ArticleFrontiers in nutrition2025
The impact of cachexia index combined with BMI trajectory on survival outcomes in patients with cancer cachexia.
Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Early Identification and Prognostic Stratification of Cancer Cachexia Using Explainable Machine Learning: A Multicentre Cohort Study.Journal of cachexia, sarcopenia and muscle · 2026Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The cachexia index (CXI) has emerged as a recognized prognostic biomarker of cancer cachexia. However, the dynamic progression of cachexia may not be fully captured by a single assessment. This study examined the impact of integrating the CXI with BMI trajectories on the survival prognosis of patients with cancer cachexia to enable early identification of high-risk populations. Methods: This is a retrospective review of clinical and pathological data from 147 patients diagnosed with cancer cachexia at Xuzhou Central Hospital between January 2019 and May 2024. Based on computed tomography images at the time of initial cancer cachexia diagnosis to calculate the L3-SMI, the CXI was calculated using serum albumin (ALB) level, neutrophil-to-lymphocyte ratio (NLR), and skeletal muscle index (SMI). Using X-tile software, gender-specific optimal cutoff values for CXI were determined, and patients were divided into low and high CXI groups. Multiple BMI measurements were collected, and BMI dynamic trajectory subtypes were identified using latent category growth mixture modeling (GMM). Cox regression analysis was performed to identify independent risk factors for overall survival (OS); Kaplan-Meier survival curves were plotted; and subgroup interactions were analyzed according to cancer type, BMI trajectory subtype, ECOG PS, and TNM stage. A heterogeneity analysis of CT-based body composition was conducted to evaluate the relationship between muscle and adipose tissue. Results: GMM revealed two types of BMI decline trajectories: Class 1 (low reserve-slow decline BMI, 58%) and Class 2 (high reserve-accelerated decline BMI, 42%). The low CXI group had a considerably shorter median OS compared to the high CXI group (4.5 vs. 8.3 months, Conclusion: The combination of low CXI and Class 1 trajectory was identified as an exceedingly high-risk phenotype with markedly poor survival, mandating early intensive intervention. This novel composite model provides a critical foundation for early risk stratification and precise intervention strategies in cancer cachexia, with the potential to significantly improve patient prognosis.
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.