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Nutritional immune risk score predicts overall survival in colorectal cancer inpatients

Nutritional immune risk score predicts overall survival in colorectal cancer inpatients
Photo by Sophie Popplewell / Unsplash
Key Takeaway
Note that low-risk NIRS scores associate with better overall survival in colorectal cancer inpatients, but observational data limit causal claims.

This retrospective cohort study analyzed data from 892 inpatients diagnosed with primary colorectal cancer who underwent curative resection at a single center between 2017 and 2023. The researchers constructed a nutritional immune risk score (NIRS) model using clustering and principal component analysis to stratify patients into high-risk and low-risk groups. The primary outcome assessed was overall survival. Results indicated that patients in the low-risk group had significantly better overall survival compared to those in the high-risk group. However, the study did not report specific effect sizes, absolute numbers, or exact p-values beyond stating that the difference met a statistical threshold.

The study did not report data on adverse events, serious adverse events, discontinuations, or tolerability, as the NIRS model is a predictive scoring system rather than an administered intervention. Consequently, no safety profile or discontinuation rates are available for this specific analysis. The study design is observational, which inherently limits the ability to establish causal relationships between the risk score and survival outcomes. Additionally, the study phase and publication type were not reported in the provided data.

Key limitations include the lack of reported effect sizes and the single-center setting, which may affect the generalizability of the findings. The study population was restricted to inpatients undergoing curative resection, potentially excluding ambulatory patients or those with non-curative disease. While the NIRS model shows promise for risk stratification, clinicians should interpret these results with caution due to the observational nature of the data and the absence of reported funding or conflict of interest statements.

In practice, this model could assist in identifying high-risk colorectal cancer patients who might benefit from closer surveillance or targeted interventions. However, the lack of reported practice relevance and the observational design mean that current evidence is insufficient to recommend the NIRS model for routine clinical decision-making without further validation in prospective studies.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
BackgroundSurvival outcomes among patients with colorectal cancer (CRC) often differ despite identical disease stages, partly due to variations in nutritional and immune status. Malnutrition can impair immune defense, exacerbate inflammatory responses, and influence tumor progression, ultimately contributing to a poorer prognosis. However, current clinical prognostic systems rarely integrate nutritional immune indicators with tumor biomarkers, limiting the application of nutritional intervention in CRC management. This study aimed to develop a nutritional immune risk score (NIRS) model to improve long-term prognostic evaluation in patients with CRC.MethodsIn this retrospective study, 892 inpatients with primary CRC who underwent curative resection in 2017 were included and followed until 2023. Unsupervised learning was applied to nutritional and tumor biomarkers for feature extraction and patient stratification. K-means clustering was used to identify subgroups, and principal component analysis was used to derive composite features, which were then used to construct the NIRS model for long-term prognostic assessment.ResultsFour variables—prognostic nutritional index (PNI), carcinoembryonic antigen (CEA), carbohydrate antigen 19–9 (CA19-9), and carbohydrate antigen 72–4 (CA72-4)—were selected for model construction. The final model was defined as: NIRS = 0.572 × PNI – 0.101 × CEA – 0.412 × CA19-9 – 0.028 × CA72-4. Using an optimal cutoff value of 21.34, patients were stratified into a low-risk group and a high-risk group. The Kaplan–Meier analysis showed that patients in the low-risk group had significantly better overall survival than those in the high-risk group (p 
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