中国全科医学 ›› 2026, Vol. 29 ›› Issue (30): 4489-4502.DOI: 10.12114/j.issn.1007-957.2024.0592

• 医学循证 • 上一篇    下一篇

不同骨改良药物治疗实体瘤骨转移或多发性骨髓瘤患者疗效的网状Meta分析

胡玉婷1,2, 严颖3, 闫明婕2, 王惠君2, 韩虎1,*()   

  1. 1.832061 新疆维吾尔自治区石河子市,石河子大学第一附属医院
    2.832061 新疆维吾尔自治区石河子市,石河子大学药学院
    3.100042 北京市,北京大学肿瘤医院暨北京市肿瘤防治研究所乳腺肿瘤内科 恶性肿瘤发病机制及转化研究教育部重点实验室
  • 收稿日期:2024-11-24 修回日期:2024-12-25 出版日期:2026-10-20 发布日期:2026-09-02
  • 通讯作者: 韩虎

  • 作者贡献:

    胡玉婷负责数据运算及论文初稿的撰写;以及修改论文;严颖负责选定研究主题;闫明婕负责文献的检索、筛选及数据提取;王慧君进行论文修订;韩虎负责偏倚风险中的第三方裁定。

  • 基金资助:
    新疆生产建设兵团第八师石河子市财政科技计划资助项目-重点领域科技攻关项目(2023NY04-2)

Network Meta-analysis of the Efficacy of Different Bone-modifying Drugs in the Treatment of Patients with Bone Metastases from Solid Tumours or Multiple Myeloma

HU Yuting1,2, YAN Ying3, YAN Mingjie2, WANG Huijun2, HAN Hu1,*()   

  1. 1. The First Affiliated Hospital of Shihezi University, Shihezi 832061, China
    2. School of Pharmacy, Shihezi University, Shihezi 832061, China
    3. Department of Breast Oncology, Cancer Hospital of Peking University and Beijing Institute of Cancer Prevention and Control/Key Laboratory of Pathogenesis and Translational Research of Malignant Tumour, Ministry of Education, Beijing 100042, China
  • Received:2024-11-24 Revised:2024-12-25 Published:2026-10-20 Online:2026-09-02
  • Contact: HAN Hu

摘要: 背景 骨相关事件(SREs)是实体瘤骨转移或多发性骨髓瘤患者的严重并发症,骨改良药物(BMAs)与传统治疗方法相比具有骨组织靶向给药系统的优势,但鉴于种类繁多且药物治疗策略相对复杂,如何确定适宜的药物和给药频率是现阶段BMAs面临的重要问题。 目的 比较不同BMAs治疗实体瘤骨转移或多发性骨髓瘤患者的疗效。 方法 由2名研究员按照检索策略独立检索PubMed、Cochrane Library、Embase、Clinical Trials、Web of Science、中国知网、万方数据知识服务平台及维普网中BMAs治疗实体瘤骨转移癌症或多发性骨髓瘤患者的随机对照试验(RCT),检索时限为建库至2024年1月。采用Cochrane风险评价工具对纳入文献进行质量评价,利用R 4.3.3软件和STATA 17.0软件进行统计学分析。 结果 共纳入64项RCT,28 773例患者,涉及安慰剂/未使用骨改良药物组(PLA),地舒单抗原研药标准给药组(DENO),唑来膦酸标准给药组(ZA),伊班膦酸标准给药组(IBA),帕米膦酸标准给药组(PAM),帕米膦酸长间隔给药组(PAM*),氯膦酸标准给药组(CLO),利赛膦酸标准给药组(RIS),阿仑膦酸标准给药组(ALE),地舒单抗生物类似药标准给药组(DENO#),地舒单抗原研药长间隔给药组(DENO*)和唑来膦酸长间隔给药组(ZA*)共12种干预措施。网状Meta分析结果显示,总SREs发生率的累积概率排序图下面积(SUCRA)排序为:DENO(82.29%)>DENO*(81.48%)>DENO#(76.09%)>ZA(59.74%)>ZA*(55.53%)>IBA(43.19%)>PAM*(42.21%)>CLO(37.37%)>PAM(31.87%)>RIS(31.26%)>PLA(8.97%);至首次发生SREs时间的SUCRA排序为:DENO*(85.45%)>DENO(83.89%)>IBA(56.72%)>ZA(53.35%)>PAM(44.39%)>ZA*(42.58%)>DENO#(27.04%)>PLA(6.59%);总生存时间(OS)的SUCRA排序为:ZA*(79.66%)>IBA(79.05%)>DENO(73.19%)>ZA(64.14%)>CLO(42.96%)>PAM(30.55%)>PLA(18.95%)>RIS(11.49%);无进展生存时间(PFS)的SUCRA排序为:ZA(75.90%)>ALE(68.08%)>PAM(53.91%)>PLA(31.73%)>CLO(20.37%)。亚组分析结果显示,标准给药亚组与长间隔给药亚组的总SREs发生率和至首次发生SREs时间比较,差异均无统计学意义(总SREs发生率:RR=1.00,95%CI=0.89~1.13,P=0.960;至首次发生SRE时间:HR=0.97,95%CI=0.74~1.27,P=0.775)。 结论 当前证据显示,地舒单抗是目前治疗实体瘤骨转移或多发性骨髓瘤患者的最佳药物干预方式。其中,延长给药频率是一种可接受的治疗方案。

