xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT06042543</url>
    </required_header>
    <id_info>
      <org_study_id>IEC 22-32</org_study_id>
      <secondary_id>R37CA275824</secondary_id>
      <nct_id>NCT06042543</nct_id>
    </id_info>
    <brief_title>Novel, One Stop, Affordable, Point of Care and AI Supported System of Screening, Triage and Treatment Selection for Cervical Cancer in LMICs</brief_title>
    <acronym>EASTER</acronym>
    <official_title>A Novel, One Stop, Affordable, Point of Care and Artificial Intelligence Supported System of Screening, Triage and Treatment Selection for Cervical Cancer and Precancer in the Low-to-middle Income Countries</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>International Agency for Research on Cancer</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>University of California, San Francisco</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>University of Zimbabwe</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Lancaster University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Neo Sense Vector (NSV)</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>National Cancer Institute (NCI)</agency>
        <agency_class>NIH</agency_class>
      </collaborator>
    </sponsors>
    <source>International Agency for Research on Cancer</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        AI is fast gaining reputation as a highly promising solution for cervical cancer screening.&#xD;
        AI-based detection of cervical neoplasias is named automated visual exam (AVE) by the US NCI.&#xD;
        The investigators propose to develop and evaluate the performance characteristics of a novel&#xD;
        AI system to both screen and triage women as well as help in treatment decision making. AI&#xD;
        will analyse infrared spectroscopic signals derived from urine samples of unscreened women&#xD;
        for the presence of high-risk Human Papillomavirus (hr-HPV). Our preliminary study has shown&#xD;
        that spectroscopy can detect hr-HPV in urine. For screen-positive women the AI will interpret&#xD;
        a set of cervical images captured with a high-quality devoted camera to detect high grade&#xD;
        cervical precancers and cancers and to determine the type of transformation zone (TZ) (helps&#xD;
        in treatment decision). The prototype device for image capture and the AI algorithms are&#xD;
        already developed by us. The technologies will be further improved in part 1 (initial 2&#xD;
        years) and validated in part 2 (subsequent 3 years). During Part 1, the investigators will&#xD;
        analyse urine samples collected from 1100 women at multiple screening clinics in Zimbabwe for&#xD;
        the presence of hr-HPV using spectroscopy and use the signals generated to improve the AI&#xD;
        algorithm. In this part the investigators will also assess the concordance between hr-HPV&#xD;
        detection in urine samples using spectroscopy and cervical HPV detection using a validated&#xD;
        HPV test. The cervical image recognition device and the AI algorithm will be further improved&#xD;
        during part 1 by collecting more images from hr-HPV positive and negative women. AI will also&#xD;
        be trained to interpret the cervical images to determine the TZ type. In part 2 total 2100&#xD;
        women will be screened in Zimbabwe with AI-supported spectroscopic analysis of urine to&#xD;
        detect hrHPV and a validated HPV test to evaluate and compare their sensitivity and&#xD;
        specificity to detect histology-proved high grade cervical precancers and cancers. The&#xD;
        sensitivity and specificity of AI-supported detection of cervical neoplasias on cervical&#xD;
        images will be evaluated to triage the HPV positive women. The accuracy of AI to determine TZ&#xD;
        type will be compared with expert opinion. During the field validation part (part 2), the&#xD;
        investigators will also conduct a cost analysis and compare cost of our approach to current&#xD;
        standard Zimbabwean practice. The International Agency for Research on Cancer (WHO cancer&#xD;
        research organization) has partnered with The Neo Sense Vector Company (NSV), Delaware, USA&#xD;
        (industry), The Engineering Department, Lancaster University, Lancaster, UK and The&#xD;
        University of Zimbabwe, College of Health Sciences, Harare, Zimbabwe to implement this study&#xD;
        focusing on innovation that will greatly contribute to the global elimination of cervical&#xD;
        cancer, a WHO priority.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        Cervical cancer is a major public health challenge killing over 300,000 women annually at the&#xD;
        most productive period of their lives and disproportionately affecting women in LMICs. Even&#xD;
        in developed countries like the USA, the disparity between low- and high-income populations&#xD;
        is striking. A cervical cancer death dramatically alters family and societal dynamics. In&#xD;
