Astragalus-Containing Traditional Chinese Medicine, with and without Prescription Based on Syndrome Differentiation, Combined with Chemotherapy for Advanced Non-Small-Cell Lung Cancer: A Systemic Review and Meta-Analysis
Notice bibliographique
Résumé
OBJECTIVE: Traditional Chinese Medicine (tcm) is used in China as part of the treatment for non-small-cell lung cancer (nsclc) and often includes prescription of herbal therapy based on syndrome differentiation. Studies of various Astragalus-based Chinese medicines combined with platinum-based chemotherapy in the treatment of lung cancer are popular in East Asia, particularly in China. The aim of the present study was to perform a systematic review and meta-analysis comparing platinum-based chemotherapy alone with platinum-based chemotherapy plus Astragalus-based Chinese botanicals, with and without prescription based on syndrome differentiation, as first-line treatment for advanced nsclc. METHODS: We searched the Chinese Biomedical Literature database, the China National Knowledge Internet, the VIP Chinese Science and Technology Periodicals Database, PubMed, embase, the Cochrane databases, and abstracts presented at meetings of the American Society of Clinical Oncology, the World Conference on Lung Cancer, the European Society for Medical Oncology, and the Chinese Society of Clinical Oncology for all eligible studies. Endpoints were overall survival; 1-year, 2-year, and 3-year survival rates; performance status; overall response rate; and grade 3 or 4 adverse events. Subgroup analyses based on herbal formulae individualized using syndrome differentiation or on oral or injection patent medicines were performed using the Stata software application (version 11.0: StataCorp LP, College Station, TX, U.S.A.) and a fixed-effects or random-effects model in case of heterogeneity. Results are expressed as a hazard ratio (hr) or relative risk (rr), with corresponding 95% confidence intervals (cis). RESULTS: Seventeen randomized studies with scores on the Jadad quality scale of 2 or more, representing 1552 patients, met the inclusion criteria. Compared with platinum-based chemotherapy alone, the addition of Astragalus-based tcm to chemotherapy was associated with significantly increased overall survival (hr: 0.61; 95% ci: 0.42 to 0.89; p = 0.011); 1-year (rr: 0.73; 95% ci: 0.65 to 0.82; p < 0.001), 2-year (rr: 0.3344; 95% ci: 0.237 to 0.4773; p < 0.001), and 3-year survival rates (rr: 0.30; 95% ci: 0.17 to 0.53; p < 0.001); performance status (rr: 0.43; 95% ci: 0.34 to 0.55; p < 0.001); and tumour overall response rate (rr: 0.7982; 95% ci: 0.715 to 0.89; p < 0.001). Subgroup analyses indicated that Astragalus herbal formulae given based on syndrome differentiation were more effective than Astragalus-based oral and injection patent medicines. Side effects-including anemia, neutropenia, thrombocytopenia, fatigue, poor appetite, nausea, and vomiting-were significantly more frequent with platinum-based chemotherapy alone than when platinum-based chemotherapy was combined with Astragalus-based tcm. CONCLUSIONS: Astragalus-based Chinese botanical therapy, especially when based on syndrome differentiation, is associated with increased efficacy of platinum-based chemotherapy and decreased platinum-derived toxicities for patients with advanced nsclc.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,015 | 0,033 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».