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Article(id=1240375117277090257, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240375105386238038, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202311489, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1701014400000, receivedDateStr=2023-11-27, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773658073014, onlineDateStr=2026-03-16, pubDate=1711296000000, pubDateStr=2024-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773658073014, onlineIssueDateStr=2026-03-16, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773658073014, creator=13701087609, updateTime=1773658073014, updator=13701087609, issue=Issue{id=1240375105386238038, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='6', pageStart='961', pageEnd='1152', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773658070179, creator=13701087609, updateTime=1773658539618, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240377074414833974, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240375105386238038, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240377074414833975, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240375105386238038, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=988, endPage=993, ext={EN=ArticleExt(id=1240375117713297913, articleId=1240375117277090257, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Associations of fasting plasma glucose, 2-hour postload glucose, glycated hemoglobin, and triglyceride-glucose index with cancer risk: a prospective cohort study, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the association of different glycemic measures and the risk of cancer.

Methods

A prospective cohort study conducted in Pudong New Area was used to solve the question. Cox proportional hazard model and Restricted cubic spline (RCS) regression model were used to explore the associations between different glycemic measures and the risk of cancer.

Results

A total of 411 new cancer patients were observed after median 7.78 years follow-up, accumulative person-year incidence rates were 7.12/1 000. After multi-variable adjustment, the HR (95% CI) of elevated FPG and 2hPG were 1.10 (1.03~1.18) and 1.11 (1.02~1.20), respectively. The association between FPG and cancer risk showed a linear dose-response relationship; the association between 2hPG and cancer risk showed a trend toward a U-shaped dose-response relationship.

Conclusion

FPG and 2hPG are important risk factors for cancer, attention should be paid in the prevention and intervention of cancer.

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目的

探索空腹血糖(FPG)、餐后2小时血糖(2hPG)、糖化血红蛋白(HbA1c)和甘油三酯-葡萄糖乘积指数(TyG)等血糖指标与癌症发病风险的关联。

方法

以浦东新区慢病队列人群为研究对象，采用cox回归模型和限制性立方样条(RCS)回归模型探索血糖指标与癌症结局之间的关联。

结果

队列总计观察人年数为57 762人年，共随访到411人确诊癌症，发病密度7.12/千人年。校正其它危险因素后，FPG和2hPG水平每增加1SD，癌症发病风险的HR (95% CI)分别增加1.10 (1.03~1.18)和1.11 (1.02~1.20)。FPG水平与癌症发病风险之间的关联呈现线性的剂量-反应关系，2hPG水平与癌症发病风险之间的关联有呈现U型剂量-反应关系的趋势。

结论

FPG、2hPG水平升高是癌症发病的重要危险因素，在癌症的防治工作中应重视血糖的控制。

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周弋，E-mail：
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=QHZVeSXlKKS2M8pNGkGnQg==, magXml=0DtDVNJmcuUx7GgkBeckOw==, pdfUrl=null, pdf=fg+ePaQ2tA2qkniyf4NOSQ==, pdfFileSize=683209, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=CkLrzw5lL74lJDktxPr+nw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=sjDmnMS9/QAwkMYKCifrtQ==, mapNumber=null, authorCompany=null, fund=null, authors=

柯居中（1989—），女，博士，主管医师，研究方向：慢性病流行病学

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柯居中（1989—），女，博士，主管医师，研究方向：慢性病流行病学

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柯居中（1989—），女，博士，主管医师，研究方向：慢性病流行病学

