The Relationship Between Nutritional Status and Chemotherapy Toxicity in Patients with Cervical Cancer: A Systematic Review
Notice bibliographique
Résumé
Introduction: Cervical cancer imposes a significant global health burden, disproportionately affecting low- and middle-income countries where malnutrition is also endemic. Antineoplastic therapy, particularly concurrent chemoradiotherapy (CCRT) with platinum-based agents, is the standard of care but is associated with severe toxicities. This systematic review investigates the central hypothesis that poor nutritional status—defined by a range of anthropometric, serological, and body composition metrics—is an independent and significant predictor of increased chemotherapy-related toxicity in cervical cancer patients. Methods: This review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A systematic search of PubMed, Scopus, and the Cochrane Library was performed to identify studies evaluating the relationship between nutritional status and chemotherapy toxicity in cervical cancer patients. Eligibility criteria were based on the Population (cervical cancer patients), Exposure (malnutrition), Comparison (well-nourished), and Outcome (toxicity) framework. Methodological quality was appraised using the Cochrane Risk-of-Bias 2 (RoB 2) tool for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale (NOS) for observational studies. Results: A total of 16 studies (2 RCTs and 14 observational cohorts) met the inclusion criteria. The results demonstrate a consistent and statistically significant association between malnutrition and increased treatment toxicity. Specifically, poor nutritional status assessed by the Patient-Generated Subjective Global Assessment (PG-SGA) was an independent predictor of both Grade 3+ toxicity and Toxicity-Induced Modification of Treatment (TIMT). Sarcopenia (low Skeletal Muscle Index, SMI) was significantly associated with higher rates of treatment interruption due to toxicity (p=0.024) and was a determining factor for Grade 3+ adverse events. Low Body Mass Index (BMI < 18.5 kg/m²) was linked to severe Grade 3/4 gastrointestinal complications, including bowel obstruction (p<0.001). A low Prognostic Nutritional Index (PNI) correlated with increased severity of fatigue, nausea, and diarrhea (p<0.05). Nutritional interventions, such as omega-3 supplementation, were shown in an RCT to significantly reduce the incidence of chemotherapy toxicity. Discussion: The evidence converges to confirm that malnutrition is a critical determinant of chemotherapy tolerance. The mechanisms are multifactorial. Pharmacokinetic alterations, such as hypoalbuminemia, increase the free, active fraction of protein-bound drugs, leading to toxicity. Pharmacodynamic failures, particularly in sarcopenic patients, result in a relative overdose from standard Body Surface Area (BSA)-based dosing due to a smaller volume of distribution. Malnutrition also impairs the host's ability to repair healthy tissue (e.g., gut mucosa, bone marrow) damaged by chemotherapy. Conclusion: Nutritional status is a powerful, modifiable predictor of severe chemotherapy-related toxicity in cervical cancer patients. These findings mandate the integration of nutritional screening (e.g., PG-SGA) and objective assessment (e.g., CT-based SMI) into routine oncological practice. Such screening can risk-stratify patients and trigger pre-emptive nutritional interventions to improve treatment tolerance, reduce toxicity-related interruptions, and optimize clinical outcomes
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,052 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».