P485 Prediction Model Incorporating Pharmacokinetics Calculates Probability of Endoscopic Healing in Patients with ulcerative colitis Starting Infliximab Therapy
Bibliographic record
Abstract
Infliximab (IFX) is effective treatment for moderate to severe ulcerative colitis (UC), however baseline parameters associated with, and probability of achieving endoscopic healing during induction and maintenance therapy are unknown. Data from the ACT-1 and -2 trials encompassing 484 IFX-treated UC patients were analysed. A two-compartment population pharmacokinetic model was used to calculate baseline IFX clearance (CL). The Mayo endoscopic score was available at Weeks (W) 0, 8 and 30. Three logistic regression prediction models were developed using the ACT-1 dataset and externally validated using the ACT-2 dataset. The models evaluated W0 variables for prediction of endoscopic healing (MES ≤ 1) at W8 and W30, and W8 variables for prediction of endoscopic healing at W30. An online tool to calculate the probability of achieving endoscopic healing in individual patients was also created. IFX CL, stool frequency, and rectal bleeding at W0 were independently associated with endoscopic healing at W8 with an area under the curve (AUC [95% confidence interval]) of 0.73 (0.66–0.79) and 0.67 (0.60–0.74) for the derivation and validation models, respectively. IFX CL, stool frequency, white blood cell count, and weight at W0 were independently associated with achieving endoscopic healing at W30 with an AUC of 0.68 (0.62–0.75) and 0.67 (0.61–0.74) for the derivation and validation models, respectively. Rectal bleeding, stool frequency, white blood cell count, and albumin at W8 were independently associated with achieving endoscopic healing at W30 with an AUC of 0.83 (0.78–0.89) and 0.78 (0.72–0.84), for the derivation and validation models, respectively. Odds ratios for the factors predictive of endoscopic healing are shown in Table 1. Table 1. Odds ratios for W0 and W8 factors predictive of endoscopic healing in patients receiving IFX. Variable selection was based on univariable selection (p < 0.15) followed by a forward stepwise multi-variable logistic regression model (p < 0.1). Patient-level probabilities for endoscopic healing at W8 and/or W30 can be calculated using a free online tool available at http://premedibd.com. The predicted probability of endoscopic healing at W8 for a hypothetical UC patient starting IFX therapy using the online tool is shown in Figure 1. Figure 1. Probability of W8 endoscopic healing in a hypothetical UC patient. A population pharmacokinetic model uses sex and albumin to calculate W0 IFX CL, which is incorporated into the prediction model with stool frequency and rectal bleeding. Three models were developed and externally validated to calculate the probability of endoscopic healing in individual patients with UC during IFX induction and/or maintenance therapy based on IFX CL, patient demographics and disease activity measures at W0 and/or W8.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".