        sub-Saharan Africa (SSA) for every 100 women who die from cervical cancer, 14 to 30 children&#xD;
        die as an indirect consequence. Indeed, cervical cancer mortality is a real impediment to&#xD;
        achieving WHO's Sustainable Development Goal of reducing premature mortality from non-&#xD;
        communicable diseases (NCD) by a third before 2030. WHO have also recently adopted a&#xD;
        resolution to eliminate cervical cancer globally. Whilst HPV vaccination will undoubtedly&#xD;
        support this ambition for the next generation of girls, this vision also demands an effective&#xD;
        screening and treatment programme. Yet current LMIC screening, investigation, and treatment&#xD;
        regimes, especially are deeply flawed and not widely adopted.&#xD;
  &#xD;
        The EASTER project aims to further develop and validate two new technologies for cervical&#xD;
        cancer screening and diagnosis: (i) screening for human papillomavirus (HPV) in urine with&#xD;
        spectroscopy, and (ii) diagnosis with artificial intelligence-assisted technology from NSV, a&#xD;
        private company. The project will recruit 3200 women and screen them for HPV.&#xD;
  &#xD;
        The project will be implemented in two parts. Part 1. Technology improvement to achieve two&#xD;
        key improvements.&#xD;
  &#xD;
          -  Improve the performance of spectroscopy and AI to detect hr-HPV in urine samples.&#xD;
  &#xD;
          -  Improve the performance of the n-Gyn device and AI to capture the cervical images and&#xD;
             interpret them.&#xD;
  &#xD;
        Part 2. In the second part of the study, the investigators will test the functionality and&#xD;
        effectiveness of the AI algorithms and devices developed through Part 1 in the same setting&#xD;
        in Zimbabwe. The developed system of AI interpretation of urine samples will be evaluated as&#xD;
        a screening test to detect CIN2+ lesions and compared to a validated HPV detection test. The&#xD;
        AI diagnostic accuracy of n-Gyn system to detect CIN2+ lesions based on captured cervical&#xD;
        images will be evaluated as a triage test for HPV positive women in the detection of&#xD;
        histopathologically confirmed CIN 2+ lesions.&#xD;
  &#xD;
        Settings, procedures, and analysis:&#xD;
  &#xD;
        The EASTER project (Part 1 and Part 2) will be implemented in two screening polyclinics&#xD;
        (Epworth and Mbare) in Harare where women are routinely screened (with an average of 15% of&#xD;
        WLHIV participants). Women aged 25-49 who agree to participate and sign the corresponding&#xD;
        Institutional Review Board (IRB) approved consent forms will be requested to provide two&#xD;
        self-collected samples, 1) a first void urine sample and 2) a self-collected vaginal sample.&#xD;
        Recruitment specimens will be tested for HPV with Ampfire. Women HPV positive in either&#xD;
        sample will be referred to colposcopy for disease ascertainment.&#xD;
  &#xD;
        The colposcopist will examine the cervical images on the n-Gyn screen and independent of AI&#xD;
        will document the visibility and location of the SCJ, type of TZ, Swede score, most&#xD;
        appropriate site for taking biopsy (if any abnormalities are present) and suitability for&#xD;
        treatment by ablation. Sequential images of the transformation zone will be obtained before&#xD;
        and after cleaning with normal saline and then after applying 5% acetic acid for one minute.&#xD;
        Appropriate magnifications will be used to enable delineation of the SCJ and to identify the&#xD;
        worst area of suspected abnormality. A final image will be captured after the application of&#xD;
        Lugol's iodine. After the images have been collected, the clinician will take at least one&#xD;
        punch biopsy from the most abnormal site determined by him/her. If no lesion is visible,&#xD;
        biopsies will be obtained from the 6 and 12 o'clock positions closest to the SCJ. All&#xD;
        histopathology slides will be examined by pathologists at Lancet Laboratories in Harare. The&#xD;
        patient will be managed based according to the local management protocol.&#xD;
  &#xD;
        Women will be managed according to clinical coloscopy diagnosis: women without visible lesion&#xD;
        will exit the study at this point. Women with visible lesions will be treated with thermal&#xD;
        ablation if eligible or LLETZ if needed and exit the study. Women diagnosed with cancer will&#xD;
        be referred to the regular system for appropriate management and exit the study.&#xD;
  &#xD;
        Data management and study supervision will be the responsibility of the International Agency&#xD;
        for Research on Cancer (IARC) and the local Principal Investigators, who are experienced HPV&#xD;
        researchers.&#xD;
  &#xD;
        The outcome of primary interest for the statical evaluation will be histologically confirmed&#xD;