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Diabetes-Metabolism: Research and Reviews, 2006, 22(2): 126-130., articleTitle=Different contributions of insulin resistance and beta-cell dysfunction in overweight Israeli Arabs with IFG and IGT, refAbstract=null), Reference(id=1240746307128718144, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, doi=null, pmid=null, pmcid=null, year=2021, volume=97, issue=1148, pageStart=380, pageEnd=383, url=null, language=null, rfNumber=[23], rfOrder=25, authorNames=Kaiafa G, Veneti S, Polychronopoulos G, journalName=Postgraduate Medical Journal, refType=null, unstructuredReference=Kaiafa G, Veneti S, Polychronopoulos G, et al. Is HbA1c an ideal biomarker of well-controlled diabetes?[J]. 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Pediatrics and Neonatology, 2019, 60(4): 428-434., articleTitle=Comparison of HbA1c and OGTT for the diagnosis of type 2 diabetes in children at risk of diabetes, refAbstract=null)], funds=[Fund(id=1240746304129790522, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, awardId=PWRq2021-05, language=CN, fundingSource=浦东新区卫生系统优秀青年医学人才培养计划(PWRq2021-05), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1240746299339894957, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, xref=null, ext=[AuthorCompanyExt(id=1240746299348283566, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, companyId=1240746299339894957, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Pudong New Area Centers for Disease Control and Prevention, Shanghai 200136, China), AuthorCompanyExt(id=1240746299356672175, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, companyId=1240746299339894957, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=上海市浦东新区疾病预防控制中心慢性病防治科，上海 200136)])], figs=[ArticleFig(id=1240746302930219458, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, language=EN, label=Fig.1, caption=Multivariable adjusted spline curves forassociation between different glycemic measures and risk for cancer incidence, figureFileSmall=LsSJy5scAyKovNpHOIqekQ==, figureFileBig=13X3DWvBxazqVvcNF3UAUQ==, tableContent=null), ArticleFig(id=1240746303014105545, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, language=CN, label=图1, caption=不同血糖指标与癌症发病风险的RCS回归模型分析

注：校正因素包括年龄(连续变量)、性别、婚姻状况、城乡分布、受教育水平、BMI(连续变量)、吸烟、饮酒、饮茶、体育活动、癌症家族史、高血压、血脂异常、CRP(连续变量)；条图展示各血糖指标的频数分布。

, figureFileSmall=LsSJy5scAyKovNpHOIqekQ==, figureFileBig=13X3DWvBxazqVvcNF3UAUQ==, tableContent=null), ArticleFig(id=1240746303156711897, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, language=EN, label=Table 1, caption=

Baseline characteristics of cohort participants stratified by sex

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类男性(n=2 751)女性(n=4 943)合计(n=7 694)t/Z/χ2值P
年龄(岁)-58.23±13.7056.85±12.1357.34±12.7320.63<0.001
居住地区(%)农村1 170(42.53)1 873(37.89)3 043(39.55)15.90<0.001
城市1 581(57.47)3 070(62.11)4 651(60.45)
婚姻状况(%)在婚2 482(90.22)4 280(86.59)6 762(87.89)21.93<0.001
其它269(9.78)663(13.41)932(12.11)
受教育年限(%)>=9年2 347(85.31)3 786(76.59)6 133(79.71)83.12<0.001
<9年404(14.69)1 157(23.41)1 561(20.29)
吸烟(%)否1 561(56.74)4 898(99.09)6 459(83.95)2 352.01<0.001
是1 190(43.26)45(0.91)1 235(16.05)
饮酒(%)否1 930(70.16)4 836(97.84)6 766(87.94)1 276.60<0.001
是821(29.84)107(2.16)928(12.06)
饮茶(%)否1 407(51.15)4 172(84.40)5 579(72.51)980.70<0.001
是1 344(48.85)771(15.60)2 115(27.49)
体育活动(%)否2 073(75.35)3 611(73.05)5 684(73.88)4.850.028
是678(24.65)1 332(26.95)2 010(26.12)
癌症家族史(%)否2 618(95.17)4 616(93.38)7 234(94.02)9.970.002
是133(4.83)327(6.62)460(5.98)
高血压(%)否1 591(57.83)3 120(63.12)4 711(61.23)20.80<0.001
是1 160(42.17)1 823(36.88)2 983(38.77)
血脂异常(%)否1 381(50.20)2 671(54.04)4 052(52.66)10.430.001
是1 370(49.80)2 272(45.96)3 642(47.34)
BMI(kg/m2)-25.27±3.3324.76±3.5624.94±3.4937.10<0.001
FPG(mmol/L)-5.46(5.08,5.92)5.37(5.04,5.79)5.40(5.05,5.84)5.69<0.001
2hPG(mmol/L)-6.00(4.91,7.52)6.05(5.13,7.37)6.03(5.06,7.42)1.580.114
HbA1c(%)-5.30(4.90,5.80)5.30(4.90,5.80)5.30(4.90,5.80)1.590.113
TyG-8.73(8.34,9.18)8.64(8.26,9.04)8.68(8.29,9.08)6.82<0.001
TG(mmol/L)-1.39(0.97,2.10)1.30(0.92,1.87)1.33(0.94,1.95)5.83<0.001
TC(mmol/L)-5.27(4.61,5.96)5.63(4.90,6.37)5.50(4.78,6.23)13.96<0.001
HDL(mmol/L)-1.22(1.04,1.41)1.41(1.21,1.64)1.34(1.14,1.58)25.28<0.001
LDL(mmol/L)-3.02(2.39,3.67)3.10(2.44,3.79)3.07(2.43,3.75)3.72<0.001
CRP(mg/L)-0.26(0.08,0.92)0.22(0.06,0.84)0.23(0.07,0.87)4.45<0.001
), ArticleFig(id=1240746303274152422, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, language=CN, label=表1, caption=

