Biomarkers in immunonutrition programme, is there still a need for new ones? A brief review
| Autor: | Simone Giglioli, Stephane Nikis, Marc De Kock, Brigitte Bertrand, Patrice Forget, Garazi Echeverria, Jean-Paul Lechat |
|---|---|
| Přispěvatelé: | UCL - (SLuc) Service d'anesthésiologie, UCL - (SLuc) Service de soins intensifs, UCL - (SLuc) Service de radiologie, UCL - (SLuc) Centre du cancer, UCL - SSS/IONS/CEMO - Pôle Cellulaire et moléculaire |
| Rok vydání: | 2015 |
| Předmět: |
Oncology
Cancer Research medicine.medical_specialty business.industry biomarkers Cancer Review Perioperative Immune monitoring medicine.disease Bioinformatics Malnutrition inflammation Weight loss Internal medicine Medicine Biomarker (medicine) medicine.symptom business immunonutrition Body mass index Serum markers |
| Zdroj: | ecancermedicalscience Ecancermedicalscience, Vol. 9, p. 546 [1-6] (2015) |
| ISSN: | 1754-6605 |
| Popis: | Background and aims Pre-existing malnutrition is one the most important factors affecting postsurgical complications, especially in cancer patients. The consequences of this on the immune function as well as on outcome could be reversed by immunonutrition. To help the clinician as a researcher, a routinely available biomarker (derived from clinical or biological data) would be of great importance. Methods We reviewed the potential markers that may routinely be used in perioperative immunonutrition programmes. A comprehensive approach was used to identify and discuss the potential markers, focusing on body mass and serum biomarkers. Results Body mass (including weight loss and body mass index) are predictive of complications, but not specifically to malnutrition. Serum markers, such as albumin, transthyretin, white blood cells counts, and C-reactive protein are not more specific. Composite scores, including the Nutritional Risk Index (NRI), the Prognostic Inflammatory and Nutritional Index (PINI), the modified Glasgow Prognostic Score (mGPS), the neutrophil-to-lymphocyte ratio (NLR), CD4 and CD8 lymphocytes counts, the platelet-to-lymphocyte ratio (PLR), the Prognostic Index (PI), and the Prognostic Nutritional Index (PNI) are prognostic factors of outcome, but are not always correlated to immunonutrition effect. Conclusions In conclusion, there remains a lack of efficient and widely available monitoring of the effects of immunonutrition. To predict and monitor the effect of immunonutrition on immunity, efforts should be directed to the validation of routinely available tools to aid the implementation of advanced immune monitoring (like lymphocytes subpopulations counts) in clinical practices. |
| Databáze: | OpenAIRE |
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