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《中华消化外科杂志》2019年4月第18卷第4期论著

空腹血糖与肝癌发病关系的多中心回顾性研究(附94 264例报告)

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引用本文:
刘通1,刘海2,金鹏飞3,等.空腹血糖与肝癌发病关系的多中心回顾性研究(附94 264例报告)[J].中华消化外科杂志,2019,18(4):348-357.DOI:10.3760/cma.j.issn.1673-9752.2019.04.010.
【摘要】

目的:探讨空腹血糖对肝癌发病的影响。
方法:采用回顾性队列研究方法。收集2006年 7月至2015年12月由华北理工大学附属开滦总医院、开滦林西医院、开滦赵各庄医院、开滦唐家庄医院、开滦范各庄医院、开滦荆各庄医院、开滦吕家坨医院、开滦林南仓医院、开滦钱家营医院、开滦马家沟医院、开滦医院分院行健康体检的94 264例受试者的体检资料;男75 134例,女19 130例;年龄为(51±12)岁,年龄范围为18~98岁。依据受试者空腹血糖三分位水平将其分为3组:31 083例受试者空腹血糖<4.82 mmol/L设为T1组,31 594例受试者4.82 mmol/L≤空腹血糖<5.49 mmol/L设为T2组,31 587例受试者空腹血糖≥5.49 mmol/L设为T3组。由固定医师团队于2006、2008、2010、2012、2014年在相同地点按相同健康体检顺序对受试者进行5次健康体检。收集流行病学调查内容、人体测量学及实验室检查指标。观察指标:(1)3组受试者的临床特征比较。(2)受试者随访和肝癌的发病情况。(3)受试者非肝癌相关死亡情况。(4)影响受试者新发肝癌的危险因素分析。(5)空腹血糖对肝癌模型预测价值的比较。(6)竞争风险模型分析空腹血糖对新发肝癌的影响。采用健康体检的方式进行随访,随访内容为肝癌新发病情况和患者生存情况。以2006年首次健康体检时间作为随访的起始时间,随访终止事件为发生肝癌、失访、死亡,随访时间截至2015年12月31日。正态分布的计量资料以Mean±SD表示,多组间比较采用单因素方差分析。偏态分布的计量资料以M(范围)表示,多组间比较采用KruskalWallis秩和检验。计数资料以绝对数和百分比表示,组间比较采用x2检验。采用Kaplan-Meier法计算累积发病率和累积死亡率,并绘制发病曲线,累积发病率和累积死亡率的组间比较采用Log-rank法检验。采用人年发病率(发病密度)计算不同空腹血糖水平受试者肝癌发病情况。采用COX比例风险模型分析不同空腹血糖水平(连续变量和分类变量)对新发肝癌的风险比(HR)和95%可信区间。使用限制性立方样条曲线(RCS)计算连续变化的空腹血糖和肝癌发病风险的剂量反应关系。使用似然比检验和赤池信息量准则(AIC)计算空腹血糖对肝癌预测模型拟合情况的影响。使用C统计量计算不同模型的预测能力。使用竞争风险模型中的部分分布风险函数(SD)和原因别风险函数(CS)分析空腹血糖影响肝癌发病的净效应值。
结果:(1)3组受试者的临床特征比较:T1组受试者男性、年龄、收缩压、舒张压、腰围、体质量指数、总胆固醇、丙氨酸氨基转移酶、三酰甘油、饮酒、吸烟、体育锻炼、乙型肝炎病毒表面抗原阳性、脂肪肝分别为23 567例、(51±13)岁、(128±21)mmHg(1mmHg=0.133 kPa)、(82±12)mmHg、(86±10)cm、(24±3)kg/m2、(4.8±1.2)mmol/L、17.12 U/L(12.21~24.01 U/L)、1.18 mmol/L(0.82~1.75 mmol/L)、5 080例、9 423例、4 779例、724例、7 591例;T2组分别为24 870例、(50±12)岁、(129±20)mmHg、(83±12)mmHg、(86±10)cm、(25±3)kg/m2、(4.9±1.1)mmol/L、18.31 U/L(13.01~24.31 U/L)、1.23 mmol/L(0.88~1.83 mmol/L)、5 448例、9 397例、4 570例、619例、 9 009例;T3组分别为26 697例、(53±11)岁、(135±22)mmHg、(86±12)mmHg、(89±10)cm、(26±3)kg/m2、(5.1±1.2)mmol/L、19.00 U/L(13.79~26.61 U/L)、1.44 mmol/L(1.00~2.21 mmol/L)、6 354例、10 292例、 5 369例、608例、13 397例;3组上述指标比较,差异均有统计学意义(x2=761.68,F=417.84,1 010.71,747.64,702.73,1 075.06,703.83, x2=447.44,2 109.38,165.97,66.69,78.90,15.50,2 576.95,P<0.05)。