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Article(id=1324077959350460602, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077716676424398, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202509108, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1757433600000, receivedDateStr=2025-09-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614385687, onlineDateStr=2026-11-02, pubDate=1773072000000, pubDateStr=2026-03-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614385687, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614385687, creator=13701087609, updateTime=1793614385687, updator=13701087609, issue=Issue{id=1324077716676424398, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='5', pageStart='769', pageEnd='960', issueExtLink='null', onlineDate='null', pubDate='1773072000000', pubDateStr='2026-03-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614327830, creator='13701087609', updateTime=1793614418028, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078095132655884, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077716676424398, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078095132655885, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077716676424398, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=954, endPage=960, ext={EN=ArticleExt(id=1324077959610507451, articleId=1324077959350460602, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association of lymphocyte to monocyte ratio with breast cancer:a cross-sectional study based on NHANES, columnId=1228016569138213037, journalTitle=Modern Preventive Medicine, columnName=Clinical Medicine and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

Systemic inflammation and immune status play critical roles in carcinogenesis. However, evidence regarding the association between the lymphocyte-to-monocyte ratio (LMR) and the risk of breast cancer (BC) remains limited.This study aims to investigate the relationship between LMR and BC risk.

Methods

A total of 13 519 participants with complete LMR and BC data were identified from the U.S. National Health and Nutrition Examination Survey (NHANES) 2005—2018. Multivariable weighted logistic regression models, restricted cubic spline analyses, and subgroup analyses were conducted to evaluate the independent association between LMR and BC risk. Sensitivity analyses were performed to assess the robustness of the findings.

Results

A significant U-shaped association was observed between LMR and BC risk, with an inflection point at 1.82. When LMR was ≤1.82, it was inversely associated with BC risk, with each one-unit increase in LMR corresponding to a 76% reduction in BC risk (OR=0.24, 95% CI: 0.18-0.31). Above this threshold, the association was no longer statistically significant. In the LMR quartile groups, the highest quartile (Q4) showed a significant reduction in breast cancer risk of approximately 47% compared to the Q1 group (OR=0.53, 95% CI: 0.38-0.74). Likelihood ratio tests indicated that the piecewise linear model provided a better fit than the linear model. Subgroup and interaction analyses revealed significant differences in the association between LMR and BC risk between participants with and without diabetes.

Conclusion

This study is the first to demonstrate a non-linear (broad U-shaped) association between LMR and BC risk,indicating that both low and high LMR levels are associated with an increased risk of BC. Maintaining LMR within a stable range may help prevent and slow the development and progression of breast cancer. Further large-scale prospective cohort studies are warranted to validate these findings.

, authors=Xiao-yu LI1, Ke HONG1, Meng-fan CHEN1, Chang YAO1, 2, authorsList=Xiao-yu LI, Ke HONG, Meng-fan CHEN, Chang YAO, authorCompany=null, correspAuthors=Chang YAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1324077961145622726, articleId=1324077959350460602, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=淋巴细胞与单核细胞比值与乳腺癌的相关性——一项横断面研究, columnId=1228016570119680182, journalTitle=现代预防医学, columnName=临床与预防, runingTitle=null, highlight=null, articleAbstract=
目的

全身性炎症与免疫状态在癌症发生中起着重要作用，但关于淋巴细胞与单核细胞比值（lymphocyte-to-monocyte ratio，LMR）与乳腺癌发病风险之间关联的研究尚有限。本研究旨在探讨LMR与乳腺癌风险之间的关系。

方法

基于2005—2018年美国国家健康与营养调查中13 519名具备完整LMR及乳腺癌数据的参与者。通过多元加权logistic回归、限制性立方样条、亚组分析，探索LMR与乳腺癌的独立关联性，进行敏感性分析以确保结果的稳定性。

结果

研究显示LMR与乳腺癌风险存在显著U型关系，转折点在1.82，当≤1.82 时，其水平与乳腺癌风险呈显著负相关，每增加一个单位，乳腺癌风险降低76%（OR=0.24,95% CI: 0.18～0.31）；而在该阈值以上，关联不再显著。LMR四分位组中，最高四分位组（Q4）的乳腺癌风险较Q1组显著降低约47%（OR= 0.53，95% CI: 0.38～0.74）。对数似然比检验提示分段线性模型优于线性模型。亚组分析与交互作用检验显示，糖尿病患者与非糖尿病患者在LMR与乳腺癌风险关联性方面存在显著差异。

