發(fā)布時間：2018-08-13 15:42

【摘要】：胃癌是最常見的消化道腫瘤之一。胃癌的發(fā)生與飲食生活習慣密切相關。血清胃功能,包括血清胃泌素-17和胃蛋白酶原,在西方國家又稱為GastroPanel,常用于無創(chuàng)的胃癌篩查,但篩查效能存在爭議。通過基于院內(nèi)人群的大樣本、連續(xù)病例的全國多中心橫斷面研究,進行了胃癌危險因素的調(diào)查與分析,分析了血清胃功能與胃癌的相關性,確立了血清胃功能指標用于胃癌篩查的最佳界限值,建立了基于胃癌危險因素和血清胃功能指標的胃癌風險預測模型及評分系統(tǒng),初步探索出胃癌篩查策略。一、胃癌危險因素調(diào)查及分析(一)研究目的進行胃癌危險因素調(diào)查,較全面分析飲食、生活習慣和代謝綜合征等因素與胃癌的相關性,為建立胃癌發(fā)生風險預測模型提供依據(jù)。(二)研究方法基于院內(nèi)人群的橫斷面研究。采用問卷調(diào)查方式,調(diào)查研究對象諸如飲食、生活習慣及代謝綜合征等胃癌危險因素。所有研究對象均按照問卷調(diào)查、抽血化驗和胃鏡精查等流程操作。以胃鏡及病理診斷作為最后診斷的金標準,本研究共納入病例12961例,包括非胃癌組12637例和胃癌組324例。采用logistic回歸和卡方檢驗等統(tǒng)計方法進行分析。(三)結(jié)果1、病例特征本研究共入組病例12961例,包括非胃癌組12637例和胃癌組324例。非胃癌組包括非萎縮性胃炎5401例、萎縮性胃炎2950例(其中低級別上皮內(nèi)瘤變282例)和其他診斷(包括消化性潰瘍、反流性食管炎和胃息肉等)4286例。胃癌組包括早期胃癌127例(39.20%)和進展期胃癌197例(60.80%)。平均年齡為57.29±9.628。女性和男性病例分別為6545例(50.5%)和6416例(49.5%)。有癥狀和無癥狀的患者分別為10571例(81.6%)和2390例(18.4%)。2、胃癌危險因素的單因素分析本研究結(jié)果表明,男性、高齡、吸煙、飲酒、經(jīng)常攝入隔夜菜、飲食偏咸、經(jīng)常攝入腌煎熏制食品和體重指數(shù)偏瘦是胃癌高危因素,經(jīng)常攝入新鮮蔬菜水果是胃癌的保護因素。胃癌發(fā)生風險隨著年齡增大而增大。飲酒習慣是胃癌發(fā)生的高危因素,且隨著飲酒量和飲酒年數(shù)增加而增加。對于女性人群糖尿病和高甘油三酯人群胃癌檢出率較高,但差異無統(tǒng)計學意義,因此代謝綜合征與胃癌相關性并不顯著。3、胃癌危險因素的多因素分析經(jīng)多因素logistic回歸分析后,性別、年齡、體重指數(shù)、飲食咸淡習慣、煎炸食品攝入、腌制食品攝入是胃癌危險因素,新鮮水果攝入為胃癌保護因素。logistic回歸模型的擬合優(yōu)度和區(qū)分度良好。roc曲線下面積為0.737(95%ci:0.708-0.766)(p0.001)。(四)小結(jié)本研究通過大規(guī)模流行病學調(diào)查,較全面分析了飲食、生活習慣與胃癌的相關性,初步探討了代謝綜合征與胃癌相關性。經(jīng)多因素logistic回歸分析可知,男性、高齡、偏瘦、飲食偏咸、經(jīng)常攝入腌制食品、經(jīng)常攝入煎炸食品是胃癌危險因素,經(jīng)常攝入新鮮水果是胃癌保護因素。二、血清胃功能與胃癌相關性及篩查效能分析(一)研究目的探討血清胃功能與胃癌相關性,確定血清胃功能用于胃癌篩查的界限值,評估血清胃功能用于胃癌篩查的效能。(二)研究方法基于院內(nèi)人群的橫斷面研究。用elisa法空腹檢測血清胃功能(包括血清胃泌素-17、胃蛋白酶原Ⅰ和胃蛋白酶原Ⅱ等),然后行胃鏡精查及活檢。以胃鏡及病理診斷作為金標準,納入病例12961例,包括非萎縮性胃炎5401例、萎縮性胃炎2950例(其中低級別上皮內(nèi)瘤變282例)、早期胃癌127例、進展期胃癌197例和其他診斷4286例。采用非參數(shù)檢驗、卡方檢驗、roc曲線下面積分析和logistic回歸分析等多種統(tǒng)計方法。(三)結(jié)果1、血清胃功能與胃癌相關性分析與非胃癌組相比,胃癌組的血清胃泌素-17水平較高,血清胃蛋白酶原Ⅱ較高,而pgr較低;與非萎縮性胃炎組相比,萎縮性胃炎組血清胃蛋白酶原Ⅰ和pgr較低。2、血清胃功能對胃癌的篩查效能分析血清胃泌素-17、胃蛋白酶原Ⅱ和pgr是篩查胃癌的可靠血清學指標,三者的roc曲線下面積分別為0.621(95%ci:0.593-0.649)、0.622(95%ci:0.592-0.652)和0.643(95%ci:0.611-0.675)(p值0.001),最佳診斷界限值分別為3.61pmol/l、12.00ug/l和9.42。血清胃功能單項診斷中,血清胃泌素-17的敏感度最高(70.1%),而pgr的特異度最高(65.3%)。血清胃泌素-17診斷胃癌的敏感度、特異度、陽性預測值、陰性預測值、準確度分別為70.1%(227/324)、51.4%(6499/12637)、3.6%(227/6365)、98.5%(6499/6596)和51.89%(6726/12961)。血清胃蛋白酶原Ⅱ診斷胃癌的敏感度、特異度、陽性預測值、陰性預測值和準確度分別為58.6%(190/324)、62.5%(7892/12637)、3.9%(190/4935)、98.3%(7892/8026)和63.96%(8082/12961)。pgr診斷胃癌的敏感度、特異度、陽性預測值、陰性預測值、準確度分別為58.3%(189/324)、65.3%(8257/12637)、4.1%(189/4569)、98.4%(8257/8392)和64.65%(8446/12961)。血清胃功能聯(lián)合診斷中,血清胃泌素-17聯(lián)合pgr的診斷效能較好。當s-g-17聯(lián)合pgr(即s-g-173.61pmol/l且pgr9.42)診斷胃癌時,敏感度、特異度、陽性預測值、陰性預測值和準確度分別為44.1%(143/324)、77.0%(9736/12637)、4.7%(143/3044)、98.2%(9736/9917)和76.22%(9879/12961)。