Observational studyBMC cancer2025
Effect of comorbidity classes on survival of patients with gastrointestinal tract cancer.
Observational study in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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Who cites it
2 citing papers in PubMed.
- Composition and influencing factors of malnutrition management costs among gastrointestinal cancer patients with chronic comorbidities.Frontiers in public health · 2026Article
- Article
Corrections and comments
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Authors and funding
20 authors.
Funding
Abstract
backgroundComorbidities may complicate medical situations and have an impact on the treatment decisions and poor survival of cancer patients. How comorbidities cluster together and ultimately affect patients' outcomes in gastrointestinal tract cancer (GTC) is a poorly understood area.
methodsIn a multicenter prospective observational study from 2012 to 2021, we grouped the comorbidities of patients with GTC by latent class analysis, obtaining two comorbidity classes. Cox regression models were initially used to predict mortality. LASSO techniques were used to reduce the dimension. The final model included the comorbidity classes and nine more predictors. Additionally, the performance of different simple multimorbidity measures were compared using the Bayesian information criterion (BIC), ROC curves and C-index. Finally, the performance of the final model was analyzed using ROC curves, calibration curves and decision curves. The nomogram was drawn to evaluate the model.
resultsWe included 10,019 patients and obtained two comorbidity classes. Class 2 patients have a higher incidence of comorbidities, and a lower survival rate compared to Class 1 (P < 0.001). Compared to models containing the number of comorbidities or only a single comorbidity, the final model with the comorbidity classes has the highest AUC and C-index, as well as the lowest BIC, indicating this model has the best predictive performance.
conclusionWe identified two classes of comorbidities that were associated with overall survival in patients with GTC. The combination of different comorbidities class plays a vital role in the prognosis of GTC.
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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 Socratic graph.