结论

本研究首次揭示了LMR与乳腺癌风险之间存在非线性（宽U形）关联：无论LMR偏低或偏高均会增加患病风险，保持稳定范围的LMR，可能有助于预防和减缓乳腺癌的发生和发展。未来仍需要大规模前瞻性队列验证。

, authors=李晓玉1, 洪珂1, 陈梦帆1, 姚昶1, 2, authorsList=李晓玉, 洪珂, 陈梦帆, 姚昶, authorCompany=null, correspAuthors=姚昶, authorNote=

李晓玉（2000-），女，硕士在读，研究方向：中西医防治乳腺癌转移

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姚昶，E-mail:
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Breast Cancer Research and Treatment, 2023, 202(1): 11-22., articleTitle=Breast cancer and incidence of type 2 diabetes mellitus: a systematic review and meta-analysis, refAbstract=null)], funds=[Fund(id=1324077967118311674, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, awardId=KYCX25_2224, language=CN, fundingSource=2025年江苏省研究生科研创新计划(KYCX25_2224), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324077961376309447, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, xref=1., ext=[AuthorCompanyExt(id=1324077961388892360, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, companyId=1324077961376309447, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China), AuthorCompanyExt(id=1324077961401475273, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, companyId=1324077961376309447, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.南京中医药大学附属医院，江苏 南京 210029)]), AuthorCompany(id=1324077961565053130, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, xref=2., ext=[AuthorCompanyExt(id=1324077961573441739, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, companyId=1324077961565053130, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.江苏省中医院乳腺外科，江苏 南京 210029)])], figs=[ArticleFig(id=1324077964568174829, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=EN, label=Figure 1, caption=Flowchart of participant selection in this study, figureFileSmall=w7UNNTk0xPoLPhWX43eqbg==, figureFileBig=06lcyKkvw0OfPUsPsvm9ew==, tableContent=null), ArticleFig(id=1324077964652060910, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=CN, label=图1, caption=本研究参与者筛选流程图, figureFileSmall=w7UNNTk0xPoLPhWX43eqbg==, figureFileBig=06lcyKkvw0OfPUsPsvm9ew==, tableContent=null), ArticleFig(id=1324077965075685615, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=EN, label=Figure 2, caption=Association between LMR and breast cancer risk based on a smoothed curve fit, figureFileSmall=KeYh0ngKqGTdvkQ/vMdAXQ==, figureFileBig=jVG827kNiEedcNOPfNk92A==, tableContent=null), ArticleFig(id=1324077965369286896, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=CN, label=图2, caption=平滑曲线拟合显示的LMR与乳腺癌发生风险的关系

注：A为平滑曲线拟合 LMR 水平与乳腺癌风险之间的非线性关系，图中黑色线代表OR值，虚线表示95%置信区间；B为不同 LMR 四分位数组的乳腺癌调整后患病率及其 95% 置信区间。

, figureFileSmall=KeYh0ngKqGTdvkQ/vMdAXQ==, figureFileBig=jVG827kNiEedcNOPfNk92A==, tableContent=null), ArticleFig(id=1324077965436395761, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=EN, label=Figure 3, caption=Restricted cubic spline (RCS) analysis of the association between LMR and breast cancer risk, figureFileSmall=oaKjsZ8dMXziMwpZMqAULg==, figureFileBig=ZJgW5F/nFa2DV2pVCJJ65A==, tableContent=null), ArticleFig(id=1324077965750968563, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=CN, label=图3, caption=LMR 与乳腺癌患病风险的RCS分析, figureFileSmall=oaKjsZ8dMXziMwpZMqAULg==, figureFileBig=ZJgW5F/nFa2DV2pVCJJ65A==, tableContent=null), ArticleFig(id=1324077965860020468, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=EN, label=Table 1, caption=

