本文選題：膠質(zhì)母細(xì)胞瘤 + 預(yù)后因子　； 參考：《浙江大學(xué)》2017年碩士論文

【摘要】：背景:膠質(zhì)母細(xì)胞瘤是中樞神經(jīng)系統(tǒng)中惡性程度最高、預(yù)后最差的腫瘤之一,最大程度腫瘤切除及術(shù)后同步放化療為現(xiàn)階段的標(biāo)準(zhǔn)治療方案,但不同患者的預(yù)后存在較大差異,且目前為止仍未發(fā)現(xiàn)決定患者預(yù)后的核心因素。膠質(zhì)母細(xì)胞瘤的異質(zhì)性可能是造成預(yù)后差異的重要原因。因此,不同因素之間的交互效應(yīng)可能對預(yù)后產(chǎn)生顯著的作用。目的:驗證目前已發(fā)現(xiàn)的膠質(zhì)母細(xì)胞瘤預(yù)后相關(guān)因素;尋找并解讀因素間交互效應(yīng);最終為膠質(zhì)母細(xì)胞瘤個體化治療方案的制定提供依據(jù)。方法:連續(xù)性地收集浙一醫(yī)院2009年4月至2015年4月間住院治療的66例膠質(zhì)母細(xì)胞瘤病例。收集患者一般資料如性別、起病時年齡、基礎(chǔ)疾病情況、確診年份等;患者術(shù)前卡氏評分、癥狀、起病至手術(shù)時間間隔、腫瘤部位、手術(shù)治療情況、術(shù)后并發(fā)癥、放化療、復(fù)發(fā)時間、復(fù)發(fā)后治療、影像學(xué)表現(xiàn)、腫瘤分子標(biāo)記物、術(shù)后生存期等。采用Cox比例風(fēng)險模型進(jìn)行單因素、多因素以及交互效應(yīng)分析。結(jié)果:與膠質(zhì)母細(xì)胞瘤總體生存期相關(guān)的獨立危險因素包括腫瘤定位于額葉[HR(95%CI):0.339(0.185-0.622),P0.001;adjusted:0.186(0.059-0.586),P=0.004]、腫瘤完全切除[HR(95%CI):0.391(0.166-0.923),P=0.032;ad justed:0.110(0.020-0.610),P=0.012]、復(fù)發(fā)后積極治療[HR(95%CI):0.321(0.118-0.871),P=0.026;adjusted:0.229(0.060-0.878),P=0.032]。與膠質(zhì)母細(xì)胞瘤無進(jìn)展生存期相關(guān)的獨立危險因素主要為腫瘤定位于額葉[HR(95%CI):0.412(0.227-0.748),P=0.004;adjusted:0.382(0.172-0.850),P=0.018]。除廣泛的二階交互效應(yīng)網(wǎng)絡(luò)外,復(fù)發(fā)后治療、前額葉腫瘤、術(shù)前卡氏評分之間存在顯著的三階交互效應(yīng)(HR:0.957,95%CI:0.920-0.996,P=0.030)。結(jié)論:因素間交互效應(yīng)與膠質(zhì)母細(xì)胞瘤的預(yù)后存在相關(guān)性,提示可基于交互效應(yīng)進(jìn)行膠質(zhì)母細(xì)胞瘤預(yù)后評估、指導(dǎo)個體化治療方案制定。
[Abstract]:Background: glioblastoma is one of the most malignant tumors with the worst prognosis in the central nervous system. So far, no core factors have been found to determine the prognosis of patients. The heterogeneity of glioblastoma may be an important reason for the difference of prognosis. Therefore, the interaction between different factors may play a significant role in prognosis. Objective: to verify the prognostic factors of glioblastoma, to find out the interaction between the factors, and to provide the basis for the individual treatment of glioblastoma. Methods: 66 cases of glioblastoma were collected from April 2009 to April 2015 in Zhejiang first Hospital. Collect general data of patients such as gender, age at onset, condition of underlying disease, year of diagnosis, etc. The patients had preoperative Karnox score, symptoms, time interval between onset and operation, tumor location, surgical treatment, postoperative complications, radiotherapy and chemotherapy, etc. Recurrence time, post-recurrence therapy, imaging findings, tumor molecular markers, postoperative survival time, etc. Cox proportional hazard model was used to analyze single factor, multi factor and interaction effect. 緇撴灉:涓庤兌璐ㄦ瘝緇嗚優(yōu)鐦ゆ，

本文編號：2111084