Systematic review: impact of non‐adherence to 5‐aminosalicylic acid products on the frequency and cost of ulcerative colitis flares
Bibliographic record
Abstract
BACKGROUND: Ulcerative colitis (UC) can be maintained in remission with 5-aminosalicylic acid (5-ASA) medications, but frequent non-adherence by patients who are feeling well has been associated with more frequent flares of colitis. AIM: To perform a systematic review of the published literature and unpublished randomized clinical trials (RCTs) regarding the impact of non-adherence with 5-ASA medications on the incidence of UC flares and costs of care. METHODS: A search of MEDLINE, EMBASE and the Cochrane databases was performed. Prospective studies of UC maintenance with 5-ASAs in adults were selected if they included data on adherence and disease flares. Studies using insurance claims data to estimate the impact of non-adherence on cost of care were included. Data from unpublished RCTs were obtained from the FDA with a request under the Freedom of Information Act. RESULTS: The relative risk for flare in non-adherent vs. adherent patients ranged from 3.65 to infinity. Data were obtained from six unpublished 5-ASA RCTs, but none measured the impact of adherence on disease activity. The comorbidity-adjusted annual costs of care in adherent patients were 12.5% less than in non-adherent patients, despite increased medication expenditures. CONCLUSIONS: A substantial proportion of UC flares and medical costs of UC are attributable to 5-ASA non-adherence. As non-adherence to 5-ASA medications is common, cost-effective strategies to improve adherence are needed. The impact of adherence on disease activity should be measured in RCTs of all inflammatory bowel disease treatments.
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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 | 0.009 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".