关键词: 多发性骨髓瘤, 实体瘤, 骨转移, 骨改良药物, 网状Meta分析

Abstract:

Background

Skeletal-related events (SREs) are severe complications in patients with bone metastases from solid tumors or multiple myeloma. Bone-modifying agents (BMAs) offer the advantage of a targeted drug delivery system to bone tissue compared to traditional treatment methods. However, given the variety of BMAs and the relative complexity of drug treatment strategies, determining the appropriate drug and dosing frequency is a significant challenge currently faced by BMAs.

Objective

A network meta-analysis comparing the efficacy of different BMAs in the treatment of patients with bone metastases from solid tumors or multiple myeloma.

Methods

Two researchers independently searched PubMed, Cochrane Library, Embase, Clinical Trials, Web of Science, China National Knowledge Infrastructure, Wanfang Data, and VIP databases for randomized controlled trials (RCTs) on bone-modifying agents in the treatment of patients with bone metastases from solid tumors or multiple myeloma, following the predefined search strategy. The search timeframe spanned from the inception of each database to January 2024. The quality of the included studies was assessed using the Cochrane risk of bias tool. Statistical analyses were performed using R 4.3.3 and STATA 17.0 software.

Results

A total of 64 RCTs were included, involving 28 773 patients. The interventions involved were: placebo/no bone-modifying agents group (PLA), standard dosing of denosumab originator group (DENO), standard dosing of zoledronic acid group (ZA), standard dosing of ibandronic acid group (IBA), standard dosing of pamidronate group (PAM), longer-interval dosing of pamidronate group (PAM*), standard dosing of clodronate group (CLO), standard dosing of risedronate group (RIS), standard dosing of alendronate group (ALE), standard dosing of denosumab biosimilar group (DENO#), longer-interval dosing of denosumab originator group (DENO*), and longer-interval dosing of zoledronic acid group (ZA*), totaling 12 different intervention measures. For the incidence of total SREs, the surface under the cumulative ranking curve (SUCRA) showed the following ranking: DENO (82.29%) >DENO* (81.48%) >DENO# (76.09%) >ZA (59.74%) >ZA* (55.53%) >IBA (43.19%) >PAM* (42.21%) >CLO (37.37%) >PAM (31.87%) >RIS (31.26%) >PLA (8.97%). For the time to first SREs, the SUCRA ranking was: DENO* (85.45%) >DENO (83.89%) >IBA (56.72%) >ZA (53.35%) >PAM (44.39%) >ZA* (42.58%) >DENO# (27.04%) >PLA (6.59%). Regarding overall survival (OS), the SUCRA ranking was: ZA* (79.66%) >IBA (79.05%) >DENO (73.19%) >ZA (64.14%) >CLO (42.96%) >PAM (30.55%) >PLA (18.95%) >RIS (11.49%). For progression-free survival (PFS), the SUCRA ranking was: ZA (75.90%) >ALE (68.08%) >PAM (53.91%) >PLA (31.73%) >CLO (20.37%). Subgroup analysis revealed there was no statistically significant differences between the standard dosing group and the extended-interval dosing group in overall incidence of SREs or the time to the first SREs (Overall incidence of SREs: RR=1.00, 95%CI=0.89-1.13, P=0.960; The time to the first SREs: HR=0.97, 95%CI=0.74-1.27, P=0.775).

Conclusion

Current evidence suggests that denosumab may be the best pharmacological intervention available for the treatment of patients with bone metastases from solid tumours or multiple myeloma. In this regard, extended dosing frequency may be an acceptable treatment regimen option.

Key words: Multiple myeloma, Solid tumour, Bone metastasis, Bone-modifying agents, Network meta analysis