ArticleBMC gastroenterology2022
Combination of serological biomarkers and clinical features to predict mucosal healing in Crohn's disease: a multicenter cohort study.
Article in BMC gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Tracing the evolving dynamics and research hotspots of spinal cord injury and surgical decompression from 1975 to 2024: a bibliometric analysis.Frontiers in neurology · 2024Pooled it
- A nomogram for predicting small bowel mucosal healing in pediatric Crohn's disease.Frontiers in medicine · 2025Article
- A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis.Journal of translational medicine · 2024Article
- Capsule Endoscopy in Inflammatory Bowel Disease: Panenteric Capsule Endoscopy and Application of Artificial Intelligence.Gut and liver · 2023Article
- Article
- Middle small-bowel segment Lewis score may predict long-term outcomes among patients with quiescent Crohn's disease.Therapeutic advances in gastroenterology · 2023Article
- Predicting Mucosal Healing in Crohn's Disease: A Nomogram Model Developed from a Retrospective Cohort.Journal of inflammation research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeMucosal healing (MH) has become the treatment goal of patients with Crohn's disease (CD). This study aims to develop a noninvasive and reliable clinical tool for individual evaluation of mucosal healing in patients with Crohn's disease.
methodsA multicenter retrospective cohort was established. Clinical and serological variables were collected. Separate risk factors were incorporated into a binary logistic regression model. A primary model and a simple model were established, respectively. The model performance was evaluated with C-index, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy. Internal validation was performed in patients with small intestinal lesions.
resultsA total of 348 consecutive patients diagnosed with CD who underwent endoscopic examination and review after treatment from January 2010 to June 2021 were composed in the derivation cohort, and 112 patients with small intestinal lesions were included in the validation cohort. The following variables were independently associated with the MH and were subsequently included into the primary prediction model: PLR (platelet to lymphocyte ratio), CAR (C-reactive protein to albumin ratio), ESR (erythrocyte sedimentation rate), HBI (Harvey-Bradshaw Index) score and infliximab treatment. The simple model only included factors of PLR, CAR and ESR. The primary model performed better than the simple one in C-index (87.5% vs. 83.0%, p = 0.004). There was no statistical significance between these two models in sensitivity (70.43% vs. 62.61%, p = 0.467), specificity (87.12% vs. 80.69%, p = 0.448), PPV (72.97% vs. 61.54%, p = 0.292), NPV (85.65% vs. 81.39%, p = 0.614), and accuracy (81.61% vs. 74.71%, p = 0.303). The primary model had good calibration and high levels of explained variation and discrimination in validation cohort.
conclusionsThis model can be used to predict MH in post-treatment patients with CD. It can also be used as an indication of endoscopic surveillance to evaluate mucosal healing in patients with CD after treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.