Baseline characteristics of participants by breast cancer status ［（），n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总数(n=13 519)非乳腺癌 （n=13 136）乳腺癌(n=383)P值
年龄（岁）47.09±16.6547.99±16.9565.76±11.53<0.001
血液总钙吸收9.45±0.089.37±0.379.42±0.420.002
BMI39.8±3.1129.20±7.5329.39±6.730.615
LMR1.85±0.391.41±0.361.19±0.41<0.001
绝经状态<0.001
绝经6 920（51.18）6 568(50.20)352(91.72)
非绝经6 599（48.81）6 568(49.80)31(8.28)
种族<0.001
墨西哥裔美国人1 063（7.86）1 050(7.94)13 (3.37)
其他西班牙裔799（5.91）788(5.85)11(2.90)
非西班牙裔白人9 201（68.05）8 885(67.64)316(82.56)
非西班牙裔黑人1 497（11.07）1 471(11.20)26(6.80)
其他种族959（7.09）942(7.37)17(4. 38)
教育程度0.079
高中以下及同等高中学力4 916（36.36）4 793(36.49)123(32.23)
大学毕业及以上8 603（63.63）8 343(63.51)260(67.77)
婚烟状况0.033
已婚或与伴侣同住8 109(59.98)7 899(60.13)210(54.86)
离婚或丧偶或分居5 410(40.01)5 237(39.87)173(45.14)
高血压<0.001
是4 352(32.19)4 156(31.64)196(51.25)
否9 167(67.81)8 980(68.36)187(48.75)
充血性心力衰竭<0.001
是282(2.09)259(1.97)23(6.04)
否13 237(97.91)12 877(98.03)360(93.96)
冠心病<0.001
是310(2.29)281(2.14)29(7.64)
否13 209(97.71)12 855(97.86)354(92.36)
心绞痛/心肌缺血性疼痛<0.001
是253(1.87)234(1.78)19(4.94)
否13 266(98.13)12 902(98.22)364(95.06)
中风<0.001
是405(3.0)378(2.88)27(7.07)
否13 114(97.00)12 758(97.12)356(92.93)
吸烟状况0.818
吸烟5 141(38.03)4 993(38.01)148(38.57)
不吸烟8 378(61.97)8 143(61.99)235(61.43)
糖尿病<0.001
是1 265(9.36)1 199(9.13)66(17.24)
否12 254(90.64)11 937(90.87)317(82.76)
饮酒状况0.150
饮酒9 874(73.04)9 606(73.13)268(69.91)
不饮酒3 645(26.96)3 530(26.87)115(30.09)
LMR分位数<0.001
Q13 681(27.23)3 484(26.52)197(51.56)
Q23 635(26.89)3 551(27.03)84(21.93)
Q33 207(23.72)3 140(23.90)67(17.39)
Q42 997(22.17)2 962(22.55)35(9.11)
), ArticleFig(id=1324077966191370485, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=CN, label=表1, caption=