當s-g-17聯(lián)合pgⅡ(即s-g-173.61pmol/l且pgⅡ12ug/l)診斷胃癌時,敏感度、特異度、陽性預測值、陰性預測值和準確度分別為43.5%(141/324)、73.0%(9230/12637)、4.0%(141/3548)、98.1%(9230/9413)和72.3%(9371/12961)。3、血清胃功能對預測胃癌發(fā)生風險的評價由胃泌素-17和胃蛋白酶原聯(lián)合的血清胃功能abc法,可以預測胃癌發(fā)生風險,篩選出胃癌高危人群。把pgr9.42視為pgr陽性(+),pgr≥9.42視為pgr陰性(-);把s-g-173.61pmol/l視為g-17陽性(+),s-g-17≤3.61pmol/l視為g-17陰性(-)。根據(jù)上述判斷標準,所有研究對象依據(jù)血清胃功能結(jié)果分為a、b和c三組,a組為血清胃功能雙陰性,b組為血清胃功能單陽性,c組為血清胃功能雙陽性。分析結(jié)果表明,a、b和c三組的胃癌檢出率分別為1.0%(51/5071)、2.7%(130/4846)和4.7%(143/3044);各組的胃癌發(fā)生風險從a組至c組依次增加,其中a組的胃癌發(fā)生風險最低而c組的胃癌發(fā)生風險最高。與a組相比,b組、c組兩組的胃癌發(fā)生風險or值分別為2.532(95%:1.823-3.515)和4.392(95%:3.171-6.084)(p值0.001)。(四)小結(jié)通過大樣本、連續(xù)病例的橫斷面研究,確定了針對院內(nèi)人群血清胃功能篩查胃癌的最佳界限值,提出了預測胃癌發(fā)生風險的血清胃功能abc法。本研究結(jié)果表明,血清胃泌素-17、胃蛋白酶原Ⅱ和pgr是篩查胃癌的可靠血清學指標,血清胃泌素-17聯(lián)合pgr篩查胃癌的效能最佳;血清胃功能abc法可以篩查出胃癌高危人群,c組發(fā)生胃癌風險最大。三、基于胃癌危險因素和血清胃功能的胃癌發(fā)生風險預測模型及其評分系統(tǒng)的建立(一)研究目的結(jié)合胃癌危險因素和血清胃功能指標建立胃癌發(fā)生風險預測模型及其評分系統(tǒng),評估其篩查效能。(二)研究方法以胃鏡及病理診斷作為金標準,本研究共納入病例12961例,包括非胃癌組12637例和胃癌組324例。以胃癌危險因素分析為基礎,結(jié)合血清胃功能指標,進行多因素logistic回歸分析,建立胃癌發(fā)生風險預測模型及其評分系統(tǒng),采用roc曲線下面積評估其對胃癌的篩查效能。最后通過后期入組人群對評分系統(tǒng)的準確性進行驗證,驗證人群共納入病例918例,包括非胃癌組893例和胃癌組25例。(三)結(jié)果1、基于性別、年齡和血清胃功能的胃癌發(fā)生風險預測模型的建立由性別、年齡、s-g-17(≥3.61pmol/l)和pgr(9.42)四個因素建立的logistic回歸模型,可以提高血清胃功能對于胃癌的篩查效能。此時的roc曲線下面積為0.754(95%ci:0.729-0.780),敏感度、特異度、陽性預測值、陰性預測值和準確度分別為82.4%(267/324)、56.2%(7106/12637)、4.6%(267/5798)、99.2%(7106/7163)和56.89%(7373/12961)。2、基于多個胃癌危險因素和血清胃功能的胃癌發(fā)生風險預測模型及其評分系統(tǒng)的建立與篩查效能評價由性別、年齡、體重指數(shù)、飲食咸淡習慣、腌制食品攝入、煎炸食品攝入、水果攝入、S-G-17(≥3.61pmol/L)和PGR(9.42)等9個胃癌危險因素建立的logistic回歸胃癌發(fā)生風險預測模型,血清胃功能篩查效能又可以進一步提高。此時ROC曲線下面積為0.777(95%CI:0.751-0.802),敏感度、特異度、陽性預測值、陰性預測值和準確度分別為68.8%(223/324)、73.6%(9303/12637)、6.3%(223/3557)、98.9%(9303/9404)和73.50%(9526/12961)。根據(jù)logistic回歸分析中各因素的OR值賦予分值,建立胃癌風險預測評分系統(tǒng)。該評分系統(tǒng)得分范圍為0~24分,ROC曲線下面積為0.775(95%CI:0.749-0.800)。以11分作為界限值,將研究對象劃分為胃癌低風險人群和高風險人群。高風險(11-24分)人群中胃癌檢出率為5.5%(234/4255),顯著高于低風險(0-10分)人群中胃癌檢出率1.0%(90/8706)。若總評分以11分作為界限值,則評分系統(tǒng)對胃癌診斷的敏感度、特異度、陽性預測值、陰性預測值和準確度分別為72.2%(234/324)、68.2%(8616/12637)、5.5%(234/4255)、99.0%(8616/8706)和68.28%(7373/12961)。驗證人群包括非胃癌組893例和胃癌組25例。按照胃癌發(fā)生風險評分系統(tǒng)標準,計算驗證病例風險分值,最終總分值范圍為0~20分,ROC曲線下面積為0.683(95%CI:0.583-0.783)。以11分作為界限值,驗證人群分為胃癌低風險人群(0-10分)和高風險人群(11-20分),后者胃癌檢出率明顯高于前者(5.1%vs1.6%)。若總得分以11分作為界限值,則評分系統(tǒng)對胃癌診斷的敏感度、特異度、陽性預測值、陰性預測值和準確度分別為60.0%(15/25)、68.6%(613/893)、5.1%(15/295)、99.0%(613/623)和68.4%(628/918),與建模人群一致。(四)小結(jié)基于胃癌危險因素和血清胃功能指標建立的胃癌發(fā)生風險預測模型及評分系統(tǒng),可以較好的預測院內(nèi)人群胃癌發(fā)生風險,篩查出胃癌高危人群,節(jié)約醫(yī)療成本,提高早期胃癌診斷率。
