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  string(690) "Ulcerative colitis (UC) is a chronic inflammatory disease with an increasingly incidence worldwide. Patients with UC have heterogenous prognosis: some patients have good long-term outcomes after initiation treatment, while some will suffer from relapsing and exacerbated disease courses. Therefore, predicting the prognosis of UC patients is important for selecting optimal treatment approaches and conducting personalized management.  Biomarkers are non-invasive, easy-available and promising indicators for assessing disease activity and predicting prognosis in UC. In this project, we will perform post-hot analysis and identify useful biomarkers for predicting long-term outcomes in UC."
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  string(88) "National Natural Science Foundation of China, grant/award number: 82070538 and 81870374."
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  ["property_scientific_abstract"]=>
  string(1524) "Background: Ulcerative colitis (UC) is a chronic inflammatory disease with an increasingly incidence around the world. Patients with UC have heterogenous prognosis which hamper the selection of optimal treatment.

Objective: This study aims at investigating the prognostic value of candidate biomarkers and long-term outcomes in patients with UC.

Study Design: This is a post hoc analysis including three clinical trials (UNIFI, PURSUIT and ACT). Faecal calprotectin and faecal lactoferrin are major predictors. Other biomarkers like C-reactive protein, albumin and haemoglobin are also evelauted. This study will analyse the predictive ability of candidate biomarkers for long term outcomes. 

Participants: Patients who completed an induction study and participate in the maintenance study will be included.

Main Outcome Measure(s): The primary outcome is endoscopic remission at the end of maintenance therapy. Secondary outcomes include endoscopic improvement, histological remission, histological improvement, clinical remission and colectomy. 

Statistical Analysis: Multivariate logistic and cox regression will be used to assess the relationship between candidate biomarkers and the likelihood of achieving long term outcomes, after adjusting for confounders. The receiver operating characteristic analysis is performed to assess the predictive ability of candidate biomarkers. Subgroup analysis by treatment allocation, disease activity at baseline, age and gender will be performed."
  ["project_brief_bg"]=>
  string(1752) "Ulcerative colitis (UC) is a chronic inflammatory disease affecting around 2% of the general population in North America and Western Europe, and its incidence is rising worldwide. [1,2]  Patients with UC have heterogenous prognosis: some patients have good long-term outcomes after initiation treatment, while some will suffer from relapsing and exacerbated disease courses.[3,4]  Therefore, predicting the prognosis of UC patients is important for selecting optimal treatment approaches and conducting personalized management. Nowadays, identifying effective indicators for predicting the prognosis in UC is receiving considerable attention. Biomarkers are non-invasive, easy-available and promising indicators for assessing disease activity and predicting prognosis in UC. [5]  This study aims at identifying useful biomarkers and investigating their predictive ability for long-term outcomes in UC. This analysis will include data from three clinical trials (UNIFI, PURSUIT and ACT1/2). The primary objective of this study is to investigate the relationship between candidate biomarkers and long-term outcomes, such as endoscopic remission, histological remission and colectomy. Multivariate logistic regression or cox regression will be used to assess the relationship between candidate biomarkers and the likelihood of achieving long-term outcomes, after adjusting for confounders. The receiver operating characteristic (ROC) analysis is performed to assess the predictive ability of candidate biomarkers. Subgroup analysis by treatment allocation, disease activity at baseline, age and gender will be performed. The results will explore useful biomarkers and may help in selecting treatment approaches for patients with different prognosis in UC."
  ["project_specific_aims"]=>
  string(429) "This study aims at investigating the association between candidate biomarkers and long-term outcomes, such as endoscopic remission, histological remission and colectomy, in UC patients. Moreover, the ability of candidate biomarkers for predicting long-term outcomes will be analysed. The scientific hypothesis of this study is that biomarker concentration can reflect inflammation condition and indicate long-term outcomes in UC."
  ["project_study_design"]=>
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    ["label"]=>
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      ["label"]=>
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  string(217) "The source of the data will be from UNIFI, PURSUIT (PURSUIT-SC, PURSUIT-IV and PURSUIT-M) and ACT (ACT 1 and ACT 2). Patients who completed an induction study and participate in the maintenance study will be included."
  ["project_main_outcome_measure"]=>
  string(436) "The primary outcome is endoscopic remission at the end of maintenance therapy. Endoscopic remission is a dichotomized variable and defined as mayo endoscopic score equal to 0. Secondary outcomes include endoscopic improvement, histological remission, histological improvement, clinical remission at the end of maintenance therapy. All these outcomes are dichotomized variables. Endoscopic improvement is defined as mayo endoscopic score"
  ["project_main_predictor_indep"]=>
  string(252) "The main predictors of this study include faecal calprotectin and faecal lactoferrin at different time, such as baseline, week 2, 4, end of induction. Concentration of faecal calprotectin and faecal lactoferrin will be analysed as continuous variables."
  ["project_other_variables_interest"]=>
  string(459) "Other variables of interest include potential biomarkers, such as c-reactive protein, albumin, haemoglobin, neutrophils, lymphocytes, platelet and so on, disease activity at baseline, age, gender, treatment allocation, concomitant therapy, disease duration, disease location, disease behaviour, prior biologic exposure. Continuous variables and categorized variables will be described as median (interquartile range) and proportion (percentage), respectively."
  ["project_stat_analysis_plan"]=>
  string(1219) "Continuous and categorical variables are described as median (interquartile range, IQR) and proportion (percentage), respectively. The Mann-Whitney test and ?2 test were performed to evaluate the difference for continuous and categorical variables, respectively. A p-value less than 0.05 was considered as statistical significance. Univariate logistic or cox regression analysis will be conducted to analyse the association of candidate predictors and outcomes. Multivariate logistic or cox regression analysis will be performed to adjusted potential confounders (like disease duration, treatment allocation). The ROC analysis is performed to calculate the area under ROC curve (AUROC). The cut-off value is determined by the Youden index. AUROC, sensitivity, specificity, positive predictive value and negative predictive value are used to assess the predictive capacity of the predictors for predicting specific outcomes. Furthermore, we will perform subgroup analyses by treatment allocation, disease activity at baseline, age and gender. Missing value for major outcome will be excluded from statistical analysis. Missing values for other variables will be imputed by simple imputation, using the mice package in R."
  ["project_timeline"]=>
  string(153) "Start date - December 2022

