Systematic Literature Review of Real-World Evidence on Dose Escalation and Treatment Switching in Ulcerative Colitis
Bibliographic record
Abstract
Harpreet Singh,1 Liam Wilson,2 Tom Tencer,3 Jinender Kumar3 1Health Economics & Market Access (HEMA), Amaris Consulting Ltd, Toronto, ON, Canada; 2Health Economics & Market Access (HEMA), Amaris Consulting Ltd, Shanghai, People’s Republic of China; 3Bristol Myers Squibb, Princeton, NJ, USACorrespondence: Jinender Kumar, Global HEOR, Bristol Myers Squibb, 100 Nassau Park Blvd #300, Princeton, NJ, 08540, USA, Tel +1-609-302-7630, Email Jinender.Kumar@bms.comBackground: Currently approved biologic therapies for moderate-to-severe ulcerative colitis have well-established efficacy. However, many patients fail to respond or lose response, leading to dose escalation or treatment switching.Objective: We sought to identify real-world evidence on dose escalation and treatment switching and associated clinical and economic outcomes among adults with ulcerative colitis treated with infliximab, adalimumab, golimumab, vedolizumab, ustekinumab, or tofacitinib.Methods: We conducted a systematic search of Embase, MEDLINE (up to 26 August 2020), and conference proceedings (2017− 2020) for studies in adults with ulcerative colitis to assess clinical response and remission, colectomy, adverse events, and economic outcomes related to dose escalation and treatment switching.Results: In 56 studies, dose escalation and treatment switching involving infliximab and/or adalimumab were most frequently investigated. Rates of clinical response after dose escalation were 20– 95% (1.8– 36 months), clinical remission rates were 10– 94% (1.8– 36 months), colectomy rates were 0– 33% (12– 38 months), and adverse event rates were 0– 18%. Treatment switching rates in 21 studies were 4– 70% over 3– 62 months, with switch due to loss of response rates of 4– 35% over 12– 62 months (7 studies). Up to 35% of patients underwent colectomy 12− 120 weeks after switching, and 13– 38% experienced adverse events. Data relating to economic outcomes were limited to tumor necrosis factor inhibitors, but demonstrated increased direct costs associated with both dose escalation and treatment switching.Conclusion: Dose escalation and treatment switching are common with existing therapies. However, clinical response and remission rates vary, and a proportion of patients fail to achieve optimal clinical and economic outcomes. This highlights the need for more efficacious and durable treatments for patients with moderate-to-severe ulcerative colitis.Keywords: ulcerative colitis, real-world evidence, systematic literature review, biologic therapies, tofacitinib
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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 | 0.018 | 0.082 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".