Effect of bortezomib on the treatment of multiple myeloma: a systematic review protocol

BMJ OPEN(2022)

引用 2|浏览3
暂无评分
摘要
Introduction Multiple myeloma (MM) is an incurable malignant neoplasm that accounts for approximately 1% of all cancers and 10% of haematological malignancies. Bortezomib is one of the most commonly used medications in first-line treatment and subsequent relapses, either as a single agent or in combination with other therapies. This study aims to assess the effects of bortezomib on the overall survival (OS), progression-free survival, overall response rate, time to next treatment, health-related quality of life, compliance, adverse events and treatment-related death in patients with MM. Methods and analysis We have performed a systematic review and meta-analysis and will include both randomised and non-randomised controlled studies where the effect of bortezomib was compared in similar or dissimilar background therapies in each arm. General and adaptive search strategies have been created for the following electronic health databases: Embase, Medline, LILACS and CENTRAL. Two reviewers have independently selected eligible studies, will assess the risk of bias, and will extract data from the included studies. Similar outcomes will be plotted in the meta-analysis using the Stata Statistical Software V.17. The relative risk will be calculated with a 95% CI as the effect size of bortezomib. For the OS and progression-free survival, we calculate the overall OR from the HRs of each included study. Peto's one-step OR will be calculated for event rates below 1%. We will use the Grading of Recommendations Assessment, Development and Evaluation system to evaluate the certainty of evidence. Ethics and dissemination As no primary data collection will be undertaken, formal ethical assessment is not required. We plan to present the results of this systematic review in a peer-reviewed scientific journal, conferences and popular press. PROSPERO registration number CRD42020151142.
更多
查看译文
关键词
myeloma, myeloma, clinical pharmacology
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要