(2)受试者随访和肝癌的发病情况:94 264例受试者总随访时间为817 475人年,肝癌发病密度为3.71/ 10 000人年。女性受试者肝癌发病密度为1.13/10 000人年,男性受试者为4.37/10 000人年。T1组、 T2组、T3组受试者肝癌的发病密度分别为2.84/10 000人年、3.64/10 000人年、4.64/10 000人年;累积发病率分别为2.76‰、3.90‰、4.90‰,3组累积发病率比较,差异有统计学意义(x2=11.95,P<0.05)。T1组与T2组受试者的累积发病率比较,差异无统计学意义(x2=2.73,P>0.05);T3组分别与T1组、T2组受试者累积发病率比较,差异均有统计学意义(x2=11.56,4.10,P<0.05)。(3)受试者非肝癌相关死亡情况: 94 264例受试者随访期间,非肝癌相关死亡6 880例,非肝癌相关死亡密度为84.16/10 000人年。T1组、T2组、T3组受试者非肝癌相关死亡密度分别为79.19/10 000人年、68.17/10 000人年、105.32/10 000人年;累积死亡率分别为78.90‰、67.80‰、104.40‰,3组累积死亡率比较,差异有统计学意义(x2= 1 231.46,P<0.05)。T1组分别与T2组、T3组受试者累积死亡率比较,差异均有统计学意义(x2=5.29,4.36,P<0.05);T2组与T3组受试者累积死亡率比较,差异无统计学意义(x2=0.09,P>0.05)。(4)影响受试者新发肝癌的危险因素分析。COX比例风险模型分析结果显示:校正受试者性别、年龄、体质量指数、丙氨酸氨基转移酶、饮酒、吸烟、体育锻炼、乙型肝炎病毒表面抗原阳性、脂肪肝、肝硬化、直系亲属及兄弟姐妹恶性肿瘤病史后,连续变化的空腹血糖是影响新发肝癌的因素(HR=1.06,95%可信区间为1.01~1.12,P<0.05);将空腹血糖进行对数转化,ln空腹血糖是影响新发肝癌的因素(HR=1.81,95%可信区间为1.21~2.70,P<0.05)。RCS结果显示:连续变化的空腹血糖和ln空腹血糖均与肝癌发病风险呈非线性相关 (RCS_S1_ x2=7.21,4.36,P<0.05)。将空腹血糖以分类变量带入COX比例风险模型中,同样校正上述混杂因素后,以T1组为对照组,T2组和T3组分别与T1组比较,受试者新发肝癌的风险均增加(HR=1.45,1.67,95%可信区间为1.07~1.95,1.25~2.22,P<0.05)。(5)空腹血糖对肝癌模型预测价值的比较:建立多因素模型,将性别、年龄、体质量指数、丙氨酸氨基转移酶、饮酒、吸烟、体育锻炼、乙型肝炎病毒表面抗原阳性、脂肪肝、肝硬化、直系亲属及兄弟姐妹恶性肿瘤病史因素带入模型中,计算此模型的C统计量、-2Log L值和AIC值,分别为0.79、6 313.30和6 345.30。将空腹血糖分类变量带入多因素模型中,以T1组为对照组,计算多因素模型+空腹血糖模型的C统计量、-2Log L值和AIC值,分别为0.80、6 300.48和 6 336.48,两种模型比较,差异有统计学意义(x2=12.82,P<0.05)。(6)竞争风险模型分析空腹血糖对新发肝癌的影响。竞争风险模型分析结果显示:校正性别、年龄、体质量指数、丙氨酸氨基转移酶、饮酒、吸烟、体育锻炼、乙型肝炎病毒表面抗原阳性、脂肪肝、肝硬化、直系亲属及兄弟姐妹恶性肿瘤病史后,SD模型中,以T1组为对照组,T1组与T2组比较,受试者肝癌的发病风险不受影响(HR=1.42,95%可信区间为0.98~1.97,P>0.05)。T3组与T1组比较,受试者新发肝癌的风险增加(HR=1.63,95%可信区间为1.16~2.26,P<0.05)。CS模型中,以T1组为对照组,T1组与T2组比较,受试者肝癌的发病风险不受影响(HR=1.43,95%可信区间为0.99~1.97,P>0.05)。T3组与T1组比较,受试者新发肝癌的风险增加(HR=1.65,95%可信区间为1.18~2.23,P<0.05)。
结论:空腹血糖升高是肝癌发病的独立危险因素,综合分析死亡的竞争风险后,高水平空腹血糖对肝癌发病的危险效应仍存在。

【Abstract】

Objective:To explore the correlation between fasting blood glucose (FBG) and hepatocarcinogenesis.