研究对象的主要基线特征

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类男性(n=2 751)女性(n=4 943)合计(n=7 694)t/Z/χ2值P
年龄(岁)-58.23±13.7056.85±12.1357.34±12.7320.63<0.001
居住地区(%)农村1 170(42.53)1 873(37.89)3 043(39.55)15.90<0.001
城市1 581(57.47)3 070(62.11)4 651(60.45)
婚姻状况(%)在婚2 482(90.22)4 280(86.59)6 762(87.89)21.93<0.001
其它269(9.78)663(13.41)932(12.11)
受教育年限(%)>=9年2 347(85.31)3 786(76.59)6 133(79.71)83.12<0.001
<9年404(14.69)1 157(23.41)1 561(20.29)
吸烟(%)否1 561(56.74)4 898(99.09)6 459(83.95)2 352.01<0.001
是1 190(43.26)45(0.91)1 235(16.05)
饮酒(%)否1 930(70.16)4 836(97.84)6 766(87.94)1 276.60<0.001
是821(29.84)107(2.16)928(12.06)
饮茶(%)否1 407(51.15)4 172(84.40)5 579(72.51)980.70<0.001
是1 344(48.85)771(15.60)2 115(27.49)
体育活动(%)否2 073(75.35)3 611(73.05)5 684(73.88)4.850.028
是678(24.65)1 332(26.95)2 010(26.12)
癌症家族史(%)否2 618(95.17)4 616(93.38)7 234(94.02)9.970.002
是133(4.83)327(6.62)460(5.98)
高血压(%)否1 591(57.83)3 120(63.12)4 711(61.23)20.80<0.001
是1 160(42.17)1 823(36.88)2 983(38.77)
血脂异常(%)否1 381(50.20)2 671(54.04)4 052(52.66)10.430.001
是1 370(49.80)2 272(45.96)3 642(47.34)
BMI(kg/m2)-25.27±3.3324.76±3.5624.94±3.4937.10<0.001
FPG(mmol/L)-5.46(5.08,5.92)5.37(5.04,5.79)5.40(5.05,5.84)5.69<0.001
2hPG(mmol/L)-6.00(4.91,7.52)6.05(5.13,7.37)6.03(5.06,7.42)1.580.114
HbA1c(%)-5.30(4.90,5.80)5.30(4.90,5.80)5.30(4.90,5.80)1.590.113
TyG-8.73(8.34,9.18)8.64(8.26,9.04)8.68(8.29,9.08)6.82<0.001
TG(mmol/L)-1.39(0.97,2.10)1.30(0.92,1.87)1.33(0.94,1.95)5.83<0.001
TC(mmol/L)-5.27(4.61,5.96)5.63(4.90,6.37)5.50(4.78,6.23)13.96<0.001
HDL(mmol/L)-1.22(1.04,1.41)1.41(1.21,1.64)1.34(1.14,1.58)25.28<0.001
LDL(mmol/L)-3.02(2.39,3.67)3.10(2.44,3.79)3.07(2.43,3.75)3.72<0.001
CRP(mg/L)-0.26(0.08,0.92)0.22(0.06,0.84)0.23(0.07,0.87)4.45<0.001
), ArticleFig(id=1240746303391592951, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, language=EN, label=Table 2, caption=

