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Record W4387664502 · doi:10.7554/elife.91469.1

Design of the HPV-Automated Visual Evaluation (PAVE) Study: Validating a Novel Cervical Screening Strategy

2023· preprint· en· W4387664502 on OpenAlexaboutno aff
Sílvia de Sanjosé, Rebecca B. Perkins, Nicole G. Campos, Federica Inturrisi, Didem Egemen, Brian Befano, Ana Cecilia Rodríguez, José Jerónimo, Li C. Cheung, Kanan Desai, Paul K. J. Han, Akiva P. Novetsky, Abigail Ukwuani, Jenna Marcus, Syed Rakin Ahmed, Nicolas Wentzensen, Jayashree Kalpathy–Cramer, Mark Schiffman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsnot available
FundersMoonshot Research and Development ProgramNational Cancer InstituteNational Institutes of Health
KeywordsTriageCervixMedicineCervical cancerGenotypingVisual inspectionCervical cancer screeningMedical physicsOncologyCancerInternal medicineArtificial intelligenceMedical emergencyComputer scienceBiology

Abstract

fetched live from OpenAlex

Abstract Objective To describe the HPV-Automated Visual Evaluation (PAVE) Study, an international, multi-centric study designed to evaluate a novel cervical screen-triage-treat strategy for resource-limited settings as part of a global strategy to reduce cervical cancer burden. The PAVE strategy involves: 1) screening with self-sampled HPV testing; 2) triage of HPV-positive participants with a combination of extended genotyping and visual evaluation of the cervix assisted by deep-learning-based automated visual evaluation (AVE); and 3) treatment with thermal ablation or excision (Large Loop Excision of the Transformation Zone). The PAVE study has two phases: efficacy (2023-2024) and effectiveness (planned to begin in 2024-2025). The efficacy phase aims to refine and validate the screen-triage portion of the protocol. The effectiveness phase will examine implementation of the PAVE strategy into clinical practice, cost-effectiveness, and health communication. Study design Phase 1 Efficacy: Nonpregnant women, aged 25-49 years, without prior hysterectomy, are being screened at nine study sites in resource-limited settings. Eligible and consenting participants perform self-collection of vaginal specimens for HPV testing using a FLOQSwab (Copan). Swabs are transported dry and undergo testing for HPV using a newly-redesigned isothermal DNA amplification HPV test (ScreenFire), which has been designed to provide HPV genotyping by hierarchical risk groups: HPV16, else HPV18/45, else HPV31/33/35/52/58, else HPV39/51/56/59/68. HPV-negative individuals are considered negative for precancer/cancer and do not undergo further testing. HPV-positive individuals undergo pelvic examination with collection of cervical images and targeted biopsies of all acetowhite areas or endocervical sampling in the absence of visible lesions. Cervical images are used to refine a deep learning AVE algorithm that classifies images as normal, indeterminate, or precancer+. AVE classifications are validated against the histologic endpoint of high-grade precancer determined by biopsy. The combination of HPV genotype and AVE classification is used to generate a risk score that corresponds to the risk of precancer (lower, medium, high, highest). During the efficacy phase, clinicians and patients will receive HPV testing results but not AVE results or risk scores. Treatment during the efficacy phase will be performed per local standard of care: positive Visual Inspection with Acetic Acid impression, high-grade colposcopic impression or CIN2+ on colposcopic biopsy, HPV positivity, or HPV 16,18/45 positivity. The sensitivity of the PAVE strategy for detection of precancer will be compared to current SOC at a given level of specificity. Phase 2 Effectiveness: The AVE software will be downloaded to the new dedicated image analysis and thermal ablation devices (Liger Iris) into which the HPV genotype information can be entered to provide risk HPV-AVE risk scores for precancer to clinicians in real time. The effectiveness phase will examine clinician use of the PAVE strategy in practice, including feasibility and acceptability for clinicians and patients, cost-effectiveness, and health communication. Conclusion The goal of the PAVE study is to validate a screen-triage-treat protocol using novel biomarkers to provide an