[Abstract]:Gastric cancer is one of the most common cancers of the digestive tract.The occurrence of gastric cancer is closely related to dietary habits.Serum gastric function, including serum gastrin-17 and pepsinogen, is often used in noninvasive screening of gastric cancer in Western countries. A national multicenter cross-sectional study was conducted to investigate and analyze the risk factors of gastric cancer. The correlation between serum gastric function and gastric cancer was analyzed. The optimal limit value of serum gastric function index for screening gastric cancer was established. The risk prediction model and scoring system of gastric cancer based on the risk factors of gastric cancer and serum gastric function index were established. To find out the screening strategy for gastric cancer. First, to investigate and analyze the risk factors of gastric cancer. (1) To investigate the risk factors of gastric cancer, and to analyze the correlation between diet, lifestyle and metabolic syndrome and gastric cancer, so as to provide a basis for establishing a risk prediction model for gastric cancer. (2) Research methods based on cross-sectional study of hospital population. Methods: A questionnaire survey was conducted to investigate the risk factors of gastric cancer such as diet, living habits and metabolic syndrome. All the subjects followed the procedures of questionnaire survey, blood sampling test and gastroscopy. With gastroscopy and pathological diagnosis as the gold standard for final diagnosis, 12961 cases were included, including 12 cases of non-gastric cancer. 637 cases and 324 cases of gastric cancer group were analyzed by logistic regression and chi-square test. (3) Results 1. There were 12961 cases in this study, including 12637 cases in non-gastric cancer group and 324 cases in gastric cancer group. Other diagnoses (including peptic ulcer, reflux esophagitis, gastric polyp, etc.) included 4286 cases. The gastric cancer group included 127 cases (39.20%) of early gastric cancer and 197 cases (60.80%) of advanced gastric cancer. The average age was 57.29 [9.628]. The female and male cases were 6545 (50.5%) and 6416 (49.5%) respectively. 390 cases (18.4%). 2. Univariate analysis of risk factors for gastric cancer showed that male, old age, smoking, drinking, overnight vegetable intake, salty diet, frequent intake of pickled and smoked foods and lean body mass index were high risk factors for gastric cancer, and frequent intake of fresh vegetables and fruits were protective factors for gastric cancer. Drinking habit is a high risk factor for gastric cancer, and it increases with the increase of alcohol consumption and years of drinking. For women with diabetes and high triglycerides, the detection rate of gastric cancer is higher, but there is no significant difference, so the correlation between metabolic syndrome and gastric cancer is not significant. 