Cancer incidence of study participants stratified by sex

, figureFileSmall=null, figureFileBig=null, tableContent=
性别癌症种类观察例数观察人年发病例数累积发病率
（%）		发病密度
（1/1 000人年）
男性总体癌症2 75120 4531585.747.73
肺癌2 75120 453371.341.81
结直肠癌2 75120 453210.761.03
胃癌2 75120 453200.730.98
前列腺癌2 75120 453170.620.83
肾癌2 75120 45390.330.44
其它部位2 75120 453541.962.64
女性总体癌症4 94337 3082535.126.78
肺癌4 94337 308591.191.58
乳腺癌4 94337 308430.871.15
甲状腺癌4 94337 308330.670.88
结直肠癌4 94337 308180.360.48
胃癌4 94337 308150.300.40
其它部位4 94337 308851.722.28
合计总体癌症7 69457 7624115.347.12
肺癌7 69457 762961.251.66
乳腺癌7 69457 762430.560.74
结直肠癌7 69457 762390.510.68
甲状腺癌7 69457 762350.450.61
胃癌7 69457 762350.450.61
其它部位7 69457 7621632.122.82
), ArticleFig(id=1240746303601308163, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, language=CN, label=表2, caption=

研究人群的癌症发病情况

, figureFileSmall=null, figureFileBig=null, tableContent=
性别癌症种类观察例数观察人年发病例数累积发病率
（%）		发病密度
（1/1 000人年）
男性总体癌症2 75120 4531585.747.73
肺癌2 75120 453371.341.81
结直肠癌2 75120 453210.761.03
胃癌2 75120 453200.730.98
前列腺癌2 75120 453170.620.83
肾癌2 75120 45390.330.44
其它部位2 75120 453541.962.64
女性总体癌症4 94337 3082535.126.78
肺癌4 94337 308591.191.58
乳腺癌4 94337 308430.871.15
甲状腺癌4 94337 308330.670.88
结直肠癌4 94337 308180.360.48
胃癌4 94337 308150.300.40
其它部位4 94337 308851.722.28
合计总体癌症7 69457 7624115.347.12
肺癌7 69457 762961.251.66
乳腺癌7 69457 762430.560.74
结直肠癌7 69457 762390.510.68
甲状腺癌7 69457 762350.450.61
胃癌7 69457 762350.450.61
其它部位7 69457 7621632.122.82
), ArticleFig(id=1240746303718748684, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375117277090257, language=EN, label=Table 3, caption=

Hazard ratios of cancer incidence according to different glycemic measures in cohort participants

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变量单因素分析多因素分析
Wald χ2HR (95% CI)PWald χ2HR (95% CI)P
FPG19.0791.15(1.08~1.22)<0.0017.2961.10(1.03~1.18)0.007
2hPG20.2321.19(1.10~1.28)<0.0015.7761.11(1.02~1.20)0.016
HbA1c9.2541.14(1.05~1.23)0.0021.4101.06(0.96~1.16)0.235
TyG1.9211.07(0.97~1.18)0.166---
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不同血糖指标与癌症发病风险的cox回归模型分析

