基于EGFR基因突變狀態(tài)肺腺癌腦轉(zhuǎn)移預后分級模型的建立
發(fā)布時間：2018-12-16 17:16
【摘要】：目的:為更好指導臨床決策及預測預后,美國放射腫瘤協(xié)作組(RTOG)先后建立多個惡性腫瘤腦轉(zhuǎn)移預后分級指數(shù),包括RPA、BSBM、GPA,但是這些預后分級指數(shù)是根據(jù)不同原發(fā)灶來源惡性腦轉(zhuǎn)移瘤而制定,對具體來源的腫瘤腦轉(zhuǎn)移沒有很強針對性。事實上,來源不同的顱腦轉(zhuǎn)移瘤,可能有不同的預后因素,而腫瘤內(nèi)在分子生物學因素也是顱腦轉(zhuǎn)移瘤的預后因素。相關(guān)研究證實,EGFR突變狀態(tài)與NSCLC密切相關(guān),尤其是肺腺癌。我們擬進一步證實EGFR突變狀態(tài)與肺腺癌腦轉(zhuǎn)移患者預后的相關(guān)性,從而根據(jù)EGFR基因突變狀態(tài)制定肺腺癌腦轉(zhuǎn)移預后分級模型。方法:回顧性分析我院304例經(jīng)EGFR基因突變檢測的肺腺癌腦轉(zhuǎn)移患者:1.篩選腦轉(zhuǎn)移的獨立預后因素:Kaplan-Meier法計算患者生存率,各亞組生存率差異比較采用Logrank檢驗,Cox模型進行多因素預后分析。2.建立預后分級模型:根據(jù)多因素分析的結(jié)果中的獨立預后因素,建立新的預后分級模型。3.其預測能力與其他三種已經(jīng)公布的預后分級指數(shù)進行對比。結(jié)果:COX多因素分析顯示EGFR基因突變狀態(tài)(P0.001)與KPS(P0.001)評分為肺腺癌獨立的預后因素。將以上兩因素納入新的預后模型中,根據(jù)文獻描述的方法,利用6個月生存率權(quán)重賦值,根據(jù)累計得分將其分為低、中、高危組。在本組病例中,Logrank檢驗顯示新的預后分級模型與其他三種已知的預后指數(shù)各亞組間均具有統(tǒng)計學差異(P0.001)。新的預后模型的3、6、12月生存率與三種已知的預后分級指數(shù)進行對比,均顯示出明顯優(yōu)越性。此外,新的預后分級模型針對不同治療方式的不同組間也具有明顯統(tǒng)計學差異(P0.001)。結(jié)論:根據(jù)EGFR基因突變狀態(tài)而制定的新的預后分級模型可以用來評估肺腺癌腦轉(zhuǎn)移的預后情況,較其他三種公認的預后分級指數(shù)具有明顯的優(yōu)越性,但還需要未來大量的前瞻性研究進一步證實。
[Abstract]:Objective: in order to better guide clinical decision-making and predict prognosis, the United States radiation oncology cohort (RTOG) successively established several malignant tumor brain metastasis prognosis grading index, including RPA,BSBM,GPA,. However, these prognostic grading indices are based on malignant brain metastases from different primary tumors, and have no strong pertinence for specific tumor metastasis. In fact, different brain metastases may have different prognostic factors, and the intrinsic molecular biological factors are also the prognostic factors of craniocerebral metastases. Related studies confirm that EGFR mutation is closely related to NSCLC, especially lung adenocarcinoma. We intend to further confirm the correlation between the EGFR mutation status and the prognosis of patients with brain metastasis of lung adenocarcinoma, so as to establish the prognosis classification model of brain metastasis of lung adenocarcinoma according to the mutation status of EGFR gene. Methods: a retrospective analysis of 304 patients with brain metastases from lung adenocarcinoma detected by EGFR gene mutation: 1. Screening the independent prognostic factors of brain metastasis: Kaplan-Meier method was used to calculate the survival rate of patients, the difference of survival rate among the subgroups was compared by Logrank test and Cox model was used for multivariate prognostic analysis. 2. To establish a prognostic classification model: according to the independent prognostic factors in the results of multivariate analysis, a new prognostic classification model was established. Its predictive power was compared with three other published prognostic grading indices. Results: COX multivariate analysis showed that EGFR gene mutation status (P0. 001) and KPS score (P0. 001) were independent prognostic factors for lung adenocarcinoma. The above two factors were incorporated into the new prognostic model. According to the method described in the literature, the 6-month survival weight was assigned and divided into low, middle and high risk groups according to the cumulative score. In this study, Logrank test showed that the new prognostic grading model was statistically different from the other three known prognostic indices (P0. 001). Compared with the three known prognostic grading indexes, the 3- and 12- year survival rates of the new prognostic model showed significant advantages. In addition, the new prognostic classification model has significant statistical differences among different treatment groups (P0.001). Conclusion: the new prognostic classification model based on the mutation status of EGFR gene can be used to evaluate the prognosis of brain metastasis of lung adenocarcinoma, which is superior to the other three generally accepted prognostic grading indexes. However, a large number of prospective studies in the future need to be further confirmed.
