Prognostic importance of modified geriatric nutritional risk index in oral cavity squamous cell carcinoma
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View abstract on PubMed
Summary
This summary is machine-generated.Preoperative modified geriatric nutritional risk index (mGNRI) predicts outcomes in oral cavity squamous cell carcinoma (OCSCC) surgery patients. Higher mGNRI scores correlate with better overall survival (OS) and disease-free survival (DFS).
Area Of Science
- Oncology
- Surgical Oncology
- Geriatric Medicine
Background
- Oral cavity squamous cell carcinoma (OCSCC) is a significant global health concern.
- Prognostic markers are crucial for tailoring OCSCC treatment and improving patient outcomes.
- Nutritional status is increasingly recognized as a factor influencing cancer prognosis.
Purpose Of The Study
- To investigate the association between preoperative modified geriatric nutritional risk index (mGNRI) and prognosis in patients undergoing surgery for OCSCC.
- To determine the optimal cutoff value for mGNRI in predicting survival outcomes.
- To develop a nomogram for predicting overall survival (OS) based on mGNRI.
Main Methods
- Retrospective analysis of clinical data from 333 OCSCC patients who underwent surgery (2008-2017).
- Calculation of preoperative mGNRI using a validated formula involving C-reactive protein, actual body weight, and ideal body weight.
- Utilized receiver operating characteristic (ROC) curve analysis, Kaplan-Meier survival analysis, and Cox proportional hazard models.
Main Results
- The optimal mGNRI cutoff value was determined to be 73.3.
- Patients with high mGNRI (≥73.3) demonstrated significantly higher 5-year OS and DFS rates compared to those with low mGNRI (<73.3) (p < 0.001).
- A preoperative mGNRI below 73.3 was an independent predictor of unfavorable DFS and OS. A nomogram achieved a concordance index of 0.781 for OS prediction.
Conclusions
- Preoperative mGNRI is a valuable, cost-effective prognostic biomarker for OCSCC patients undergoing surgery.
- The developed mGNRI-based nomogram provides accurate and individualized OS predictions.
- Integrating mGNRI into clinical practice can aid in risk stratification and personalized management of OCSCC.
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