按乳腺癌状态分层的参与者基线特征 ［（），n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总数(n=13 519)非乳腺癌 （n=13 136）乳腺癌(n=383)P值
年龄（岁）47.09±16.6547.99±16.9565.76±11.53<0.001
血液总钙吸收9.45±0.089.37±0.379.42±0.420.002
BMI39.8±3.1129.20±7.5329.39±6.730.615
LMR1.85±0.391.41±0.361.19±0.41<0.001
绝经状态<0.001
绝经6 920（51.18）6 568(50.20)352(91.72)
非绝经6 599（48.81）6 568(49.80)31(8.28)
种族<0.001
墨西哥裔美国人1 063（7.86）1 050(7.94)13 (3.37)
其他西班牙裔799（5.91）788(5.85)11(2.90)
非西班牙裔白人9 201（68.05）8 885(67.64)316(82.56)
非西班牙裔黑人1 497（11.07）1 471(11.20)26(6.80)
其他种族959（7.09）942(7.37)17(4. 38)
教育程度0.079
高中以下及同等高中学力4 916（36.36）4 793(36.49)123(32.23)
大学毕业及以上8 603（63.63）8 343(63.51)260(67.77)
婚烟状况0.033
已婚或与伴侣同住8 109(59.98)7 899(60.13)210(54.86)
离婚或丧偶或分居5 410(40.01)5 237(39.87)173(45.14)
高血压<0.001
是4 352(32.19)4 156(31.64)196(51.25)
否9 167(67.81)8 980(68.36)187(48.75)
充血性心力衰竭<0.001
是282(2.09)259(1.97)23(6.04)
否13 237(97.91)12 877(98.03)360(93.96)
冠心病<0.001
是310(2.29)281(2.14)29(7.64)
否13 209(97.71)12 855(97.86)354(92.36)
心绞痛/心肌缺血性疼痛<0.001
是253(1.87)234(1.78)19(4.94)
否13 266(98.13)12 902(98.22)364(95.06)
中风<0.001
是405(3.0)378(2.88)27(7.07)
否13 114(97.00)12 758(97.12)356(92.93)
吸烟状况0.818
吸烟5 141(38.03)4 993(38.01)148(38.57)
不吸烟8 378(61.97)8 143(61.99)235(61.43)
糖尿病<0.001
是1 265(9.36)1 199(9.13)66(17.24)
否12 254(90.64)11 937(90.87)317(82.76)
饮酒状况0.150
饮酒9 874(73.04)9 606(73.13)268(69.91)
不饮酒3 645(26.96)3 530(26.87)115(30.09)
LMR分位数<0.001
Q13 681(27.23)3 484(26.52)197(51.56)
Q23 635(26.89)3 551(27.03)84(21.93)
Q33 207(23.72)3 140(23.90)67(17.39)
Q42 997(22.17)2 962(22.55)35(9.11)
), ArticleFig(id=1324077966266867958, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=EN, label=Table 2, caption=

Multivariable logistic regression results for the association between LMR and breast cancer risk under different adjustment models

, figureFileSmall=null, figureFileBig=null, tableContent=
变量模型1模型2模型3
OR (95%CI)P值OR (95%CI)P值OR (95%CI)P值
LMR0.28 (0.21～0.36)<0.0010.59(0.45～0.78)<0.0010.56(0.42～0.73)<0.001
LMR 四分位
Q11(reference)—1(reference)—1(reference)—
Q20.47 (0.36～0.61)<0.0010.69(0.53～0.91)<0.0080.67(0.51～0.88)<0.005
Q30.42(0.32～0.55)<0.0010.73(0.54～0.97)<0.0300.69(0.52～0.93)<0.015
Q40.29(0.21～0.39)<0.0010.57(0.41～0.79)<0.0010.53(0.38～0.74)<0.001
P趋势值<0.001<0.001<0.001
), ArticleFig(id=1324077966631772407, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=CN, label=表2, caption=

不同调整模型下LMR与乳腺癌风险的多因素logistic回归分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量模型1模型2模型3
OR (95%CI)P值OR (95%CI)P值OR (95%CI)P值
LMR0.28 (0.21～0.36)<0.0010.59(0.45～0.78)<0.0010.56(0.42～0.73)<0.001
LMR 四分位
Q11(reference)—1(reference)—1(reference)—
Q20.47 (0.36～0.61)<0.0010.69(0.53～0.91)<0.0080.67(0.51～0.88)<0.005
Q30.42(0.32～0.55)<0.0010.73(0.54～0.97)<0.0300.69(0.52～0.93)<0.015
Q40.29(0.21～0.39)<0.0010.57(0.41～0.79)<0.0010.53(0.38～0.74)<0.001
P趋势值<0.001<0.001<0.001
), ArticleFig(id=1324077966719852792, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=EN, label=Table.3, caption=