【學位授予單位】：山西醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R734.2
本文編號：2382752
[Abstract]:Objective: in order to better guide clinical decision-making and predict prognosis, the United States radiation oncology cohort (RTOG) successively established several malignant tumor brain metastasis prognosis grading index, including RPA,BSBM,GPA,. However, these prognostic grading indices are based on malignant brain metastases from different primary tumors, and have no strong pertinence for specific tumor metastasis. In fact, different brain metastases may have different prognostic factors, and the intrinsic molecular biological factors are also the prognostic factors of craniocerebral metastases. Related studies confirm that EGFR mutation is closely related to NSCLC, especially lung adenocarcinoma. We intend to further confirm the correlation between the EGFR mutation status and the prognosis of patients with brain metastasis of lung adenocarcinoma, so as to establish the prognosis classification model of brain metastasis of lung adenocarcinoma according to the mutation status of EGFR gene. Methods: a retrospective analysis of 304 patients with brain metastases from lung adenocarcinoma detected by EGFR gene mutation: 1. Screening the independent prognostic factors of brain metastasis: Kaplan-Meier method was used to calculate the survival rate of patients, the difference of survival rate among the subgroups was compared by Logrank test and Cox model was used for multivariate prognostic analysis. 2. To establish a prognostic classification model: according to the independent prognostic factors in the results of multivariate analysis, a new prognostic classification model was established. Its predictive power was compared with three other published prognostic grading indices. Results: COX multivariate analysis showed that EGFR gene mutation status (P0. 001) and KPS score (P0. 001) were independent prognostic factors for lung adenocarcinoma. The above two factors were incorporated into the new prognostic model. According to the method described in the literature, the 6-month survival weight was assigned and divided into low, middle and high risk groups according to the cumulative score. In this study, Logrank test showed that the new prognostic grading model was statistically different from the other three known prognostic indices (P0. 001). Compared with the three known prognostic grading indexes, the 3- and 12- year survival rates of the new prognostic model showed significant advantages. In addition, the new prognostic classification model has significant statistical differences among different treatment groups (P0.001). Conclusion: the new prognostic classification model based on the mutation status of EGFR gene can be used to evaluate the prognosis of brain metastasis of lung adenocarcinoma, which is superior to the other three generally accepted prognostic grading indexes. However, a large number of prospective studies in the future need to be further confirmed.
【學位授予單位】：山西醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R734.2
【參考文獻】
中國期刊全文數(shù)據(jù)庫 前1條
1 曹進;曾川;范衛(wèi)東;張獻全;;2016年ASCO會議肺癌靶向治療的相關(guān)進展[J];中華肺部疾病雜志(電子版);2016年04期
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