3. Multivariate analysis of gastric cancer risk factors. After multivariate logistic regression analysis, sex, age, body mass index, salty eating habits, fried food intake, pickled food intake were risk factors for gastric cancer, fresh fruit intake was protective factors for gastric cancer. The goodness of fit and discrimination of logistic regression model were good. The area under ROC curve was 0.737 (95% ci: 0.708-0.766) (p0.001). (4) Summary Through a large-scale epidemiological survey, this study comprehensively analyzed the relationship between diet, living habits and gastric cancer, and preliminarily explored the relationship between metabolic syndrome and gastric cancer. Fresh fruit intake is a protective factor for gastric cancer. 2. Correlation between serum gastric function and gastric cancer and analysis of screening efficacy (1) To explore the relationship between serum gastric function and gastric cancer, to determine the threshold value of serum gastric function for gastric cancer screening, and to evaluate the effectiveness of serum gastric function in gastric cancer screening. (2) Research methods based on the hospital population. Cross-sectional study. Gastric function in serum (including serum gastrin-17, pepsinogen I and pepsinogen II) was measured by ELISA on an empty stomach. Gastroscopy and biopsy were performed. 12961 cases, including 5401 cases of non-atrophic gastritis and 2950 cases of atrophic gastritis (including low-grade intraepithelial neoplasia) were included by gastroscopy and pathological diagnosis as gold standard. There were 282 cases of gastric cancer, 127 cases of early gastric cancer, 197 cases of advanced gastric cancer and 4286 cases of other diagnoses. Serum pepsinogen_and PGR were lower in atrophic gastritis group than in non-atrophic gastritis group. serum pepsinogen_and PGR were lower in atrophic gastritis group. 95% ci: 0.593-0.649, 0.622 (95% ci: 0.592-0.652) and 0.643 (95% ci: 0.611-0.675) (p value 0.001), respectively. The best diagnostic limits were 3.61 pmol/l, 12.00 ug/l and 9.42. The sensitivity of serum gastrin-17 was the highest (70.1%) and the specificity of PGR was the highest (65.3%). The positive predictive value and negative predictive value were 70.1% (227/324), 51.4% (6499/12637), 3.6% (227/6365), 98.5% (6499/6596) and 51.89% (6726/12961), respectively. 3% (7892 / 8026) and 63.96% (8082 / 12961). The sensitivity, specificity, positive predictive value and negative predictive value of PGR were 58.3% (189 / 324), 65.3% (8257 / 12637), 4.1% (189 / 4569), 98.4% (8257 / 8392) and 64.65% (8446 / 12961) respectively. In the combined diagnosis of serum gastrin-17 and pgr, the diagnostic efficacy was better. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 44.1% (143 / 324), 77.0% (9736 / 12637), 4.7% (143 / 3044), 98.2% (9736 / 9917) and 76.22% (9879 / 12961) respectively in the diagnosis of gastric cancer. Heterogeneity, positive predictive value, negative predictive value and accuracy were 43.5% (141/324), 73.0% (9230/12637), 4.0% (141/3548), 98.1% (9230/9413) and 72.3% (9371/12961) respectively. Serum gastric function ABC combined with gastrin-17 and pepsinogen could predict the risk of gastric cancer. PGR 9.42 was regarded a s PGR positive (+), PGR > 9.42 a s PGR negative (-), s-g-173.61 pmol / L A s G-17 positive (+), S-G-17 < 3.61 pmol / L A s G-17 negative (-). According to the above criteria, a l l the subjects were divided into three groups according to the results of serum gastric function: a, B and c, group A was serum gastric function double negative, group B was serum gastric function negative. The results showed that the detection rates of gastric cancer in group a, B and C were 1.0% (51/5071), 2.7% (130/4846) and 4.7% (143/3044), respectively. The risk of gastric cancer in each group increased from group A to group c, with the lowest risk of gastric cancer in group A and the highest risk of gastric cancer in group C. The OR values of gastric cancer risk in the two groups were 2.532 (95%:1.823-3.515) and 4.392 (95%:3.171-6.084) (p value 0.001). (4) Summarize the best threshold of serum gastric function screening for gastric cancer in hospital population by cross-sectional study of large sample and consecutive cases. The results showed that serum gastrin-17, pepsinogen II and PGR were reliable serum markers for screening gastric cancer, and serum gastrin-17 combined with PGR was the best for screening gastric cancer; ABC method of serum gastric function could screen high-risk group of gastric cancer, and group C had the greatest risk of gastric cancer. 3. gastric cancer based on risk factors of gastric cancer and serum gastric function had wind Establishment of risk prediction model and scoring system (1) Objective To establish a risk prediction model and scoring system for gastric cancer in combination with risk factors of gastric cancer and serum gastric function indicators, and to evaluate its screening effectiveness. (2) Gastroscopy and pathological diagnosis were used as gold standard in the study. A total of 12961 cases, including 12637 cases of non-gastric cancer, were included. Based on the analysis of risk factors of gastric cancer, combined with serum gastric function index, a multivariate logistic regression analysis was conducted to establish a risk prediction model and a scoring system for gastric cancer. The area under the ROC curve was used to evaluate the screening