Subgroup analysis of the association between LMR and breast cancer

, figureFileSmall=null, figureFileBig=null, tableContent=
变量OR (95%CI)P值交互作用
P值
绝经状态0.386
绝经0.57(0.43～0.76)<0.001
非绝经0.34(0.10～1.08)0.067
种族0.761
墨西哥裔美国人0.60 (0.24～1.51)0.279
其他西班牙裔0.50 (0.19～1.30)0.155
非西班牙裔白人0.62 (0.43～0.89)0.010
非西班牙裔黑人0.37 (0.19～0.72)0.003
其他种族0.55 (0.20～1.54)0.257
教育程度0.719
高中以下及同等高中学力0.53(0.36～0.78)0.002
大学毕业及以上0.58(0.40～0.83)0.003
婚姻状况0.181
已婚或与伴侣同住0.67(0.46～0.99)0.042
离婚或丧偶或分居0.47(0.32～0.68)<0.001
高血压0.862
是0.55(0.39～0.77)<0.001
否0.57(0.37～0.88)0.010
充血性心力衰竭0.151
是1.07(0.43～2.66)0.891
否0.52(0.39～0.69)<0.001
冠心病0.022
是2.08(0.63～6.80)0.228
否0.51(0.38～0.68)<0.001
心绞痛/心肌缺血性疼痛0.821
是0.63(0.20～2.02)0.437
否0.55(0.41～0.73)<0.001
中风0.416
是0.80(0.32～2.03)0.645
否0.54(0.40～0.72)<0.001
吸烟状况0.162
吸烟0.70(0.46～1.08)0.108
不吸烟0.47(0.33～0.68)<0.001
糖尿病0.010
是1.12(0.62～2.01)0.716
否0.46(0.34～0.63)<0.001
饮酒状况0.297
饮酒0.62(0.44～0.88)0.007
不饮酒0.47(0.31～0.71)<0.001
), ArticleFig(id=1324077967009259769, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077959350460602, language=CN, label=表3, caption=

LMR与乳腺癌关联的亚组分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量OR (95%CI)P值交互作用
P值
绝经状态0.386
绝经0.57(0.43～0.76)<0.001
非绝经0.34(0.10～1.08)0.067
种族0.761
墨西哥裔美国人0.60 (0.24～1.51)0.279
其他西班牙裔0.50 (0.19～1.30)0.155
非西班牙裔白人0.62 (0.43～0.89)0.010
非西班牙裔黑人0.37 (0.19～0.72)0.003
其他种族0.55 (0.20～1.54)0.257
教育程度0.719
高中以下及同等高中学力0.53(0.36～0.78)0.002
大学毕业及以上0.58(0.40～0.83)0.003
婚姻状况0.181
已婚或与伴侣同住0.67(0.46～0.99)0.042
离婚或丧偶或分居0.47(0.32～0.68)<0.001
高血压0.862
是0.55(0.39～0.77)<0.001
否0.57(0.37～0.88)0.010
充血性心力衰竭0.151
是1.07(0.43～2.66)0.891
否0.52(0.39～0.69)<0.001
冠心病0.022
是2.08(0.63～6.80)0.228
否0.51(0.38～0.68)<0.001
心绞痛/心肌缺血性疼痛0.821
是0.63(0.20～2.02)0.437
否0.55(0.41～0.73)<0.001
中风0.416
是0.80(0.32～2.03)0.645
否0.54(0.40～0.72)<0.001
吸烟状况0.162
吸烟0.70(0.46～1.08)0.108
不吸烟0.47(0.33～0.68)<0.001
糖尿病0.010
是1.12(0.62～2.01)0.716
否0.46(0.34～0.63)<0.001
饮酒状况0.297
饮酒0.62(0.44～0.88)0.007
不饮酒0.47(0.31～0.71)<0.001
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淋巴细胞与单核细胞比值与乳腺癌的相关性——一项横断面研究
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李晓玉 1 , 洪珂 1 , 陈梦帆 1 , 姚昶 1, 2
现代预防医学 | 临床与预防 2026,53(5): 954-960
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现代预防医学 |临床与预防 2026 , 53 (5) : 954 -960
淋巴细胞与单核细胞比值与乳腺癌的相关性——一项横断面研究
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李晓玉1, 洪珂1, 陈梦帆1, 姚昶1, 2
作者信息
  • 1.南京中医药大学附属医院，江苏 南京 210029
  • 2.江苏省中医院乳腺外科，江苏 南京 210029
通讯作者:
姚昶，E-mail:
作者简介:

李晓玉（2000-），女，硕士在读，研究方向：中西医防治乳腺癌转移

Association of lymphocyte to monocyte ratio with breast cancer:a cross-sectional study based on NHANES
Xiao-yu LI1, Ke HONG1, Meng-fan CHEN1, Chang YAO1, 2
Affiliations
  • Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China
出版时间: 2026-03-10 doi: 10.20043/j.cnki.MPM.202509108
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摘要
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目的

