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CMTTdb: the cancer molecular targeted therapy database.
Bai, Xue; Yang, Xiaobo; Wu, Liangcai; Zuo, Bangyou; Lin, Jianzhen; Wang, Shanshan; Bian, Jin; Sang, Xinting; He, Yungang; Yang, Zhen; Zhao, Haitao.
Afiliación
  • Bai X; Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing 100730, China.
  • Yang X; Institute of Biomedical Sciences, Fudan University, Shanghai 200032, China.
  • Wu L; Department of Radiology, Nanfang Hospital, First Clinical College of Northern Medical University, Guangzhou 510515, China.
  • Zuo B; Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing 100730, China.
  • Lin J; Institute of Biomedical Sciences, Fudan University, Shanghai 200032, China.
  • Wang S; Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing 100730, China.
  • Bian J; Institute of Biomedical Sciences, Fudan University, Shanghai 200032, China.
  • Sang X; Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.
  • He Y; Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200090, China.
  • Yang Z; Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing 100730, China.
  • Zhao H; Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing 100730, China.
Ann Transl Med ; 7(22): 667, 2019 Nov.
Article en En | MEDLINE | ID: mdl-31930068
BACKGROUND: The cancer molecular targeted therapy has achieved unprecedented progress in the past decade and is thought to be the most promising direction for cancer treatment in future. As the fast growing of the clinical trials of targeted anticancer agents for different cancer types, it is critical to collect and integrate such information to guide clinical practice. METHODS: We constructed the Cancer Molecular Targeted Therapy database (CMTTdb) to store and retrieve molecular targeted therapy data about randomized clinical trials (RCTs) of targeted agents and also accompanied targets, biomarkers, targeted cancer subtypes, etc. RESULTS: Different with some existing resources, CMTTdb particularly focuses on clinical application of the trails. Design of the trails, such as treatment modalities (monotherapy or combination with other therapies), as well as results on clinical efficacy parameters, adverse events are also collected. In this current version, CMTTdb contains data for 1,088 clinical trials which cover 165 agents, 80 targets, 15 cancer types (95 molecular subtypes and 56 histological or cytological subtypes) from public literatures. This database is freely available at http://www.biosino.org/CMTTdb. A user-friendly web interface was designed so that these data can be easily retrieved. CONCLUSIONS: CMTTdb will be a valuable source for providing access to information of clinical trials on the rapidly growing number of novel targeted agent and be useful in guiding oncologists for the optimization of the therapy strategy for cancer treatment.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: Ann Transl Med Año: 2019 Tipo del documento: Article País de afiliación: China Pais de publicación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: Ann Transl Med Año: 2019 Tipo del documento: Article País de afiliación: China Pais de publicación: China