Methods:The retrospective cohort study was conducted. The data of 94 264 participants who participated health examination at the Kailuan General Hospital of North China University of Science and Technology, Kailuan Linxi Hospital, Kailuan Zhaogezhuang Hospital, Kailuan Tangjiazhuang Hospital, Kailuan Fan′gezhuang Hospital,Kailuan Jinggezhuang Hospital, Kailuan Lyujiatuo Hospital, Kailuan Linnancang Hospital, Kailuan Qianjiaying Hospital, Kailuan Majiagou Hospital and Kailuan Branch Hospital from July 2006 to December 2015 were collected. There were 75 134 males and 19 130 females, aged (51±12)years, with a range of 18- 98 years. All the subjects were allocated into 3 groups according to tertiles of FBG, including 31 083 with FBG < 4.82 mmol/L in the T1 group, 31 594 with 4.82 mmol/L≤ FBG <5.49 mmol/L in the T2 group and 31 587 with FBG ≥5.49 mmol/L in the T3 group. All participants received the sameorder health examinations by the fixed team of doctors in 2006, 2008, 2010, 2012 and 2014 at the same place. Epidemiological investigation, anthropometric parameters and biochemical indicators were collected. Observation indicators: (1) comparisons of clinical characteristics among the 3 groups; (2) follow-up and incidence of liver cancer; (3) situations of nonliver cancer death; (4) risk factors analysis affecting new-onset liver cancer; (5) comparisons of the prognostic value of FBG on liver cancer model; (6) effects of FBG on new-onset liver cancer using competing risk model. follow-up using physical examination was performed to detect new-onset liver cancer and survival up to December 31, 2015. The start time of follow-up was the first health examination in 2016 and the terminal event was new-onset liver cancer, loss of follow-up and death. Measurement data with normal distribution were expressed as Mean±SD, and comparisons among groups were analyzed using the oneway ANOVA. Measurement data with skewed distribution were described as M (range), and comparisons among groups were analyzed using the KruskalWallis rank sum test. Count data were described as absolute number and percentage, and comparisons among groups were analyzed using the chisquare test. The cumulative incidence and mortality of new-onset liver cancer were calculated and incidence curve was drawn by the KaplanMeier method, and comparisons of incidences among groups were done by the Logrank test. The incidence of liver cancer in patients with different levels of FBG was calculated by person-year incidence (incidence density). The hazard ratio (HR) and 95% confidence interval (CI) of different levels of FBG (classification variable and continuous variable) on new-onset liver cancer were estimated by the COX proportional hazards regression models. Restrictive cubic spline regression was used to calculate the doseresponse relation between the continuous FBG and the risks of new-onset liver cancer. The fitting degree of FBG on new-onset liver cancer model was calculated by the likelihood ratio test and akaike information criterion (AIC).The predictive power of different models was calculated using the Cstatistics. The net effects of FBG on incidence of liver cancer were analyzed using causespecific hazard function (CS) and subdistribution hazard function (SD).
Results:(1) Comparisons of clinical characteristics among the 3 groups: gender(male), age, systolic pressure, diastolic pressure, waistline, body mass index (BMI), total cholesterol (TC), alanine aminotransferase (ALT), triglyceride (TG), cases with drinking, smoking, physical exercise, positive HBsAg and fatty liver were 23 567, (51±13)years, (128±21)mmHg (1 mmHg=0.133 kPa), (82±12)mmHg, (86±10)cm, (24±3)kg/m2, (4.8±1.2)mmol/L, 17.12 U/L (range, 12.21-24.01 U/L), 1.18 mmol/L (range, 0.82-1.75 mmol/L), 5 080, 9 423, 4 779, 724, 7 591 in the T1 group, 24 870, (50±12)years, (129± 20)mmHg, (83±12)mmHg, (86±10)cm, (25±3)kg/m2, (4.9±1.1)mmol/L,18.31 U/L (range, 13.01-24.31 U/L),1.23 mmol/L (range, 0.88-1.83 mmol/L), 5 448, 9 397, 4 570, 619, 9 009 in the T2 group and 26 697, (53±11)years, (135±22)mmHg, (86±12)mmHg, (89±10)cm, (26±3)kg/m2, (5.1± 1.2)mmol/L, 19.00 U/L (range, 13.79-26.61 U/L),1.44 mmol/L (range, 1.00-2.21 mmol/L), 6 354, 10 292, 5 369, 608, 13 397 in the T3 group, showing statistically significant differences among groups (x2=761.68, F=417.84, 1 010.71, 747.64, 702.73, 1 