全身性炎症与免疫状态在癌症发生中起着重要作用，但关于淋巴细胞与单核细胞比值（lymphocyte-to-monocyte ratio，LMR）与乳腺癌发病风险之间关联的研究尚有限。本研究旨在探讨LMR与乳腺癌风险之间的关系。

方法

基于2005—2018年美国国家健康与营养调查中13 519名具备完整LMR及乳腺癌数据的参与者。通过多元加权logistic回归、限制性立方样条、亚组分析，探索LMR与乳腺癌的独立关联性，进行敏感性分析以确保结果的稳定性。

结果

研究显示LMR与乳腺癌风险存在显著U型关系，转折点在1.82，当≤1.82 时，其水平与乳腺癌风险呈显著负相关，每增加一个单位，乳腺癌风险降低76%（OR=0.24,95% CI: 0.18～0.31）；而在该阈值以上，关联不再显著。LMR四分位组中，最高四分位组（Q4）的乳腺癌风险较Q1组显著降低约47%（OR= 0.53，95% CI: 0.38～0.74）。对数似然比检验提示分段线性模型优于线性模型。亚组分析与交互作用检验显示，糖尿病患者与非糖尿病患者在LMR与乳腺癌风险关联性方面存在显著差异。

结论

本研究首次揭示了LMR与乳腺癌风险之间存在非线性（宽U形）关联：无论LMR偏低或偏高均会增加患病风险，保持稳定范围的LMR，可能有助于预防和减缓乳腺癌的发生和发展。未来仍需要大规模前瞻性队列验证。

淋巴细胞/单核细胞比值  /  NHANES  /  乳腺癌  /  风险评估  /  炎症标志物
Objective

Systemic inflammation and immune status play critical roles in carcinogenesis. However, evidence regarding the association between the lymphocyte-to-monocyte ratio (LMR) and the risk of breast cancer (BC) remains limited.This study aims to investigate the relationship between LMR and BC risk.

Methods

A total of 13 519 participants with complete LMR and BC data were identified from the U.S. National Health and Nutrition Examination Survey (NHANES) 2005—2018. Multivariable weighted logistic regression models, restricted cubic spline analyses, and subgroup analyses were conducted to evaluate the independent association between LMR and BC risk. Sensitivity analyses were performed to assess the robustness of the findings.

Results

A significant U-shaped association was observed between LMR and BC risk, with an inflection point at 1.82. When LMR was ≤1.82, it was inversely associated with BC risk, with each one-unit increase in LMR corresponding to a 76% reduction in BC risk (OR=0.24, 95% CI: 0.18-0.31). Above this threshold, the association was no longer statistically significant. In the LMR quartile groups, the highest quartile (Q4) showed a significant reduction in breast cancer risk of approximately 47% compared to the Q1 group (OR=0.53, 95% CI: 0.38-0.74). Likelihood ratio tests indicated that the piecewise linear model provided a better fit than the linear model. Subgroup and interaction analyses revealed significant differences in the association between LMR and BC risk between participants with and without diabetes.

Conclusion

This study is the first to demonstrate a non-linear (broad U-shaped) association between LMR and BC risk,indicating that both low and high LMR levels are associated with an increased risk of BC. Maintaining LMR within a stable range may help prevent and slow the development and progression of breast cancer. Further large-scale prospective cohort studies are warranted to validate these findings.