Analysis completion date - March 2023

Manuscript draft - May 2023

Submitted for publication - August 2023"
  ["project_dissemination_plan"]=>
  string(355) "The products of this project will be submitted to scientific conference, such as Digestive Disease Week, European Crohn?s and Colitis Organization and Asian Crohn?s and Colitis Organization. A manuscript will also be submitted for publication in peer-reviewed journals. The acknowledgement for YODA Project will be presented in all products of this study."
  ["project_bibliography"]=>
  string(1456) "
[1] Ungaro, R., Mehandru, S., Allen, P. B., Peyrin-Biroulet, L., & Colombel, J. F. (2017). Ulcerative colitis. Lancet (London, England), 389(10080), 1756?1770. https://doi.org/10.1016/S0140-6736(16)32126-2

[2] Ng, S. C., Shi, H. Y., Hamidi, N., Underwood, F. E., Tang, W., Benchimol, E. I., Panaccione, R., Ghosh, S., Wu, J., Chan, F., Sung, J., & Kaplan, G. G. (2017). Worldwide incidence and prevalence of inflammatory bowel disease in the 21st century: a systematic review of population-based studies. Lancet (London, England), 390(10114), 2769?2778. https://doi.org/10.1016/S0140-6736(17)32448-0

[3] Verstockt, B., Bressler, B., Martinez-Lozano, H., McGovern, D., & Silverberg, M. S. (2022). Time to Revisit Disease Classification in Inflammatory Bowel Disease: Is the Current Classification of Inflammatory Bowel Disease Good Enough for Optimal Clinical Management?. Gastroenterology, 162(5), 1370?1382. https://doi.org/10.1053/j.gastro.2021.12.246

[4] Kobayashi, T., Siegmund, B., Le Berre, C., Wei, S. C., Ferrante, M., Shen, B., Bernstein, C. N., Danese, S., Peyrin-Biroulet, L., & Hibi, T. (2020). Ulcerative colitis. Nature reviews. Disease primers, 6(1), 74. https://doi.org/10.1038/s41572-020-0205-x

[5] Liu, D., Saikam, V., Skrada, K. A., Merlin, D., & Iyer, S. S. (2022). Inflammatory bowel disease biomarkers. Medicinal research reviews, 42(5), 1856?1887. https://doi.org/10.1002/med.21893
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pi country
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pi affil
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products
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res
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}