2014-05-012024-05-13https://scholars.lib.ntu.edu.tw/handle/123456789/649880摘要：相較於西方國家, 台灣婦女癌症臨床及流行病學上呈現特殊的疾病型態，有必要研究分析這現象的生物分子機轉，進而發展獨特的預防、診斷、及治療的策略。我們提出一個前瞻性的計畫來建構一個技術及管理平台 -台灣婦女癌症研究網路。本研究網路將提供足夠的檢體數、品質良好的生物檢體及完整的疾病相關資料，以期加速相關研究的進展及增進生技醫學的競爭力。 本網路將有 9到 11家醫學中心参加，用以募集北、中及南部不同社經、族群和生活型態的婦癌病患。這個三期年計畫將募集約 1000位原位及侵襲性子宮頸癌、1200位子宮體癌、1000位卵巢癌、及 350位乳癌病患，收集病人的生物檢體(組織、血液、及腹水)及登錄、追蹤病理診斷、治療過程、治療反應以及預後資料，並利用問卷訪視收集癌症相關危險因子，生活品質、睡眠及活動量表。本資料庫的組織架構包含合作醫院、中央資料庫、管理中心、及使用者委員會。各醫院的運作模式將遵循共同的規範及標準程序，生物檢體將儲存於各醫院，疾病相關資料將藉由電腦傳輸集中保存於中央資料庫。管理中心將負責建立本網路運作的各類標準作業流程、人員訓練、提供問題的解決方法、與各合作醫院溝通及訊息交流。使用者委員會審核檢體、臨床，及流行病學資料的申請案，並監督檢體使用的正確及公平性。 本資料庫的組織架構、運作模式及前置作業已逐步建構完成，目前有臺大醫院、奇美醫院及臺北榮總等三家醫院進行計畫前導測試，收集檢體及、臨床與流行病學相關資料。另有 8家醫院已經完成所屬醫院的倫委會審查程序，在計畫確認獲得通過後，可以開始進行收案的工作。另外兩家醫院的倫委會正在審查，預計在計畫第二年可加入收案的工作。本資料庫收集的生物檢體和疾病相關資料開放研究者使用，以協助增進研究的效率及推論的正確性，以期在婦癌相關研究上有更完整和突破性的進展。<br> Abstract: The epidemiological and clinical pattern of gynecologic cancers is unique, and this has triggered significant impacts on women’s health in Taiwan. However, the underlying cause of the phenomenon has not been well identified. Although, advance of genomic research has developed new understanding of biomolecular mechanisms of gynecologic cancers, the access to a wide collection of biospecimens coupled with epidemiological and clinical data for a valid genomic research is limited. To offer high-quality biosamples with comprehensive data of clinical phenotype, risk factors, clinical treatments, follow-up data of treatment effects and vital status. The research group has constructed a technology and management platform - the Taiwan Gynecologic Cancer Network to support clinical, molecular, epidemiological, and translational researches. The network is constituted by a uni-management center with multiple participating hospitals. Currently, three hospitals (National Taiwan University Hospital, Chi Mei Medical Center, and Taipei Veterans General Hospital) are in the network, and the sample collection is initiated and continuing. The network will maintain 9 to 11 co-operating hospitals. To collect more representative patients of gynecologic cancers with various ethnics, environmental and socioeconomic background, and life styles, we will select hospital in northern, central and southern Taiwan to join the network. Overall, the network plans to collect carcinoma in situ and invasive cervical cancer, uterine cancer, ovarian cancers and breast cancer, the expected case numbers are 1500, 1000, 1000, and 150 cases; respectively. The biospecimens in network includes tissues, plasma, peripheral blood mononucleated cells, and ascites. All the biospecimens will be stockpiled in each participating hospital without centralization, and will be provided to the applicants by random selection. Clinical information and patient self-reported data in the network include diagnosis, disease status , stage, medical history, family history of cancers and chronic diseases, menstrual history, hormone use, physical activity, quality of life and other disease relevant factors. A globally unique identification number transformed from several unique identifiers of each participant by a highly protected system is used for the storage of biosamples and information. Web base information system is applied for data collection and storage, administration, and biosample management. Also, the website (https://100sb204.cims.tw/) work as an interface between the Taiwan Gynecologic Cancer Network and researchers intending to apply the tissues and/or associated information. Also, it is a platform for applicants, management center and user committee to communicate with each other, and complete the application procedure. The network will play an essential role to tie chains of drug discovery together to support NRPB programs and pharmaceutical industries. The representative biosamples and comprehensive disease relevant data are able to discover previous unseen patterns in both pre-clinical and clinical research. The integration of biosample and data helps elucidate the link between genotype and phenotype, and control the confounding factors to construct valid studies. Additionally, biosamples with high quantity of biosamples in biobank shortens the time to collect statistically meaningful sample size. For clinical trial, the comprehensive disease relevant data in the network help make an accurate trial strategy. Additionally, in the future the infrastructure and the connection of the network can work as a management platform to facilitate multicenter clinical trials.