance S1.3
Time frame: up to 10 months
Diagnostic performance S1.4
Time frame: up to 10 months
Repeatability and Reproducibility Performance S2.1
Time frame: up to 10 months
Repeatability and Reproducibility Performance S2.2
Time frame: up to 10 months
Time to Result S3.1
Time frame: up to 10 months
Time to Result S3.2
Time frame: up to 10 months
Time to Result S3.3
Time frame: up to 10 months
Cost Efficiency S4.1
Time frame: up to 10 months
Cost Efficiency S4.2
Time frame: up to 10 months
Cost Efficiency S4.3
Time frame: up to 10 months
Cost Efficiency S4.4
Time frame: up to 10 months
Cost Efficiency S4.5
Time frame: up to 10 months
Usability observation S5.1
Time frame: up to 10 months
Usability observation S5.2
Time frame: up to 10 months
Usability observation S5.3
Time frame: up to 10 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Oct 2023.
- Derived from this study: PubMed 39466830Ward PK, Roose S, Ayana M, Broadfield LA, Dahlberg P, Kabatereine N, Kazienga A, Mekonnen Z, Nabatte B, Stuyver L, Velde FV, Hoecke SV, Levecke B. A comprehensive evaluation of an artificial intelligence based digital pathology to monitor large-scale deworming programs against soil-transmitted helminths: A study protocol. PLoS One. 2024 Oct 28;19(10):e0309816. doi: 10.1371/journal.pone.0309816. eCollection 2024.
- Individual participant dataSharing planned: No. The investigators do not intend to share individual participant data (IPD).
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Bruno Levecke, PhD study director
University Ghent
Zeleke Mekonnen, PhD principal investigator
Jimma University
Narcis Kabatereine, PhD principal investigator
Ministry of Health, Uganda
Questions about this trial
What is this clinical trial studying?
An observational study of Soil Transmitted Helminths and Schistosomiasis Mansoni, run by Enaiblers AB.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 2 Oct 2023. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Peter Dahlberg, MSc (+46735195218, peter.dahlberg@enaiblers.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic performance, P1.1-2 (time frame: up to 10 months). The study lists 7 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06055530, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 2 Oct 2023.