efficacy for gastric cancer. Finally, the accuracy of the scoring system was assessed by the later grouping population. Results 1. Establishment of a logistic regression model based on sex, age, S-G-17 (> 3.61 pmol/l) and PGR (9.42) could improve the serum gastric function. The area under the ROC curve was 0.754 (95% ci: 0.729-0.780), sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 82.4% (267/324), 56.2% (7106/12637), 4.6% (267/5798), 99.2% (7106/7163) and 56.89% (7373/12961) respectively, based on multiple risk factors and serum gastric function. Establishment of risk prediction model and scoring system and evaluation of screening efficacy were based on nine risk factors including sex, age, body mass index, salty eating habits, pickled food intake, fried food intake, fruit intake, S-G-17 (>3.61 pmol/L) and PG (9.42) for gastric cancer, serum gastric function. The area under the ROC curve was 0.777 (95% CI: 0.751-0.802), sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 68.8% (223/324), 73.6% (9303/12637), 6.3% (223/3557), 98.9% (9303/9404) and 73.50% (9526/12961) respectively. The scoring system ranged from 0 to 24 and the area under the ROC curve was 0.775 (95% CI: 0.749-0.800). The subjects were divided into low-risk group and high-risk group with 11 points as the threshold value. The detection rate of gastric cancer in high-risk group (11-24 points) was 5.5% (234/4255), significantly higher than that in low-risk group (95% CI: 0.749-0.800). The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the scoring system for gastric cancer were 72.2% (234/324), 68.2% (8616/12637), 5.5% (234/4255), 99.0% (8616/8706) and 68.28% (7373/12961) respectively. According to the criteria of gastric cancer risk scoring system, the final total score ranged from 0 to 20, and the area under the ROC curve was 0.683 (95% CI: 0.583-0.783). With 11 as the threshold, the validated population was divided into low-risk group (0-10 points) and high-risk group (11-20 points). The latter was screened for gastric cancer. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the scoring system were 60.0% (15/25), 68.6% (613/893), 5.1% (15/295), 99.0% (613/623) and 68.4% (628/918), respectively, if the total score was 11 as the threshold value. The risk prediction model and scoring system of gastric cancer based on risk factors and serum gastric function index can better predict the risk of gastric cancer in hospital population, screen out the high risk group of gastric cancer, save medical cost and improve the diagnostic rate of early gastric cancer.
【學位授予單位】：第二軍醫(yī)大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：R735.2

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