We searched PubMed, Embase, and ClinicalTrials.gov from inception until August 31, 2021, for phase II/III randomized controlled trials of 11 VEGF-TKIs (axitinib, cabozantinib, lenvatinib, pazopanib, ponatinib, ripretinib, regorafenib, sorafenib, sunitinib, tivozanib, and vandetanib). The endpoints were heart failure, thromboembolism, and cardiovascular death. The Mantel-Haenszel method was used to calculate the risk of VEGF-TKI among users by comparing it to nonusers. Pairwise meta-analyses with a random-effects model were used to estimate the risks of the various VEGF-TKIs. We estimated ranked probability with a P-score and assessed credibility using the Confidence in Network Meta-Analysis framework.
We identified 69 trials involving 30 180 patients with cancer. The highest risk of MACEs was associated with high-potency tivazonib (odds ratio [OR]: 3.34), lenvatinib (OR: 3.26), and axitinib (OR: 2.04), followed by low-potency pazopanib (OR: 1.79), sorafenib (OR: 1.77), and sunitinib (OR: 1.66). The risk of heart failure significantly increased in association with less-selective sorafenib (OR: 3.53), pazopanib (OR: 3.10), and sunitinib (OR: 2.65). The risk of thromboembolism significantly increased in association with nonselective lenvatinib (OR: 3.12), sorafenib (OR: 1.54), and sunitinib (OR: 1.53). Higher potency (tivozanib, axitinib) and lower selectivity (sorafenib, vandetanib, pazopanib, sunitinib) were associated with a higher probability of heart failure. Low selectivity (lenvatinib, cabozantinib, sorafenib, sunitinib) was associated with a higher probability of thromboembolism.
Higher-potency and lower-selectivity VEGF-TKIs may influence the risks of MACEs, heart failure, and thromboembolism. These findings may facilitate evidence-based decision-making in clinical practice.
方法:我们搜索了PubMed,Embase,和ClinicalTrials.gov从开始到2021年8月31日,用于11个VEGF-TKIs的II/III期随机对照试验(阿西替尼,卡博替尼,lenvatinib,帕唑帕尼,普纳替尼,里替尼,Regorafenib,索拉非尼,舒尼替尼,tivozanib,和vandetanib)。终点是心力衰竭,血栓栓塞,心血管死亡。使用Mantel-Haenszel方法通过与非使用者比较来计算使用者中VEGF-TKI的风险。使用随机效应模型的成对荟萃分析来估计各种VEGF-TKIs的风险。我们用P分数估计排名概率,并采用网络元分析框架中的信心评估可信度。
结果:我们确定了69项试验,涉及30180例癌症患者。MACE的最高风险与高效替伐唑尼(比值比[OR]3.34)有关,乐伐替尼(OR3.26),和阿西替尼(OR:2.04),其次是低效帕唑帕尼(OR:1.79),索拉非尼(OR:1.77),和舒尼替尼(OR:1.66)。心力衰竭的风险显著增加与选择性较低的索拉非尼(OR:3.53),帕唑帕尼(OR:3.10),和舒尼替尼(OR:2.65)。非选择性来伐替尼(OR:3.12)与血栓栓塞的风险显着增加,索拉非尼(OR:1.54),和舒尼替尼(OR:1.53)。更高的效力(tivozanib,阿西替尼)和较低的选择性(索拉非尼,Vandetanib,帕唑帕尼,舒尼替尼)与心力衰竭的可能性较高有关。低选择性(乐伐替尼,卡博替尼,索拉非尼,舒尼替尼)与较高的血栓栓塞概率相关。
结论:高效力和低选择性的VEGF-TKIs可能会影响MACEs的风险,心力衰竭,和血栓栓塞。这些发现可能有助于临床实践中基于证据的决策。