        cervical intraepithelial neoplasia grade 2 or worse (CIN2+), including CIN2 lesions positive&#xD;
        for p16. For Part I, our analyses will focus on the agreement between hr-HPV detection by&#xD;
        spectroscopic analysis of urine and by Ampfire HPV, which will be tested using the Cohen's&#xD;
        kappa statistic. Spectroscopy will be deemed as good as HPV testing in defining screen&#xD;
        results if a kappa of 0.7 (80% agreement) is achieved. For Part 2, standard formulations will&#xD;
        be used to calculate the test performance characteristics (sensitivity/specificity). For the&#xD;
        comparison of the performance characteristics of the screening tests, if ẟ is the&#xD;
        hypothesized relative sensitivity (or specificity), the equivalence of the two tests will be&#xD;
        inferred if the true relative risk to be within the interval (ẟ to 1/ẟ). The test of&#xD;
        proportions will be used to assess if the performance characteristics of the triage tests are&#xD;
        not different from the hypothesized value.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">September 30, 2023</start_date>
    <completion_date type="Anticipated">December 31, 2027</completion_date>
    <primary_completion_date type="Anticipated">December 31, 2027</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Other</observational_model>
      <time_perspective>Prospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>Histologically confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+)</measure>
      <time_frame>a) Through completion of part 1, an average of 2 years from the start of recruitment; b) Through completion of part 2, an average of 3 years after completion of part 1</time_frame>
      <description>Participants with histologically confirmed cervical intraepithelial neoplasia grade 2, 3 or cancer, including CIN2 positive for p16.</description>
    </primary_outcome>
    <enrollment type="Anticipated">3200</enrollment>
    <condition>Cervical Cancer</condition>
    <condition>Screening</condition>
    <biospec_retention>Samples With DNA</biospec_retention>
    <biospec_descr>
      <textblock>
        The women participating in the study will be asked to provide two types of samples at&#xD;
        recruitment.&#xD;
  &#xD;
        1 ) Urine sample: Women will self-collect 10ml of first-stream Urine using the ColipeeTM&#xD;
        collecting device in the clinic. After HPV testing, the leftover samples will be aliquoted&#xD;
        and stored at -70C 2) Vaginal self-sampling: Women will self-collect an upper vaginal sample&#xD;
        using a dry swab. In the lab, the swab will be washed in 4ml of preservation medium. After&#xD;
        HPV testing, the leftover samples will be aliquoted and stored at -70C Stored samples will be&#xD;
        used for quality assurance and to address any discordant results between Urine and cervical&#xD;
        cell sampling.&#xD;
      </textblock>
    </biospec_descr>
    <eligibility>
      <study_pop>
        <textblock>
          This study will be conducted in 2 polyclinics (Epworth and Mbare) in Harare, Zimbabwe. All&#xD;
          women 25 to 49 residents of the selected area will be invited using different approaches to&#xD;
          the local health centers where screening is to happen.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  No cervical screening during the previous 3 years&#xD;
  &#xD;
            -  Between the ages of 25 and 49 years&#xD;
  &#xD;
            -  Understands and signs a written informed consent form&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Refusal to take part for any reason&#xD;
  &#xD;
            -  Actively menstruating or pregnant&#xD;
  &#xD;
            -  Treated earlier for cervical precancer or cancer&#xD;
        </textblock>
      </criteria>
      <gender>Female</gender>
      <gender_based>Yes</gender_based>
      <gender_description>Female</gender_description>
      <minimum_age>25 Years</minimum_age>
      <maximum_age>49 Years</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Partha Basu, MD</last_name>
      <role>Principal Investigator</role>
      <affiliation>International Agency For Research On Cancer (IARC)</affiliation>
    </overall_official>
    <overall_official>
      <last_name>Bothwell Guzha, MD</last_name>
      <role>Principal Investigator</role>
      <affiliation>University of Zimbabwe</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Partha Basu, MD</last_name>
      <phone>+33764485370</phone>
      <email>basup@iarc.who.int</email>
    </overall_contact>
    <location>
      <facility>
        <name>Bothwell Guzha</name>
        <address>
          <city>Harare</city>
          <zip>0002</zip>
          <country>Zimbabwe</country>
        </address>
      </facility>
      <contact>
        <last_name>Bothwell Guzha, MD</last_name>
        <email>bothwellguzha@gmail.com</email>
      </contact>
    </location>
    <location_countries>
