PTH-070 A Multinational Study to Determine Indicators of Suboptimal Therapy Among Ulcerative Colitis Patients Treated with Tumour Necrosis Factor Antagonists
Bibliographic record
Abstract
Introduction Ulcerative colitis (UC) patients treated with tumour necrosis factor antagonists (anti-TNFs) may require therapy changes over time, which may be considered as indicators of suboptimal therapy. Methods A multinational, multicentre, retrospective, chart review study was conducted to assess the indicators of suboptimal therapy among adult UC patients receiving their first anti-TNF [infliximab (IFX) or adalimumab (ADA)] between June 2009 and June 2013 (index therapy). The indicators of suboptimal therapy during 2 year follow up included: anti-TNF dose-escalation (assessed >4 months after index to allow for initial dose adjustments), augmentation with non-biologic therapy, UC-related surgery, discontinuation of first anti-TNF and switching to second anti-TNF. Dose escalation was defined as any increase in dose and/or frequency of the index anti-TNF agent(s). Augmentation was defined as starting a new non-biologic drug or increase in dose/frequency of the concurrent non-biological drugs with anti-TNF therapy. Discontinuation of index anti-TNF was based on entry in patients’ charts and excluded patients who discontinued anti-TNF despite it being effective during the follow-up period. Switch was defined as a subset of discontinuation patients who initiated another anti-TNF therapy over the follow-up period. The number and percentage of patients with each indicator and ≥1 indicator was summarised descriptively by country. Results The study included 538 UC patients with mean age (SD) of 42 (14) years. Forty-seven percent of patients were females and 73% reported moderate to severe UC at index. The percentages of patients on IFX and ADA as first anti-TNF were 92% and 8%, respectively. Overall, within 2 years, 61% of UC patients had ≥1 indicator of suboptimal therapy, 26% had anti-TNF dose escalation, 21% needed augmentation with non-biologic therapy, 9% underwent UC-related surgery and 29% discontinued their index anti-TNF. Of those who discontinued index anti-TNF (N = 156), 58% switched to another anti-TNF therapy. Conclusion In this large multinational cohort, more than 60% of UC patients had ≥1 indicator of suboptimal anti-TNF therapy. Predominant indicators included dose escalation and discontinuation of anti-TNF therapy. Disclosure of Interest J. Lindsay Grant/research support from: MSD, Abbvie, Hospira, Takeda, Janssen, Ferring, Shire Pharmaceuticals, Vifor Pharma, Atlantic Health care, Actavis (Warner Chilcott), and Tillotts, Consultant for: MSD, Abbvie, Hospira, Takeda, Janssen, Ferring, Shire Pharmaceuticals, Vifor Pharma, Atlantic Health care, Actavis (Warner Chilcott), and Tillotts, Speaker bureau with: MSD, Abbvie, Hospira, Takeda, Janssen, Ferring, Shire Pharmaceuticals, Vifor Pharma, Atlantic Health care, Actavis (Warner Chilcott), and Tillotts, J. Gisbert Grant/research support from: MSD, Abbvie, Hospira, Kern Pharma, Takeda, Janssen, Pfizer, Ferring, Faes Farma, Shire Pharmaceuticals, Dr. Falk Pharma, Chiesi, Casen Fleet, Gebro Pharma, Otsuka Pharmaceutical, Vifor Pharma, Consultant for: MSD, Abbvie, Hospira, Kern Pharma, Takeda, Janssen, Pfizer, Ferring, Faes Farma, Shire Pharmaceuticals, Dr. Falk Pharma, Chiesi, Casen Fleet, Gebro Pharma, Otsuka Pharmaceutical, Vifor Pharma, Speaker bureau with: MSD, Abbvie, Hospira, Kern Pharma, Takeda, Janssen, Pfizer, Ferring, Faes Farma, Shire Pharmaceuticals, Dr. Falk Pharma, Chiesi, Casen Fleet, Gebro Pharma, Otsuka Pharmaceutical, Vifor Pharma, R. Mody Employee of: Takeda Pharmaceuticals International, Inc, L. Peyrin-Biroulet Consultant for: Abbvie, MSD, Jansse, Takeda, Hospira, Celltrion, Biogaran, Speaker bureau with: Abbvie, MSD, Janssen, Takeda, Mitsubishi, A. Armuzzi Grant/research support from: MSD, Consultant for: Abbvie, Hospira, Liily, MSD, Mundipharma, Pfizer, Sofar, Takeda, Speaker bureau with: Abbvie, Astra-Zeneca, Chiesi, Ferring, Hospira, MSD, Otsuka, Takeda, Zambon, B. Bokemeyer Grant/research support from: Abbvie, Ferring, UCB, Consultant for: Abbvie, MSD, Shire, Ferring, UCB, Hospira, Takeda, Movetis, Speaker bureau with: Abbvie, Ferring, MSD, Merckle, Falk, HLR, UCB, G. Nguyen Consultant for: Janssen and Abbvie, J. Siebenaler Conflict with: Employee of Mapi, a company hired to conduct the study by Takeda Pharmaceuticals International, Inc., Ö. Åkerborg Conflict with: Employee of Mapi, a company hired to conduct the study by Takeda Pharmaceuticals International, Inc., M. Smyth Employee of: Takeda Development Centre Europe Ltd, London, UK
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".