075.06, 703.83, x2=447.44, 2 109.38, 165.97, 66.69, 78.90, 15.50, 2 576.95, P<0.05). (2) follow-up and incidence of liver cancer: all 94 264 participants were followed up for 817 475 person-year, with a total person-year incidence of 3.71/10 000 person-year, 1.13/10 000 person-year in the female participants and 4.37/10 000 person-year in the male participants. The incidence density of liver cancer was 2.84/10 000 person-year, 3.64/10 000 person-year, 4.64/10 000 person-year in the T1, T2, T3 groups, respectively. The cumulative incidence was 2.76‰, 3.90‰, 4.90‰ in the T1, T2, T3 groups, respectively, showing statistically significant differences among groups (x2=11.95, P<0.05), showing no statistically significant difference between T1 and T2 groups (x2=2.73, P>0.05), showing statistically significant differences between T1 and T3 groups, between T2 and T3 groups (x2=11.56, 4.10, P<0.05). (3) Situations of nonliver cancer death: during the follow-up, 6 880 of 94 264 participants had of nonliver cancer related death, with a nonliver cancer death intensity of 84.16/10 000 person-year. The nonliver cancer death intensity was 79.19/10 000 person-year, 68.17/10 000 person-year, 105.32/10 000 person-year in the T1, T2, T3 groups. The accumulative mortality was 78.90‰, 67.80‰, 104.40‰ in the T1, T2, T3 groups, respectively, showing a statistically significant difference among groups (x2=1 231.46, P<0.05), showing statistically significant differences between T1 and T2 groups, between T1 and T3 groups (x2=5.29, 4.36, P<0.05), showing no statistically significant difference between T2 and T3 groups (x2=0.09, P>0.05). (4) Risk factors analysis affecting new-onset liver cancer. Results of COX proportional hazards regression model analysis showed that continuous FBG was a related factor affecting new-onset liver cancer after adjustment of gender, age, BMI, ALT, drinking, smoking, physical exercise, positive HBsAg, fatty liver, liver cirrhosis, malignant tumor in immediate family (HR=1.06, 95% CI: 1.01-1.12, P<0.05). After ln transformation of FBG, ln FBG was a related factor affecting new-onset liver cancer (HR=1.81, 95% CI: 1.21-2.70, P<0.05). Results of restrictive cubic spline regression showed that continous FBG and ln FBG were nonlinear correlated with incidence of liver cancer (RCS_S1_ x2=7.21, 4.36, P<0.05). After adding FBG as classification variable in the COX model, risk of new-onset liver cancer in the T2 and T3 groups was increased compared with the T1 group (HR=1.45,1.67, 95% CI: 1.07-1.95, 1.25-2.22, P<0.05). (5) Comparisons of the prognostic value of FBG on liver cancer model: multivariate model was constructed after adding risk factors of gender, age, BMI, ALT, drinking, smoking, physical exercise, positive HBsAg, fatty liver, liver cirrhosis, malignant tumor in immediate family, and Cvalue, -2Log L and AIC were 0.79, 6 313.30 and 6 345.30 for the multivariate model. Then FBG variable was added into the multivariate model, and the Cvalue, -2Log L and AIC of the multivariate model + FBG model were 0.80, 6 300.48 and 6 336.48, respectively, showing statistically significant differences compared with the T1 group (x2 = 12.82, P<0.05). (6) Effects of FBG on new-onset liver cancer using competing risk model. Results of competing risk model showed that the risk of new-onset liver cancer in the T2 group was not affected compared with the T1 group (HR=1.42, 95%CI: 0.98-1.97, P>0.05) and risk of new-onset liver cancer in the T3 group was increased compared with the T1 group with the SD model (HR=1.63, 95% CI: 1.16-2.26, P<0.05), after adjustment of gender, age, BMI, ALT, drinking, smoking, physical exercise, positive HBsAg, fatty liver, liver cirrhosis, malignant tumor in immediate family. In the CS model, the risk of new-onset liver cancer in the T2 group was not affected compared with the T1 group (HR=1.43, 95% CI: 0.99-1.97, P>0.05) and risk of new-onset liver cancer in the T3 group was increased compared with the T1 group (HR=1.65, 95% CI: 1.18-2.23, P<0.05).
Conclusions:The elevated FBG is an independent risk factor for the incidence of liver cancer. After considering the competitive risk of death, the risk effect of high-level FBG on the liver cancer still exists.

DOI:10.3760/cma.j.issn.1673-9752.2019.04.010
基金项目:河北省卫生和计划生育委员会重点科技研究计划(20171435)
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