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变量单因素分析多因素分析
Wald χ2HR (95% CI)PWald χ2HR (95% CI)P
FPG19.0791.15(1.08~1.22)<0.0017.2961.10(1.03~1.18)0.007
2hPG20.2321.19(1.10~1.28)<0.0015.7761.11(1.02~1.20)0.016
HbA1c9.2541.14(1.05~1.23)0.0021.4101.06(0.96~1.16)0.235
TyG1.9211.07(0.97~1.18)0.166---
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不同血糖指标与癌症发病风险的前瞻性队列研究
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柯居中 , 吴抗 , 刘晓琳 , 邱桦 , 王小楠 , 李智韬 , 周弋
现代预防医学 | 流行病与统计方法 2024,51(6): 988-993
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现代预防医学 | 流行病与统计方法 2024, 51(6): 988-993
不同血糖指标与癌症发病风险的前瞻性队列研究
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柯居中, 吴抗, 刘晓琳, 邱桦, 王小楠, 李智韬, 周弋
作者信息
  • 上海市浦东新区疾病预防控制中心慢性病防治科，上海 200136

    • 柯居中（1989—），女，博士，主管医师，研究方向：慢性病流行病学

通讯作者:

周弋，E-mail：
Associations of fasting plasma glucose, 2-hour postload glucose, glycated hemoglobin, and triglyceride-glucose index with cancer risk: a prospective cohort study
Ju-zhong KE, Kang WU, Xiao-lin LIU, Hua QIU, Xiao-nan WANG, Zhi-tao LI, Yi ZHOU
Affiliations
  • Pudong New Area Centers for Disease Control and Prevention, Shanghai 200136, China
出版时间: 2024-03-25 doi: 10.20043/j.cnki.MPM.202311489
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摘要
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目的

探索空腹血糖(FPG)、餐后2小时血糖(2hPG)、糖化血红蛋白(HbA1c)和甘油三酯-葡萄糖乘积指数(TyG)等血糖指标与癌症发病风险的关联。

方法

以浦东新区慢病队列人群为研究对象，采用cox回归模型和限制性立方样条(RCS)回归模型探索血糖指标与癌症结局之间的关联。

结果

队列总计观察人年数为57 762人年，共随访到411人确诊癌症，发病密度7.12/千人年。校正其它危险因素后，FPG和2hPG水平每增加1SD，癌症发病风险的HR (95% CI)分别增加1.10 (1.03~1.18)和1.11 (1.02~1.20)。FPG水平与癌症发病风险之间的关联呈现线性的剂量-反应关系，2hPG水平与癌症发病风险之间的关联有呈现U型剂量-反应关系的趋势。

结论

FPG、2hPG水平升高是癌症发病的重要危险因素，在癌症的防治工作中应重视血糖的控制。

空腹血糖  /  餐后2小时血糖  /  糖化血红蛋白  /  甘油三酯-葡萄糖乘积指数  /  癌症
Objective

To explore the association of different glycemic measures and the risk of cancer.

Methods

A prospective cohort study conducted in Pudong New Area was used to solve the question. Cox proportional hazard model and Restricted cubic spline (RCS) regression model were used to explore the associations between different glycemic measures and the risk of cancer.

Results

A total of 411 new cancer patients were observed after median 7.78 years follow-up, accumulative person-year incidence rates were 7.12/1 000. After multi-variable adjustment, the HR (95% CI) of elevated FPG and 2hPG were 1.10 (1.03~1.18) and 1.11 (1.02~1.20), respectively. The association between FPG and cancer risk showed a linear dose-response relationship; the association between 2hPG and cancer risk showed a trend toward a U-shaped dose-response relationship.

Conclusion

FPG and 2hPG are important risk factors for cancer, attention should be paid in the prevention and intervention of cancer.

