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      string(258) "NCT02407236 - A Phase 3, Randomized, Double-blind, Placebo-controlled, Parallel-group, Multicenter Protocol to Evaluate the Safety and Efficacy of Ustekinumab Induction and Maintenance Therapy in Subjects With Moderately to Severely Active Ulcerative Colitis"
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  string(143) "External Validation of novel Endo-Histo AI fusion model for predicting histologic remission and early response to therapy in Ulcerative Colitis"
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  string(688) "Accurate disease assessment is crucial for managing ulcerative colitis and determining treatment response in clinical trials. Endoscopic and histological scores are complex and burdened by interobserver variability. This study aims to validate our new AI model that integrates endoscopic and histological data to objectively and accurately assess activity and predict treatment response in UC. Furthermore, it aims to validate our AI model to detect and localise neutrophils, determining a cutoff to define histological remission and predict treatment response. The model could potentially replace central readout through standardized UC assessment and improve clinical trial development."
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    string(94) "APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, Ireland"
    ["email"]=>
    string(17) "iacuccim@yahoo.it"
    ["state_or_province"]=>
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    ["country"]=>
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      ["p_pers_pr_affil"]=>
      string(136) "Instituto Universitario de Investigacion e Innovacion en Bioingenieria, HUMAN-tech, Universitat Politecnica de Valencia, Valencia, Spain"
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    ["label"]=>
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  ["project_funding_source"]=>
  string(40) "Start up funds of Prof. Marietta Iacucci"
  ["project_date_type"]=>
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  ["property_scientific_abstract"]=>
  string(1634) "Background: Achieving mucosal healing is a long-term target in UC. Thus, objective disease assessment is crucial, especially when evaluating treatment response in clinical trials. We recently developed AI models that integrate endoscopic and histological data and detect, localize and quantify neutrophils to assess activity and predict treatment response. The models were developed and tested on data from a phase II trial of mirikizumab in UC, showing promising results. 

Objective: Validate our AI models’ performance on an external cohort from a phase III trial on efficacy and safety of Ustekinumab as induction and maintenance treatment in UC. 

Study design: retrieve endoscopy videos and WSI from W0, W8 and W52, as well as demographic and treatment information. 

Participants: patients enrolled in this phase III trial with demographic, endoscopic and histological data available at W0, W8 and W52.

Primary outcome: assess the models’ ability to determine disease activity through validated scores combining endoscopic and histological data or based on automated neutrophil cutoff.

Secondary outcome: assess the models’ ability to predict treatment response as histological improvement and remission through validated scores. 

Statistical analysis: diagnostic performance of the model will be reported as sensitivity, specificity, PPV, NPV, accuracy and F1 score. Inter-rater agreement between the model and central readout will be evaluated through Cohen’s Kappa. Neutrophils cutoff to assess UC activity and predict treatment response will be determined by the Youden Index."
  ["project_brief_bg"]=>
  string(3047) "Accurately assessing endoscopic and histological activity is critical for guiding disease management in Ulcerative Colitis (UC)(1). Precise evaluation informs clinical decision-making and ensures objective assessment of treatment response in clinical trials (2). Endoscopic and histologic scoring systems to evaluate disease activity are often complex and burdened by interobserver variability, highlighting the need for standardised evaluation(3,4). Currently, clinical trials often mitigate interobserver variability through central readouts performed by experts. While this approach helps achieve greater consistency, it is expensive and still subject to variability. Moreover, neutrophils are considered the key cells to determine histological remission (3). Indeed, the recently developed PICaSSO Histological Remission Index (PHRI) focused only on neutrophils and showed a good ability to assess disease activity and predict outcomes (5). However, the potential role of number and localisation of neutrophils (epithelial and lamina propria) in defining the disease remission is still unexplored. 

Several AI models have been developed to assess disease activity based on validated scores or evaluating specific cellular features (6). Recently, starting from data from the phase II trial on efficacy and safety of mirikizumab in UC, we developed an innovative AI model based on a foundational framework that integrates endoscopic and histological data. The new fusion model outperformed single-modality assessments to assess histologic remission, achieving a sensitivity of 89.72% (95% CI 82.35–94.76), specificity of 89.67% (95% CI 84.34–93.67), and accuracy of 89.69% (95% CI 85.61–92.94). It demonstrated remarkable performance in assessing response to therapy, achieving a sensitivity of 97.96% (95% CI 89.15–99.95), specificity of 86.84% (95% CI 71.91–95.59) and accuracy of 93.10% (95% CI 85.59–97.43) for predicting histologic remission at week 52.  

Furthermore, we recently developed a novel AI-driven model to standardize the detection, localization, and quantification of neutrophils, supporting objective evaluations of histological activity and enabling prediction of early therapy response predictions in the same Phase 2 Clinical trial UC cohort. Our new model showed remarkable ability to localize (DICE score 67.6%) and detect (F1 score 72%) neutrophils. We identified optimal neutrophil density cutoffs (cells/mm²) to indicate disease activity and response to therapy.