      <country>Zimbabwe</country>
    </location_countries>
    <verification_date>September 2023</verification_date>
    <study_first_submitted>September 6, 2023</study_first_submitted>
    <study_first_submitted_qc>September 15, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">September 18, 2023</study_first_posted>
    <last_update_submitted>September 15, 2023</last_update_submitted>
    <last_update_submitted_qc>September 15, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">September 18, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Uterine Cervical Neoplasms</mesh_term>
    </condition_browse>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT06042543
  org study id: IEC 22-32
  secondary id: R37CA275824
  nct id: NCT06042543
  lead sponsor: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  AI is fast gaining reputation as a highly promising solution for cervical cancer screening.
        AI-based detection of cervical neoplasias is named automated visual exam (AVE) by the US NCI.
        The investigators propose to develop and evaluate the performance characteristics of a novel
        AI system to both screen and triage women as well as help in treatment decision making. AI
        will analyse infrared spectroscopic signals derived from urine samples of unscreened women
        for the presence of high-risk Human Papillomavirus (hr-HPV). Our preliminary study has shown
        that spectroscopy can detect hr-HPV in urine. For screen-positive women the AI will interpret
        a set of cervical images captured with a high-quality devoted camera to detect high grade
        cervical precancers and cancers and to determine the type of transformation zone (TZ) (helps
        in treatment decision). The prototype device for image capture and the AI algorithms are
        already developed by us. The technologies will be further improved in part 1 (initial 2
        years) and validated in part 2 (subsequent 3 years). During Part 1, the investigators will
        analyse urine samples collected from 1100 women at multiple screening clinics in Zimbabwe for
        the presence of hr-HPV using spectroscopy and use the signals generated to improve the AI
        algorithm. In this part the investigators will also assess the concordance between hr-HPV
        detection in urine samples using spectroscopy and cervical HPV detection using a validated
        HPV test. The cervical image recognition device and the AI algorithm will be further improved
        during part 1 by collecting more images from hr-HPV positive and negative women. AI will also
        be trained to interpret the cervical images to determine the TZ type. In part 2 total 2100
        women will be screened in Zimbabwe with AI-supported spectroscopic analysis of urine to
        detect hrHPV and a validated HPV test to evaluate and compare their sensitivity and
        specificity to detect histology-proved high grade cervical precancers and cancers. The
        sensitivity and specificity of AI-supported detection of cervical neoplasias on cervical
        images will be evaluated to triage the HPV positive women. The accuracy of AI to determine TZ
        type will be compared with expert opinion. During the field validation part (part 2), the
        investigators will also conduct a cost analysis and compare cost of our approach to current
        standard Zimbabwean practice. The International Agency for Research on Cancer (WHO cancer
        research organization) has partnered with The Neo Sense Vector Company (NSV), Delaware, USA
        (industry), The Engineering Department, Lancaster University, Lancaster, UK and The
        University of Zimbabwe, College of Health Sciences, Harare, Zimbabwe to implement this study
        focusing on innovation that will greatly contribute to the global elimination of cervical
        cancer, a WHO priority.
  Cervical cancer is a major public health challenge killing over 300,000 women annually at the
        most productive period of their lives and disproportionately affecting women in LMICs. Even
        in developed countries like the USA, the disparity between low- and high-income populations
        is striking. A cervical cancer death dramatically alters family and societal dynamics. In
        sub-Saharan Africa (SSA) for every 100 women who die from cervical cancer, 14 to 30 children
        die as an indirect consequence. Indeed, cervical cancer mortality is a real impediment to
        achieving WHO's Sustainable Development Goal of reducing premature mortality from non-
        communicable diseases (NCD) by a third before 2030. WHO have also recently adopted a
        resolution to eliminate cervical cancer globally. Whilst HPV vaccination will undoubtedly
        support this ambition for the next generation of girls, this vision also demands an effective
        screening and treatment programme. Yet current LMIC screening, investigation, and treatment
        regimes, especially are deeply flawed and not widely adopted.
  