Fasting plasma glucose  /  2-hour postload glucose  /  Hemoglobin A1c  /  Triglyceride glucose index  /  Cancer
柯居中, 吴抗, 刘晓琳, 邱桦, 王小楠, 李智韬, 周弋. 不同血糖指标与癌症发病风险的前瞻性队列研究. 现代预防医学, 2024 , 51 (6) : 988 -993 . DOI: 10.20043/j.cnki.MPM.202311489
Ju-zhong KE, Kang WU, Xiao-lin LIU, Hua QIU, Xiao-nan WANG, Zhi-tao LI, Yi ZHOU. Associations of fasting plasma glucose, 2-hour postload glucose, glycated hemoglobin, and triglyceride-glucose index with cancer risk: a prospective cohort study[J]. Modern Preventive Medicine, 2024 , 51 (6) : 988 -993 . DOI: 10.20043/j.cnki.MPM.202311489
正文
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癌症是全球范围内重要的公共卫生问题。中国2020年癌症粗发病率达315.6/10万，标化发病率204.8/10万，粗死亡率达207.5/10万，标化死亡率129.4/10万[1]。随着人口老龄化，城市化进程，人群生活方式改变增加癌症风险，中国的癌症发病率和死亡率在未来较长时间内都呈持续增长趋势[2]。糖代谢异常是多种癌症发病的独立危险因素，空腹血糖(FPG)、餐后2小时血糖(2hPG)和糖化血红蛋白(HbA1c)等均是常用的血糖检测指标，但这些指标与癌症发病风险的关联仍不够明确[3]。甘油三酯-葡萄糖乘积指数(TyG)是基于空腹血甘油三酯(TG)与FPG建立的评估胰岛素抵抗的指标[4]，但TyG指数与癌症发病风险之间的相关性研究目前仍比较缺乏。本研究基于浦东新区慢病队列研究，探索FPG、2hPG、HbA1c和TyG四种血糖指标与癌症发病风险的关联，为癌症的防治工作提供参考依据。
1 材料与方法
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1.1 研究对象
本研究基于浦东新区慢病队列工作，基线调查于2013年1—7月开展，采用多阶段分层随机抽样法选取调查人群[5]。本研究通过上海市浦东新区疾病预防控制中心伦理委员会的审核，所有调查对象都签署了知情同意书。在参与基线调查的10 657人中，去除基线调查时自报患糖尿病，未开展OGTT试验的1 031人，基线调查时患癌症的170人和随访观察第一年内诊断癌症的54人，调查问卷信息缺失的126人，实验室检测信息缺失的850人，服糖后出现呕吐等不良反应影响2hPG 检测结果的499人，以及失访的233人，余下的7 694人纳入分析数据集。
1.2 资料收集
基线调查现场首先询问研究对象是否患有糖尿病，对于自报未患糖尿病者开展OGTT试验，先抽取空腹静脉血，受试者在5分钟之内服用完溶于250~300 ml水内的75 g葡萄糖，并抽取服糖后2小时静脉血；对于自报患糖尿病者不开展OGTT试验，仅抽取空腹静脉血。问卷调查采用面对面访谈的形式，调查内容包括人口学信息、慢性病疾病史和家族史、行为危险因素等信息。身体测量包括身高、体重、血压、腰臀围等。实验室检测指标包括FPG、2hPG、HbA1c、TG、总胆固醇（TC）、高密度脂蛋白（HDL）、低密度脂蛋白（LDL）、C-反应蛋白（CRP）等，均采用日立全自动生化分析仪 (型号HITACHI 7170A) 检测。
1.3 质量控制
所有调查表统一印刷，调查物资统一采购，保证调查现场做到器材统一、方法统一和标准统一。调查员均经过统一培训和考核，每日现场测量前均对仪器进行统一校正。对所有的调查问卷进行质量复核、双轨录入和逻辑校对。每日实验室检测前均进行化学质控品检测。
1.4 指标定义
