Predictors of therapeutic and adverse effects of medicines used in the treatment of breast cancer_012021

Breast cancer is the most commonly occurring cancer in women and the second most common cancer overall. There were over 2 million new cases in 2018. There are many important medicines used in the treatment of breast cancer. However, response and toxicity to many therapies is highly unpredictable. For example, over half the eligible patients do not respond to anti-human epidermal growth factor receptor 2 (HER2) targeted therapy when used in the treatment of advanced breast cancer. Thus, more research is required to confirm and explore novel predictive markers of therapeutic and adverse effects of medicines used in the treatment of breast cancer.
Using the diverse range of data collected from clinical trials, it is possible to develop clinical tools that enable improved prediction of therapeutic and adverse outcomes of patients using medicines in the treatment of breast cancer. Being able to identify the expected response and adverse effect profile may enable patients and clinicians to make better decisions regarding whether to commence, continue, discontinue or change dosing of medicines used in the treatment of breast cancer.

乳腺癌是女性群体中发病率最高的恶性肿瘤，亦是全球范围内第二大高发癌症。2018年全球新增乳腺癌病例超200万例。目前临床中可用于乳腺癌治疗的重要药物种类繁多，但多数治疗方案的临床响应与毒性反应均具有高度不可预测性。例如，在晚期乳腺癌的治疗中，超半数符合适应症的患者对抗人表皮生长因子受体2（HER2）靶向治疗无响应。因此，亟需开展更多研究，以确认并探索可用于预测乳腺癌治疗药物疗效与不良反应的新型标志物。
依托临床试验中采集的多维度数据，可开发临床辅助工具，实现对乳腺癌患者接受药物治疗后的治疗响应与不良反应结局的精准预测。若能准确预判药物的预期响应特征与不良反应谱，将有助于患者与临床医师针对是否启动治疗、维持治疗、停药或调整给药剂量做出更优化的临床决策。