Lymphocyte to monocyte ratio  /  NHANES  /  Breast cancer  /  Risk assessment  /  Inflammatory markers
李晓玉, 洪珂, 陈梦帆, 姚昶. 淋巴细胞与单核细胞比值与乳腺癌的相关性——一项横断面研究. 现代预防医学, 2026 , 53 (5) : 954 -960 . DOI: 10.20043/j.cnki.MPM.202509108
Xiao-yu LI, Ke HONG, Meng-fan CHEN, Chang YAO. Association of lymphocyte to monocyte ratio with breast cancer:a cross-sectional study based on NHANES[J]. Modern Preventive Medicine, 2026 , 53 (5) : 954 -960 . DOI: 10.20043/j.cnki.MPM.202509108
正文
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根据国际癌症研究机构的最新估算，乳腺癌占所有新发癌症病例的11.6%，对生命健康构成重大威胁。基于人口统计的预测显示，到2050年，新发癌症病例数将达到3 500万例[1]。乳腺癌的病因复杂，其化疗敏感性与疗效受多种因素影响，包括激素受体状态、Ki-67指数、人表皮生长因子受体2（human epidermal growth factor receptor 2,HER2）表达、淋巴血管浸润、肿瘤分期、组织学分级及分子分类等，但具体机制尚不明确[2]。
研究表明，肿瘤中存在的炎性细胞和细胞因子更可能促进肿瘤生长、进展及免疫抑制，而非触发有效的宿主抗肿瘤反应；癌症易感性与严重程度可能与炎性细胞因子基因的功能性多态性密切相关[3]。癌细胞与周围基质细胞及炎性细胞通过精密协调的双向交互作用，共同构筑炎性肿瘤微环境[4-5]。系统性免疫炎性指标、中性粒细胞淋巴细胞比值、血小板淋巴细胞比值及淋巴细胞与单核细胞比值（lymphocyte-to-monocyte ratio，LMR）——这些通过外周血流细胞计数测定的指标，是肿瘤相关全身性炎症的重要临床标志物，也是预测肿瘤进展的关键指标[6]，并在多种癌症中展现出显著的预后价值[7-9]。Kristijan Skok[10]发现，高肿瘤浸润淋巴细胞浸润（尤其是CD8+T细胞）常与子宫内膜癌、侵袭性乳腺癌及卵巢上皮肿瘤预后改善相关。淋巴细胞亚群是机体免疫功能的直观体现[11]，LMR亦清晰反映慢性炎症活动程度。
目前关于研究探讨乳腺癌患病风险与LMR之间的关联相对较少。本研究利用2005—2018年开展的美国国家健康与营养调查（National Healthnd Nutrition Examination Survey NHANES）数据，旨在探索美国女性中LMR与乳腺癌风险的关系。
1　对象与方法
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1.1　研究人群
本横断面研究基于2005—2018年NHANES公开数据。相关资料均可在www.cdc.gov/nchs/nhanes/获取。纳入对象需具备完整的乳腺癌及其风险因素数据。最终共纳入13 519名20岁及以上女性，其实验室检测结果、乳腺癌病史及相关协变量信息均完整。筛选流程见图1。
1.2　LMR及乳腺癌评估
LMR是评估机体炎症状态的有效指标，计算方法为外周血淋巴细胞计数除以单核细胞计数[12-13]。具体检测流程可见《实验室医学技术员操作手册》（https://wwwn.cdc.gov/nchs/nhanes/）。血常规均在体检中心按照统一标准在单次访视时采集，样本类型为冷藏血清。分析前对连续变量进行正态性检验。原始LMR分布呈明显右偏，Shapiro-Wilk 检验提示其偏离正态分布，因此对LMR进行自然对数转换［LN(LMR)］以改善分布特性。乳腺癌病史的判定依据参与者对以下问题的自我报告回答：“医生或其他医疗专业人员是否曾告知您患有癌症？”以及“何种癌症？”，若参与者选择“是”且回答“乳腺癌”，则被归类为有乳腺癌病史。
1.3　协变量
