治疗耐甲氧西林金黄色葡萄球菌菌血症的头孢他啶磷酰胺:真实世界临床疗效比较研究》。

IF 1.9 Q3 PHARMACOLOGY & PHARMACY
Drugs - Real World Outcomes Pub Date : 2024-06-01 Epub Date: 2024-04-02 DOI:10.1007/s40801-024-00422-5
Jennifer Hammond, Michael Benigno, Nataly Bleibdrey, Wajeeha Ansari, Jennifer L Nguyen
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引用次数: 0

摘要

背景和目的:耐甲氧西林金黄色葡萄球菌(MRSA)菌血症会导致严重的发病率和死亡率。由于目前的治疗方法往往无法取得令人满意的疗效,因此需要有证据来指导替代治疗方案。本研究评估了头孢他啶福沙米尔治疗MRSA菌血症的实际临床效果:这项回顾性研究纳入了 2011 年至 2019 年期间因 MRSA 菌血症住院的成人患者。根据头孢他啶福沙米尔(ceftaroline fosamil)、万古霉素或达托霉素的治疗情况对患者进行分类:第1组:头孢他啶;第2组:万古霉素或达托霉素(不含头孢他啶);第3组:这三种药物中≥2种的联合疗法。临床结果采用逻辑回归模型中倾向分数调整后的几率比(ORs)进行比较:共纳入 24479 名患者(第 1 组,n = 532;第 2 组,n = 21555;第 3 组,n = 2392)。第一组、第二组和第三组的平均年龄分别为 59.6 岁、60.8 岁和 57.4 岁。指数治疗后的平均住院时间分别为 8.8 天、8.8 天和 8.0 天。在第 1、2 和 3 组中,最常用的治疗方法分别是头孢他啶一线疗法(42.1%)、万古霉素或达托霉素一线疗法(95.4%)和三线或三线以上联合疗法(67.8%)。与第 2 组相比,第 1 组和第 3 组具有相似的良好临床反应{ds ratio [OR] = 1.18 [95% confidence interval (CI)0.98-1.44],p = 0.08;OR = 1.20 [95% CI 0.97-1.47],p = 0.09,分别},并且较少更换治疗方法(均为 p 结论:与第 2 组相比,第 1 组和第 3 组具有相似的良好临床反应:与接受万古霉素或达托霉素单药治疗的患者相比,接受头孢他啶治疗的患者更常出现良好的临床反应。在缺乏大规模随机对照试验的情况下,这些真实世界的数据为头孢他啶治疗 MRSA 菌血症的潜在作用提供了启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ceftaroline Fosamil for the Treatment of Methicillin-Resistant Staphylococcus Aureus Bacteremia: A Real-World Comparative Clinical Outcomes Study.

Background and objective: Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia results in substantial morbidity and mortality. As current treatments often lead to unsatisfactory outcomes, evidence guiding alternative treatment options is needed. This study evaluated real-world clinical outcomes of ceftaroline fosamil for the treatment of MRSA bacteremia.

Methods: This retrospective study included adults hospitalized with MRSA bacteremia between 2011 and 2019. Patients were classified according to treatment with ceftaroline fosamil (ceftaroline), vancomycin, or daptomycin: Group 1, ceftaroline; Group 2, vancomycin or daptomycin (without ceftaroline); Group 3, combination therapy with ≥ 2 of these three agents. Clinical outcomes were compared using propensity-score-adjusted odds ratios (ORs) from logistic regression models.

Results: Overall, 24,479 patients were included (Group 1, n = 532; Group 2, n = 21,555; Group 3, n = 2392). Mean age was 59.6, 60.8, and 57.4 years in Groups 1, 2, and 3, respectively. Mean post-index treatment length of stay was 8.8, 8.8, and 8.0 days, respectively. The most frequent line of therapy was ceftaroline first-line (42.1%), vancomycin or daptomycin first-line (95.4%), and combination therapy third-line or later (67.8%) in Groups 1, 2, and 3, respectively. Compared with Group 2, Groups 1 and 3 had similar favorable clinical responses {odds ratio [OR] = 1.18 [95% confidence interval (CI) 0.98-1.44], p = 0.08; OR = 1.20 [95% CI 0.97-1.47], p = 0.09, respectively} and were less likely to switch treatment (both p < 0.001). Compared with Group 2, Group 1 was more likely to undergo 30-day all-cause readmission [OR = 1.38 (95% CI 1.06-1.80), p = 0.02], whereas this was less likely for Group 3 [OR = 0.77 (95% CI 0.58-1.00), p = 0.05].

Conclusions: Patients receiving ceftaroline more often had favorable clinical responses than those receiving vancomycin or daptomycin monotherapy. In the absence of large-scale randomized controlled trials, these real-world data provide insights into the potential role of ceftaroline for treating MRSA bacteremia.

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来源期刊
Drugs - Real World Outcomes
Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-
CiteScore
3.60
自引率
5.00%
发文量
49
审稿时长
8 weeks
期刊介绍: Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.
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