        The EASTER project aims to further develop and validate two new technologies for cervical
        cancer screening and diagnosis: (i) screening for human papillomavirus (HPV) in urine with
        spectroscopy, and (ii) diagnosis with artificial intelligence-assisted technology from NSV, a
        private company. The project will recruit 3200 women and screen them for HPV.
  
        The project will be implemented in two parts. Part 1. Technology improvement to achieve two
        key improvements.
  
          -  Improve the performance of spectroscopy and AI to detect hr-HPV in urine samples.
  
          -  Improve the performance of the n-Gyn device and AI to capture the cervical images and
             interpret them.
  
        Part 2. In the second part of the study, the investigators will test the functionality and
        effectiveness of the AI algorithms and devices developed through Part 1 in the same setting
        in Zimbabwe. The developed system of AI interpretation of urine samples will be evaluated as
        a screening test to detect CIN2+ lesions and compared to a validated HPV detection test. The
        AI diagnostic accuracy of n-Gyn system to detect CIN2+ lesions based on captured cervical
        images will be evaluated as a triage test for HPV positive women in the detection of
        histopathologically confirmed CIN 2+ lesions.
  
        Settings, procedures, and analysis:
  
        The EASTER project (Part 1 and Part 2) will be implemented in two screening polyclinics
        (Epworth and Mbare) in Harare where women are routinely screened (with an average of 15% of
        WLHIV participants). Women aged 25-49 who agree to participate and sign the corresponding
        Institutional Review Board (IRB) approved consent forms will be requested to provide two
        self-collected samples, 1) a first void urine sample and 2) a self-collected vaginal sample.
        Recruitment specimens will be tested for HPV with Ampfire. Women HPV positive in either
        sample will be referred to colposcopy for disease ascertainment.
  
        The colposcopist will examine the cervical images on the n-Gyn screen and independent of AI
        will document the visibility and location of the SCJ, type of TZ, Swede score, most
        appropriate site for taking biopsy (if any abnormalities are present) and suitability for
        treatment by ablation. Sequential images of the transformation zone will be obtained before
        and after cleaning with normal saline and then after applying 5% acetic acid for one minute.
        Appropriate magnifications will be used to enable delineation of the SCJ and to identify the
        worst area of suspected abnormality. A final image will be captured after the application of
        Lugol's iodine. After the images have been collected, the clinician will take at least one
        punch biopsy from the most abnormal site determined by him/her. If no lesion is visible,
        biopsies will be obtained from the 6 and 12 o'clock positions closest to the SCJ. All
        histopathology slides will be examined by pathologists at Lancet Laboratories in Harare. The
        patient will be managed based according to the local management protocol.
  
        Women will be managed according to clinical coloscopy diagnosis: women without visible lesion
        will exit the study at this point. Women with visible lesions will be treated with thermal
        ablation if eligible or LLETZ if needed and exit the study. Women diagnosed with cancer will
        be referred to the regular system for appropriate management and exit the study.
  
        Data management and study supervision will be the responsibility of the International Agency
        for Research on Cancer (IARC) and the local Principal Investigators, who are experienced HPV
        researchers.
  
        The outcome of primary interest for the statical evaluation will be histologically confirmed
        cervical intraepithelial neoplasia grade 2 or worse (CIN2+), including CIN2 lesions positive
        for p16. For Part I, our analyses will focus on the agreement between hr-HPV detection by
        spectroscopic analysis of urine and by Ampfire HPV, which will be tested using the Cohen's
        kappa statistic. Spectroscopy will be deemed as good as HPV testing in defining screen
        results if a kappa of 0.7 (80% agreement) is achieved. For Part 2, standard formulations will
        be used to calculate the test performance characteristics (sensitivity/specificity). For the
        comparison of the performance characteristics of the screening tests, if ẟ is the
        hypothesized relative sensitivity (or specificity), the equivalence of the two tests will be
        inferred if the true relative risk to be within the interval (ẟ to 1/ẟ). The test of
        proportions will be used to assess if the performance characteristics of the triage tests are
        not different from the hypothesized value.
  observational model: Other
  time perspective: Prospective
  measure: Histologically confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+)
  time frame: a) Through completion of part 1, an average of 2 years from the start of recruitment; b) Through completion of part 2, an average of 3 years after completion of part 1
  description: Participants with histologically confirmed cervical intraepithelial neoplasia grade 2, 3 or cancer, including CIN2 positive for p16.
  The women participating in the study will be asked to provide two types of samples at
        recruitment.
  
        1 ) Urine sample: Women will self-collect 10ml of first-stream Urine using the ColipeeTM
        collecting device in the clinic. After HPV testing, the leftover samples will be aliquoted
        and stored at -70C 2) Vaginal self-sampling: Women will self-collect an upper vaginal sample
        using a dry swab. In the lab, the swab will be washed in 4ml of preservation medium. After
        HPV testing, the leftover samples will be aliquoted and stored at -70C Stored samples will be
        used for quality assurance and to address any discordant results between Urine and cervical
        cell sampling.
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: Female
  gender based: Yes
  gender description: Female
  minimum age: 25 Years
  maximum age: 49 Years
  healthy volunteers: No
  last name: Partha Basu, MD
  role: Principal Investigator
  affiliation: International Agency For Research On Cancer (IARC)
  last name: Bothwell Guzha, MD
  role: Principal Investigator
  affiliation: University of Zimbabwe
  last name: Partha Basu, MD
  phone: +33764485370
  email: basup@iarc.who.int
  facility: 
  contact: 
  country: Zimbabwe
  responsible party type: Sponsor
  mesh term: Uterine Cervical Neoplasms