ArticleEuropean journal of clinical nutrition2026
An RFH-NPT-based nomogram for predicting the long-term survival of liver cirrhosis patients: a multicenter study.
Article in European journal of clinical nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05513651 (Establishment of a Model for Predicting the Prognosis of HBV-related Decompensated Liver Cirrhosis Based on RFH-NPT), which is not on this map. Cited by 2 papers.
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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.
Establishment of a Model for Predicting the Prognosis of HBV-related Decompensated Liver Cirrhosis Based on RFH-NPT
Who cites it
2 citing papers in PubMed.
- A Machine Learning-Based Model for Cirrhosis Risk Stratification Incorporating Noninvasive Markers and Clinical Variables.International journal of general medicine · 2026Article
- Real-Life Challenges in Assessing Nutritional Status and Quality of Life in Patients with Cirrhosis.Diagnostics (Basel, Switzerland) · 2025Article
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Authors and funding
23 authors.
Funding
Abstract
BACKGROUND AND
aimsThe Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) identifies nutritional risk in patients with liver disease, an important factor in cirrhosis outcomes. Recognizing the gap in existing prognostic models, which often overlook malnutrition, we developed and validated an RFH-NPT-based model for predicting outcomes of patients with cirrhosis.
methodsThis study included inpatients with cirrhosis from a single center between February and July 2016 (training cohort) and patients from six other medical centers admitted between December 2011 and May 2022 (validation cohort). RFH-NPT assessment was conducted at admission, followed by a 5-year follow-up. A nomogram was created using prognostic variables from Cox modeling, best subset regression (BSR), and least absolute shrinkage and selection operator (LASSO) regression. Its performance was evaluated using various statistical methods and compared with that of existing models such as the Child‒Pugh, MELD, and MELD-Na.
resultsA total of 152 patients were included in the training cohort. The nutritional risk was significantly greater in nonsurvivors (81.1%) than in survivors (46.5%). The nomogram showed better accuracy in predicting 1-, 3-, and 5-year survival than traditional methods. The nomogram's effectiveness was confirmed in the validation cohort of 320 patients.
conclusionThis study re-emphasizes the critical role of malnutrition in patients with liver cirrhosis and establishes an effective RFH-NPT-based model for outcome prediction. CLINICAL
trial registrationThis study is registered at Clinicaltrials.gov (NCT05513651).
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