Validating these AI-driven algorithms in external clinical trial cohorts of UC patients could further standardize and optimize disease assessment in UC. This approach would reduce interobserver variability and improve the precision of treatment allocation in clinical trials, reduce the costs related to expert central readout and advance disease evaluation overall. Ultimately, this work has the potential to enhance clinical trial outcomes and support more tailored, evidence-based treatment strategies for UC patients."
  ["project_specific_aims"]=>
  string(1313) "The aim is to validate in an external clinical trial UC cohort the endo-histo fusion model, and the automated neutrophil detection and localization recently developed on a phase II UC trial  by assessing their performance on data from the phase III trial on efficacy and safety of Ustekinumab as induction and maintenance treatment in UC.  We plan to retrieve endoscopic videos and whole-slide histology images from W0, W8 and W52 of the trial. We would like to retrieve data on endoscopic activity evaluated by Mayo Endoscopic Score (MES) and Ulcerative Colitis Endoscopic Index of Severity (UCEIS), as well as histological activity evaluated by Geboes score. Moreover, we would like to retrieve demographic data (country, year of birth, age, sex, BMI, smoking status, race, year of diagnosis), clinical information (Partial Mayo score, IBDQ score [total and single items], laboratory data (fecal calprotectin, CRP) and treatment information (prior biologic exposure, current use of steroids/mesalamine/thiopurines). We aim to assess the model's performance to accurately assess disease activity and remission according to established endoscopic scores and histological scores, such as the Geboes(7) and PHRI(5). Moreover, we aim to evaluate the model's ability to predict response to Ustekinumab



"
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    ["label"]=>
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  ["project_purposes"]=>
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      ["label"]=>
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  string(1216) "Inclusion and exclusion criteria will be the ones considered by the trial. Patients enrolled in this phase III trial with available demographic data, endoscopy videos and histological WSIs at W0, W8 and W52 will be included. Namely, adults with moderate-severe UC (Mayo score 6-12 and MES >=2 at W0) with failure/intolerance to conventional treatment, regardless of prior biologic use. Excluded patients will be the ones without demographic, endoscopic and histological features at the predefined time-points, as well as the ones excluded according to trial criteria.

Endoscopic videos and histological WSI at W0, W8 and W52 will be used. Data on disease activity assessed through MES and UCEIS and histological activity assessed by Geboes will be retrieved, as well as single items of each score.

Moreover, demographic characteristics (country, year of birth, age, sex, weight, height, smoking status, race, year of UC diagnosis), clinical information (PMS, IBDQ score [total+single items - bowel symptoms;systemic symptoms;emotional function;social function]), laboratory data (FC, CRP) and treatment information (prior biologic exposure; use of steroids/mesalamine/thiopurines) will be retrieved."
  ["project_main_outcome_measure"]=>
  string(1020) "The primary outcome is to assess the AI foundational fusion and neutrophil detection/localization algorithms’ ability in assessing disease activity trough validated score combining endoscopic and histological data. 

Endoscopic activity will be evaluated through MES and UCEIS, and endoscopic remission will be defined as MES 0 and UCEIS <=1.

Histological activity will be evaluated through Geboes score and PHRI, and histological remission will be defined as Geboes <=2B.0 and PHRI 0.

The secondary outcome is to assess their ability in detecting, localizing and quantifying neutrophils to evaluate disease activity and remission and predict response to therapy in terms of histological improvement and remission through validated histological scores (Geboes and PHRI). Histological activity will be evaluated through Geboes score and PHRI, and histological remission will be defined as Geboes <=2B.0 and PHRI 0. Histological improvement will be defined as Geboes <3.1 and PHRI <=1."
  ["project_main_predictor_indep"]=>
  string(340) "The main predictors of the study include endoscopic and histologic disease severity at baseline and W8-52. Endoscopic remission will be defined as MES 0 and UCES <= 1, while 

histological remission will be defined as Geboes <=2B.0 and PHRI 0. Histological improvement will be defined as Geboes <3.1 and PHRI <= 1.

"
  ["project_other_variables_interest"]=>
  string(568) "Other variables such as age, sex, body mass index (BMI), smoking status, disease location, disease duration, partial Mayo score, IBDQ score (total and items), fecal calprotectin, C-reactive protein, treatment allocation, prior biologic exposure, concomitant treatments (immunomodulators, steroids or mesalamine), will be used for descriptive statistics to describe the study population. Continuous variables will be represented as means/standard deviations (or medians/interquartile ranges) and categorical variables will be represented as proportions and percentages."
  ["project_stat_analysis_plan"]=>
  string(1100) "The foundational model previously developed will be applied in the new cohort of data.

The diagnostic performance of the AI-enabled Endo-Histo fusion model will be reported as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and F1 score. The 95% confidence intervals (CIs) for each metric will be calculated.

