Development of the Escalation of Therapy or Intervention (ETI) Calculator for Patients with Ulcerative Colitis Using ePROMs

Abstract Background and Aims Digital collection of patient-reported outcome measures [PROMs] is largely unexplored as a basis for follow-up for patients with ulcerative colitis [UC]. Our aim was to develop a model to predict the likelihood of escalation of therapy or intervention at an outpatient ap...

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Veröffentlicht in:Journal of Crohn's and colitis 2023-11, Vol.17 (11), p.1744-1751
Hauptverfasser: Matini, Lawrence, Chapman, Thomas P, Kantschuster, Ramona, Wilson, Jean, Tarafdar, Adib, Hussain, Moheez, Song, Kaiyang, Simadibrata, Daniel M, Seeva, Pavetha, White, Lydia, Slater, Jessica, Kormilitzin, Andrey, Collins, Gary, Travis, Simon P L, Walsh, Alissa
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Sprache:eng
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Zusammenfassung:Abstract Background and Aims Digital collection of patient-reported outcome measures [PROMs] is largely unexplored as a basis for follow-up for patients with ulcerative colitis [UC]. Our aim was to develop a model to predict the likelihood of escalation of therapy or intervention at an outpatient appointment that may be used to rationalize follow-up. Methods TrueColours-IBD is a web-based, real-time, remote monitoring software that allows longitudinal collection of ePROMs. Data for prediction modelling were derived from a Development Cohort, guided by the TRIPOD statement. Logistic regression modelling used ten candidate items to predict escalation of therapy or intervention. An Escalation of Therapy or Intervention [ETI] calculator was developed, and applied in a Validation Cohort at the same centre. Results The Development Cohort [n = 66] was recruited in 2016 and followed for 6 months [208 appointments]. From ten items, four significant predictors of ETI were identified: SCCAI, IBD Control-8, faecal calprotectin, and platelets. For practicality, a model with only SCCAI and IBD Control-8, both entered remotely by the patient, without the need for faecal calprotectin or blood tests was selected. Between 2018 and 2020, a Validation Cohort of 538 patients [1188 appointments] was examined. A 5% threshold on the ETI calculator correctly identified 343/388 [88%] escalations and 274/484 [57%] non-escalations. Conclusions A calculator based on digital, patient-entered data on symptoms and quality of life can predict whether a patient with UC requires escalation of therapy or intervention at an outpatient appointment. This may be used to streamline outpatient appointments for patients with UC.
ISSN:1873-9946
1876-4479
DOI:10.1093/ecco-jcc/jjad099