ArticleNPJ digital medicine2025
From trial data to personalized medicine: a validated framework with an application to Crohn's disease.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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
5 citing papers in PubMed.
- Explainable AI reveals squamous histology and U-shaped PD-L1 patterns as primary subgroup predictors of neoadjuvant and perioperative immunotherapy benefit in NSCLC: a machine learning analysis.Cancer immunology, immunotherapy : CII · 2026Article
- Mesenteric adipose tissue: from protective gatekeeper to driver of inflammatory bowel disease.Immunometabolism (Cobham, Surrey) · 2026Review
- Editorial: Model-informed approaches: uniting drug development with personalized medicine.Frontiers in pharmacology · 2026Article
- Reprogramming microglia in sepsis-associated encephalopathy: from pathological dysfunction to therapeutic restoration.Frontiers in immunology · 2026Review
- Research progress in molecular targeted therapy for inflammatory bowel disease.Journal of translational medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Clinical practice is currently guided by studies that average over patient outcomes. This may not be the best approach, as different patients may have different treatment responses. Here we extend a method for simulating clinical trials to identify optimal treatments for each patient, and we illustrate this approach in the context of Crohn's disease. Using the data from 15 randomized trials (N = 5703), we used statistical hypothesis testing to identify seven subgroups with distinct responses to three different drug classes. The largest subgroup consisted of patients with equivocal responses to all drug classes, whereas the second largest showed superiority with anti-TNFs. We also identified a subgroup of women over 50 with superior responses to anti-IL-12/23s. Interestingly, this group appeared under-represented in the trials (2%) compared to patients at the University of California (25%). Overall, these results underscore the importance of studying personalized medicine, demonstrate the value of clinical trial data, and provide a roadmap for applying this method broadly across diseases. These results also highlight the importance of diverse and representative recruitment into clinical trials.
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.