accurate, feasible, cost-effective strategy for cervical cancer prevention in resource-limited settings. PAVE Study Group Brazil Ana Ribeiro - ana-ribeiro.dantas@fiocruz.br Tainá Raiol - taina.raiol@fiocruz.br Center for Women’s Integrated Health, Oswaldo Cruz Foundation (Fiocruz), Brasília, DF, Brazil. MARCO Clinical and Molecular Research Center, University Hospital of Brasília/EBSERH, Federal District, Brazil Cambodia Te Vantha, MD, Director of Takeo Provincial Hospital,Cambodia Thay Sovannara, MD, Medical Practitioner, Raffles Medical Group, Cambodia Judith Norman, MD, Director of Women’s Health, Mercy Medical Center, Cambodia judynorman@gmail.com Dr. Andrew T. Goldstein, Director, Gynecologic Cancers Research Foundation. drg.cvvd@gmail.com Dominican Republic Margaret M. Madeleine, MPH, PhD Program in Epidemiology, Fred Hutchinson Cancer Center mmadelei@fredhutch.org Yeycy Donastorg, MD Instituto Dermatológico y Cirugía de la Piel “Dr. Huberto Bogaert Díaz”, HIV Vaccine Trials Research Unit, Santo Domingo, Dominican Republic. ydonastorg@gmail.com El Salvador Miriam Cremer MD; Basic Health International, Pittsburgh, PA 15205, USA. Ob/Gyn and Women’s Health Institute, Cleveland Clinic, Cleveland, OH 44195, USA. miriam.cremer@gmail.com Karla Alfaro, MD Basic Health International, El Salvador, kalfaro@basichealth.org Honduras Miriam Cremer MD; Basic Health International, Pittsburgh, PA 15205, USA. Ob/Gyn and Women’s Health Institute, Cleveland Clinic, Cleveland, OH 44195, USA. miriam.cremer@gmail.com Karla Alfaro, MD Basic Health International, El Salvador, kalfaro@basichealth.org . Jaqueline Figueroa, MD, Programa Nacional contra el Cáncer, Tegucigalpa, Honduras. jacqueline_figueroan@yahoo.com Eswatini Eyrun F. Kjetland, MD, PhD, Professor, Departments of Global Health and Infectious Diseases Ullevaal, Centre for imported and Tropical Diseases, Oslo University Hospital Ullevaal, Oslo, Norway; College of Health Sciences, Discipline of Public Health, Nelson Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa;Centre for Bilharzia and Tropical Health Research (non-profit), BRIGHT Academy, Durban, South Africa e.f.kjetland@medisin.uio.no Teresa Norris, Founder and President, HPV Global Action, tnorris@hpvglobalaction.org Zeev Rosberger, PhD, Department of Oncology, Psychology and Psychiatry, McGill University, Montreal, Canada, zeev.rosberger@mcgill.ca Amelie McFadyen, MA, Chief Executive Officer, HPV Global Action, ameliemcfadyen@hpvglobalaction.org Marc Steben, MD, Ecole de Sante Publique, Université de Montréal; International society for STD research, marc@marcsteben.com Malawi Amna Haider, MD, Epidemiologist, Department of Epidemiology and Training, Epicentre, Dubai, UAE, amna.haider@epicentre.msf.org George Kassim Chilinda, MD, Médecins Sans Frontières, Operational Centre Paris, Blantyre, Malawi, gchilinda@gmail.com Henry B.K.Phiri, MD-Sexual and reproductive health department, Ministry of Health, Malawi, henryphiri06@gmail.com Nigeria Ajenifuja Kayode Olusegun, MD, Obafemi Awolowo University Teaching Hospital, Ile-Ife, Osun state Nigeria, ajenifujako@yahoo.com Adepiti Clement Akinfolarin, MD, Obafemi Awolowo University Teaching Hospital, Ile-Ife, Osun state Nigeria, akinfolarindepiti@yahoo.co.uk Adekunbiola Banjo, MD, College of Medicine University of Lagos, Lagos, aafbanjo@cmul.edu.ng Moharson-Bello Imran, MD, College of Medicine, University of Ibadan, Oyo state, Nigeria, imranmorhasonbello@gmail.com Oyinloye Temitope,MD, Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Osun state, Nigeria, projectcoordinator.itoju@gmail.com Bola-Oyebamiji Sekinat, MD, College of Medicine, Osun state University, Osogbo, Osun state. Adeyemo Marydiya, MD, College of Medicine, Osun state University, Osogbo, Osun state Tanzania Karen Yeates-MD, MPH, Department of Medicine, Queen’s University, Kingston, Ontario, Canada, yeatesk@queensu.ca Safina Yuma, MD, Cervical Cancer Focal Person, Ministry of Health, Tanzania, sychande@yahoo.com Bariki Mchome, MD, Head, Reproductive Health Centre, Kilimanjaro Christian Medical Centre, Kilimanjaro, Tanzania, barikimchome@gmail.com

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.348
GPT teacher head0.482
Teacher spread0.134 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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