Editorial: a clinical decision tool to identify patients who might benefit most from intensified dosing in the biological era—getting nearer? Authors' reply

Dulai, Parambir S.

doi:10.1111/apt.15671

Cited by 6 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lower Harvey-Bradshaw Index (HBI) baseline values, female sex and UST trough levels were predictors [29][30][31][32]. Dulai et al [33] created the UST clinical decision support tool (UST-CDST), which was derived from a post hoc analysis of UNITI trials. Using real-world data, the UST-CDST has demonstrated effectiveness in predicting clinical remission and relapse of UST in patients with moderate to severe CD [34].…”

Section: Discussionmentioning

confidence: 99%

Intestinal mRNA expression profiles associated with mucosal healing in ustekinumab-treated Crohn's disease patients: bioinformatics analysis and prospective cohort validation

Li,

Huang,

Yang

et al. 2024

J Transl Med

View full text Add to dashboard Cite

Background Variations exist in the response of patients with Crohn’s disease (CD) to ustekinumab (UST) treatment, but the underlying cause remains unknown. Our objective was to investigate the involvement of immune cells and identify potential biomarkers that could predict the response to interleukin (IL) 12/23 inhibitors in patients with CD. Methods The GSE207022 dataset, which consisted of 54 non-responders and 9 responders to UST in a CD cohort, was analyzed. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the most powerful hub genes. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performances of these genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to estimate the proportions of immune cell types. These significantly altered genes were subjected to cluster analysis into immune cell-related infiltration. To validate the reliability of the candidates, patients prescribed UST as a first-line biologic in a prospective cohort were included as an independent validation dataset. Results A total of 99 DEGs were identified in the integrated dataset. GO and KEGG analyses revealed significant enrichment of immune response pathways in patients with CD. Thirteen genes (SOCS3, CD55, KDM5D, IGFBP5, LCN2, SLC15A1, XPNPEP2, HLA-DQA2, HMGCS2, DDX3Y, ITGB2, CDKN2B and HLA-DQA1), which were primarily associated with the response versus nonresponse patients, were identified and included in the LASSO analysis. These genes accurately predicted treatment response, with an area under the curve (AUC) of 0.938. T helper cell type 1 (Th1) cell polarization was comparatively strong in nonresponse individuals. Positive connections were observed between Th1 cells and the LCN2 and KDM5D genes. Furthermore, we employed an independent validation dataset and early experimental verification to validate the LCN2 and KDM5D genes as effective predictive markers. Conclusions Th1 cell polarization is an important cause of nonresponse to UST therapy in patients with CD. LCN2 and KDM5D can be used as predictive markers to effectively identify nonresponse patients. Trial registration: Trial registration number: NCT05542459; Date of registration: 2022-09-14; URL: https://www.clinicaltrials.gov.

show abstract

Section: Discussionmentioning

confidence: 99%

Intestinal mRNA expression profiles associated with mucosal healing in ustekinumab-treated Crohn's disease patients: bioinformatics analysis and prospective cohort validation

Li,

Huang,

Yang

et al. 2024

J Transl Med

View full text Add to dashboard Cite

show abstract

“…10 Other tools have been developed for ustekinumab in Crohn's disease, 11 and recently, it has been demonstrated that the ustekinumab and vedolizumab tools for Crohn's disease are indeed drug specific and allow for discrimination of an individual patient for choosing between these agents. 12 The capacity to include patient specific data (smoking status, C-reactive protein results, etc. ), allows modeling to be tailored to the patient and therefore brings forward CER into a new era of personalization.…”

mentioning

confidence: 99%

The current state of comparative effectiveness research in inflammatory bowel disease

Dulai

2021

J of Gastro and Hepatol

Self Cite

View full text Add to dashboard Cite

Clinical Decision Support Tool for Infliximab in Crohn’s Disease

Dulai

Wong

Reinisch

et al. 2022

Clinical Gastroenterology and Hepatology

View full text Add to dashboard Cite

Editorial: a clinical decision tool to identify patients who might benefit most from intensified dosing in the biological era—getting nearer? Authors' reply

Abstract: LINKED CONTENTThis article is linked to Dulai et al and Verstockt and Ferrante papers. To view these articles, visit https://doi.org/10.1111/apt.15609 and https://doi.org/10.1111/apt.15634.

Cited by 6 publications

References 5 publications

Intestinal mRNA expression profiles associated with mucosal healing in ustekinumab-treated Crohn's disease patients: bioinformatics analysis and prospective cohort validation

Intestinal mRNA expression profiles associated with mucosal healing in ustekinumab-treated Crohn's disease patients: bioinformatics analysis and prospective cohort validation

The current state of comparative effectiveness research in inflammatory bowel disease

Clinical Decision Support Tool for Infliximab in Crohn’s Disease

Contact Info

Product

Resources

About