Effects of epidural anesthesia on the prognosis of ovarian cancer—a systematic review and meta-analysis
Notice bibliographique
Résumé
Abstract Introduction The global low survival rate among ovarian cancer patients has resulted in significant social and economic burdens. Nevertheless, previous studies have produced mixed results when exploring the link between anesthetic techniques and the prognosis of ovarian cancer. The study aims to compare the effect of epidural anesthesia with general anesthesia on survival time after cytoreductive surgery in patients with ovarian cancer. Methods The PubMed (National Library of Medicine), Cochrane library, Web of science, Embase, CNKI (China National Knowledge Internet), Wanfang Med Online (China database), were systematically searched from inception to May, 2023, using the Medical Subject Headings [MeSH] of “Ovarian Neoplasm” and “Anesthesia, Epidural” and free words to identify systematic reviews or meta-analyses. The research methodology involved analyzing randomized controlled trials (RCTs), as well as prospective or retrospective cohort studies, which compared the long-term prognosis of patients with ovarian cancer under general anesthesia combined with epidural anesthesia (GEA) versus general anesthesia alone (GA). The Newcastle Ottawa Scale (NOS) was used to assess methodological quality and bias. Data extraction and assessment of study quality were conducted by two independent reviewers. A meta-analysis was then performed to calculate hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). Overall survival (OS) was defined as the primary outcome, time to tumor recurrence (TTR) was the secondary outcome. Epidural anesthesia could be used intraoperatively and immediately postoperatively (EIP), or postoperatively only (EP). GEA includes EIP and EP. Results In total, 8 retrospective cohort studies with 2036 participants met the inclusion criteria. The pooled results demonstrated that GEA could extend OS (HR 0.75, 95% CI 0.67–0.84, I 2 = 0%, P < 0.05, fixed-effect model) when compared with GA in ovarian cancer patients undergoing cytoreductive surgery, but not TTR (sensitivity analysis revealed substantial heterogeneity among the included studies). The result of analyzing a total of 1490 patients in 4 studies was that EIP had a better prognosis on OS than GA (HR 0.68, 95%CI 0.55–0.85, I 2 = 61%, P < 0.05, random-effect model). However, EP had no advantage in TTR (sensitivity analysis revealed it was unstable outcome). Ovarian cancer FIGO(International Federation of Gynecology and Obstetrics) stage III, stage IV compared to stage I on OS was statistically significant, HRs respectively are 3.67 (95%CI 2.25–5.98), I 2 = 0%, fixed-effect model, P < 0.05, and 7.43 (95%CI 3.67–15.03), I 2 = 31%, fixed-effect model, P < 0.05, but there was no statistically significant difference between stage II and stage I, HR 2.00, 95%CI0.98–4.09, I 2 = 0%, fixed-effect model, P > 0.05. 1-10 mm tumor residuals shorten TTR compared with 0 residuals, HR 1.75, 95% CI1.50–2.04, I 2 = 0%, fixed-effect model, P < 0.05. Conclusions It is hard to conclude that postoperative epidural analgesia offers greater benefits than GA. However, general anesthesia combined with epidural anesthesia (EIP) can improve overall survival in ovarian cancer patients, allowing the anesthesiologist to use anesthesia techniques to provide a favorable prognosis for the ovarian cancer patient. Tumor staging and the extent of cell reduction are also critical factors that significantly influence the long-prognosis of ovarian cancer patients.
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,019 | 0,005 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| 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; un appel candidat d’une seule tête enseignante, 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 ».