糖尿病诊断参照WHO诊断标准，自报确诊有糖尿病病史者或静脉血FPG ≥ 7.0 mmol/L或2hPG ≥ 11.1 mmol/L者为糖尿病。癌症的诊断标准参照《上海市肿瘤登记管理办法》(沪卫计疾控[2015]027号文件)[6]，包括ICD-10编码C00-C97的侵袭性癌以及编码D00-D09的原位癌。TyG指数根据TG和FPG计算，TyG＝ln[TG(mmol/L)×FPG(mmol/L) /(2×0.01129×0.05551)][7]。
1.5 随访及终点事件收集
对研究人群随访观察至2020年12月31日，将随访截止日期或随访期间确诊癌症的日期作为随访终点。采用身份证号码链接浦东新区肿瘤登记数据库，并结合病史核对的方法来确定研究对象的癌症发病结局。
1.6 统计分析
计量资料用或M（P25,P75）表示，计数资料用n(%)表示。组间比较采用t检验、秩和检验或χ2检验。采用cox回归模型分析各血糖指标与癌症的关联。用Z分法对FPG、2hPG、HbA1c、TyG指数作正态性转换，Z分值 =(变量测量值-均数)/标准差，然后将Z分值代替原始变量纳入cox回归模型，并计算HR(95% CI)。采用限制性立方样条（RCS）回归模型探索血糖指标与癌症之间的非线性关联，如果P总<0.05且P非线性 <0.05，则表示存在非线性的剂量反应关系。统计分析采用SAS 9.4和SPSS 22.0软件，检验水准α=0.05。
2 结果
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2.1 研究对象基本特征
纳入分析的7 694人中，男性2 751人，女性4 943人。研究对象的基线人口学特征、行为危险因素暴露情况和实验室检测指标分布情况见表1。男性和女性人群的各项人口学特征和行为危险因素差异均有统计学意义，除2hPG、HbA1c外，男性和女性人群的各项实验室检测指标分布差异均有统计学意义。
2.2 研究人群癌症发病情况
队列总计观察人年数为57 762人年，随访观察时间中位数7.78年（P25~P75：7.70~7.82年）。共随访到411人确诊癌症，男性158例，女性253例。研究人群总体癌症累积发病率5.34%，发病密度7.12/千人年。男性和女性癌症发病密度的差异无统计学意义（χ2=1.37，P>0.05）。研究人群最常见的癌症发病类型为肺癌（96例，23.36%）、乳腺癌（43例，10.46%）、结直肠癌（39例，9.49%）、甲状腺癌（35例，8.52%）、胃癌（35例，8.52%），男性最常见的癌症发病类型为肺癌（37例，23.42%）、结直肠癌（21例，13.29%）、胃癌（20例，12.66%）、前列腺癌（17例，10.76%）、肾癌（9例，5.70%），女性最常见的癌症发病类型为肺癌（59例，23.32%）、乳腺癌（43例，17.00%）、甲状腺癌（33例，13.04%）、结直肠癌（18例，7.11%）、胃癌（15例，5.93%）。见表2。
2.3 不同血糖指标与癌症发病风险的关联
单因素cox回归模型分析结果显示，FPG，2hPG和HbA1c与癌症发病风险有关，TyG与癌症发病风险的关联无统计学意义。多因素分析结果显示，FPG和2hPG与癌症发病风险的关联仍然存在，FPG和2hPG每增加1SD，癌症发病风险增加的HR (95% CI)分别为1.10(1.03~1.18)和1.11(1.02~1.20)，HbA1c与癌症发病风险的关联无统计学意义。见表3。RCS回归模型分析结果显示，FPG和2hPG与癌症发病风险有关：FPG与癌症发病风险存在线性关联，FPG水平升高，癌症发病风险也升高；2hPG与癌症发病风险之间的关联有呈现U型剂量-反应关系的趋势(P总 =0.017,P非线性=0.092)，但未达到有统计学意义。HbA1c和TyG与癌症发病风险的关联无统计学意义(P总> 0.05)。见图1。
3 讨论
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本研究比较了四种血糖指标与癌症风险的关联，发现经过多因素校正后，FPG水平与癌症发病风险的关联呈现线性剂量-反应关系，2hPG水平与癌症发病风险的关联有呈现U型剂量-反应关系的趋势。本研究是在社区居民中开展的前瞻性队列研究，研究人群通过抽样获得，代表性较好，各项血糖指标均在基线调查时同步检测，并配合严格的质量控制措施，因此研究结果有较强的公共卫生指导意义。