Inter-rater agreement between the AI model and central readout in assessing histological remission and response to therapy at weeks 8 and 52 will be calculated according to Cohen’s Kappa (K). Results will be presented as K coefficient, 95% confidence interval and p-values. K values above 0.41 signify moderate agreement, K values higher than 0.61 correspond to substantial agreement, and values above 0.81 represent almost perfect agreement, according to Landis and Koch’s criteria. A p-value <0.05 will be considered statistically significant. Optimal cell density cut-offs for neutrophils will be determined by the Youden Index to assess disease activity and to predict early response to therapy at weeks 8 and 52."
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  string(176) "Start date – February  2025

Analysis completion date – March  2025

Manuscript draft – April 2025

Submitted for publication – April/May 2025

"
  ["project_dissemination_plan"]=>
  string(384) "Results arising from this study may be presented as abstracts and papers to target audiences. These may be submitted to relevant conferences such as European Crohn’s Colitis Organization (ECCO) and Digestive Disease Week. A manuscript may also be submitted for publication. The YODA Project will be acknowledged in all study products, which will be shared at the time of submission."
  ["project_bibliography"]=>
  string(2089) "

Turner D, Ricciuto A, Lewis A, D’Amico F, Dhaliwal J, Griffiths AM, et al. STRIDE-II: An Update on the Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE) Initiative of the International Organization for the Study of IBD (IOIBD): Determining Therapeutic Goals for Treat-to-Target strategies in IBD. Gastroenterology. 2021 Apr;160(5):1570–83.
Adamina M, Feakins R, Iacucci M, Spinelli A, Cannatelli R, D’Hoore A, et al. ECCO Topical Review Optimising Reporting in Surgery, Endoscopy, and Histopathology. J Crohns Colitis [Internet]. 2021 Jul 5;15(7):1089–105. Available from: https://academic.oup.com/ecco-jcc/article/15/7/1089/6081305
Magro F, Doherty G, Peyrin-Biroulet L, Svrcek M, Borralho P, Walsh A, et al. ECCO Position Paper: Harmonization of the Approach to Ulcerative Colitis Histopathology. J Crohns Colitis. 2020 Nov 7;14(11):1503–11.
Feakins R, Borralho Nunes P, Driessen A, Gordon IO, Zidar N, Baldin P, et al. Definitions of Histological Abnormalities in Inflammatory Bowel Disease: an ECCO Position Paper. J Crohns Colitis [Internet]. 2024 Feb 26;18(2):175–91. Available from: https://academic.oup.com/ecco-jcc/article/18/2/175/7247579
Gui X, Bazarova A, del Amor R, Vieth M, de Hertogh G, Villanacci V, et al. PICaSSO Histologic Remission Index (PHRI) in ulcerative colitis: development of a novel simplified histological score for monitoring mucosal healing and predicting clinical outcomes and its applicability in an artificial intelligence system. Gut. 2022 May;71(5):889–98.
Iacucci M, Santacroce G, Zammarchi I, Maeda Y, Del Amor R, Meseguer P, et al. Artificial intelligence and endo-histo-omics: new dimensions of precision endoscopy and histology in inflammatory bowel disease. Lancet Gastroenterol Hepatol [Internet]. 2024 May; Available from: https://linkinghub.elsevier.com/retrieve/pii/S2468125324000530
Geboes K. A reproducible grading scale for histological assessment of inflammation in ulcerative colitis. Gut. 2000 Sep 1;47(3):404–9.

 
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    string(80) "https://yoda.yale.edu/data-request/2024-1060/yoda-project-review-2024-1060_site/"
    ["alt"]=>
    string(0) ""
    ["author"]=>
    string(4) "1885"
    ["description"]=>
    string(0) ""
    ["caption"]=>
    string(0) ""
    ["name"]=>
    string(34) "yoda-project-review-2024-1060_site"
    ["status"]=>
    string(7) "inherit"
    ["uploaded_to"]=>
    int(16292)
    ["date"]=>
    string(19) "2025-03-19 15:04:42"
    ["modified"]=>
    string(19) "2025-03-19 15:04:42"
    ["menu_order"]=>
    int(0)
    ["mime_type"]=>
    string(15) "application/pdf"
    ["type"]=>
    string(11) "application"
    ["subtype"]=>
    string(3) "pdf"
    ["icon"]=>
    string(62) "https://yoda.yale.edu/wp/wp-includes/images/media/document.png"
  }
  ["project_highlight_button"]=>
  string(0) ""
  ["request_overridden_res"]=>
  string(1) "3"
}
data partner
array(1) {
  [0]=>
  string(15) "johnson-johnson"
}


pi country
array(0) {
}


pi affil
array(0) {
}


products
array(1) {
  [0]=>
  string(7) "stelara"
}


num of trials
array(1) {
  [0]=>
  string(1) "1"
}


res
array(1) {
  [0]=>
  string(1) "3"
}