多项研究证实了FPG、2hPG与癌症发病风险的关联。全球疾病负担研究认为，2019年有860万癌症伤残调整寿命年可归因于空腹血糖水平升高[8]。日本的一项应用全国数据的分析性研究认为FPG水平升高者的结直肠癌发病风险升高[9]。2hPG主要用于OGTT试验，结合FPG水平共同预测疾病结局。有研究认为2hPG在识别糖尿病前期和糖尿病高危人群方面比FPG更敏感[10]。日本的一项真实世界研究认为糖尿病患者2hPG水平控制不佳是死亡和癌症死亡的独立危险因素[11]。目前在中国人群中开展的不同血糖指标与疾病风险的关联研究较少，有的研究认为2hPG与糖尿病、癌症、心脑血管急性事件等发病的关联强度优于FPG和HbA1c[12-13]。也有研究认为FPG和2hPG水平升高都是高血压发病的独立危险因素，但HbA1c则没有这样的关联[14]。
TyG指数综合了脂毒性和糖毒性在胰岛素抵抗的过程中的作用，常作为反应胰岛素抵抗的指标应用于流行病学现场研究[15]。一项在欧洲人群中开展的研究认为TyG指数与肾癌、肝癌、胰腺癌和结直肠癌等肥胖相关癌症的发病风险有关[16]。一项基于UK Biobank数据开展的研究认为TyG指数与肺癌发病风险无关[17]。本研究亦未发现TyG指数与癌症发病风险有关。造成这些研究结果不一致的可能原因是TyG指数所反映的胰岛素抵抗主要在消化系统癌症发病过程中发挥作用[18-19]。
血糖水平与癌症发病相关的病理机制主要是高血糖和内源性高胰岛素血症，促进癌细胞转移和侵袭[20-21]。不同血糖指标反映了糖代谢过程中不同类型的病理异常。FPG水平升高引起的IFG以及2hPG水平升高引起的IGT都是与胰岛素抵抗有关的糖代谢异常，IFG与肝脏胰岛素抵抗有关，而IGT反映的是肌肉胰岛素抵抗[22]。HbA1c是反映过去3个月内的血糖总体控制情况的间接指标，贫血、磷酸脱氢酶缺乏症、血液透析、以及高血糖导致的蛋白质糖基化等多种因素都会对HbA1c产生影响，因此不能实时准确的反映机体的血糖水平和短期波动情况[23]。与HbA1c相比，FPG和2hPG可能更直接的体现了实时的血糖水平和短期波动情况，更灵敏的反映机体的高血糖和胰岛素抵抗状况，以及糖代谢异常在癌症发病机制中发挥的促进作用[24]。在开展长期疾病风险的预测时，需要结合相关的发病机制选择最佳的血糖检测指标。
本研究的主要优点包括：采用前瞻性队列研究设计；证实了FPG和2hPG水平对于个体的癌症发病风险的预测作用，有助于癌症风险评估，筛查出癌症的高危人群开展早期干预；评估了衍生指标TyG与癌症发病风险的关联。本研究的主要局限性包括：队列的随访观察时间不够长，需要更长的随访时间才能得到更可靠的结论；出于伦理方面的考虑，对于基线调查时自报患糖尿病者未开展OGTT实验，导致用于分析比较的样本量偏小；仅分析了基线调查时不同血糖指标与癌症发病风险的关联，未能考虑到随访期间血糖波动对癌症发病的影响；未考虑饮食习惯、心理社会因素等的影响，可能造成残余的混杂偏倚。
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doi: 10.20043/j.cnki.MPM.202311489
  • 接收时间：2023-11-27
  • 首发时间：2026-03-16
  • 出版时间：2024-03-25
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  • 收稿日期：2023-11-27
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浦东新区卫生系统优秀青年医学人才培养计划(PWRq2021-05)
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    上海市浦东新区疾病预防控制中心慢性病防治科，上海 200136

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
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红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
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光柄菇属 Pluteus 5 2.39
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