基于既往研究中已证实与乳腺癌风险或乳腺癌相关的生活方式及代谢因素[14-17]，纳入多项协变量，包括年龄、种族、教育程度、婚姻状况、总钙（mg/dl）、身体质量指数（body mass index,BMI，kg/㎡）、高血压、心血管疾病、中风史、吸烟、糖尿病、饮酒及绝经状况。结合问卷RHQ031“过去12个月是否有月经期？”和问卷RHQ050“当前是否怀孕？”，回答均为“否”的定义为绝经状态[18]。心血管疾病经医疗专业人员诊断，包括心绞痛/心肌缺血性疼痛、冠心病和充血性心力衰竭。上述变量均通过标准化的NHANES访谈和体检收集。
1.4　统计分析
遵循美国疾病控制与预防中心指南，所有统计分析均采用复杂分层全簇抽样法并应用适当的NHANES样本权重[19]。本研究使用EmpowerStats软件（X&Y Solutions Inc., Boston, MA）及 R 软件（版本 4.1.0）进行统计分析。正态分布的连续变量采用（x±s）表示，非正态分布采用［M（P25，P75）］表示；分类变量以加权百分比呈现。连续变量组间比较采用加权t检验，分类变量采用加权χ2检验或Fisher精确检验。构建加权多元logistic回归模型，计算比值比及其95%置信区间。依次建立三类模型：模型1为未调整模型；模型2调整年龄和种族；模型3在模型2基础上进一步调整教育程度、婚姻状况、BMI、高血压、糖尿病、吸烟、饮酒、心血管疾病（冠心病、心绞痛、充血性心力衰竭、中风）、绝经状态及总钙水平等混杂因素。将LMR四分位数组中位数作为连续变量纳入模型行线性趋势检验。采用限制性立方样条（restricted cubic splines, RCS）评估LMR与乳腺癌风险的非线性暴露-反应关系，并进行阈值效应分析以确定潜在拐点。非线性趋势通过似然比检验进行评估。此外，按年龄、种族、绝经状态、BMI、吸烟饮酒状况及慢性疾病等进行分层与交互作用分析，各亚组采用相同的协变量调整策略。交互作用的显著性以交互项的P值判定，统计检验均为双侧检验，检验水准α=0.05。
2　结果
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2.1　研究对象的基线特征
共纳入13 519名女性参与者，其中383人（2.8%）报告有乳腺癌病史。研究人群平均年龄为（47.09±16.65）岁，平均LMR为1.85。与无乳腺癌病史者相比，乳腺癌病史者年龄更大，非西班牙裔白人比例及总钙水平更高，高血压、心血管疾病、糖尿病和中风患病率显著更高（均P<0.001）。无乳腺癌史者的LMR水平显著高于乳腺癌患者（P<0.001）。两组在教育程度、婚姻状况、吸烟饮酒习惯及BMI方面无显著差异（P>0.05）。见表1。
2.2　LMR与乳腺癌风险的关联分析
如表2所示，较高的LMR水平与乳腺癌风险呈负相关。为控制潜在混杂因素，本研究构建了三个多因素logistic回归模型，在未调整模型中，LMR每升高1个单位，乳腺癌风险显著降低72%（OR=0.28，95% CI: 0.21～0.36）。在进一步调整人口学特征及临床相关协变量后，该负向关联仍然保持显著。按LMR四分位数分组分析显示，与最低四分位组（Q1）相比，较高LMR水平组的乳腺癌风险呈逐渐下降趋势。在完全调整模型中，最高四分位组（Q4）的乳腺癌风险较Q1组显著降低约47%（OR=0.53，95% CI: 0.38～0.74）。趋势检验结果进一步表明，随着LMR水平升高，乳腺癌风险显著下降（P趋势值< 0.001）。
此外，采用平滑曲线拟合模型评估LMR与乳腺癌风险之间的非线性关联。结果显示二者呈显著的宽U形关联。RCS分析结果与之一致。模型整体关联具有统计学意义（P-overall<0.001），且存在明显的非线性趋势（非线性P值 <0.001）。阈值分析表明，LMR 的拐点为1.82。当LMR<1.82时，每增加1个单位，乳腺癌风险降低约72%（OR=0.28，95% CI：0.21～0.36）；当LMR≥1.82时，该关联不再显著（OR= 1.85，95% CI：0.63～5.41）。对数似然比检验进一步支持上述非线性关系。由于本研究为横断面设计，无法确定因果关系，仍需前瞻性研究加以验证。见图2、3。
2.3　亚组分析
本研究通过亚组分析评估不同人群特征下LMR与乳腺癌风险的关联差异。结果显示，LMR与乳腺癌风险的负相关总体一致，但效应量存在差异。在绝经女性、非西班牙裔白人/黑人等亚组中，LMR升高均与乳腺癌风险显著降低相关。相比之下，糖尿病状态显示出显著效应修饰作用：在无糖尿病人群中，较高LMR与乳腺癌风险降低显著相关，而在糖尿病患者中，该关联不再显著。提示糖尿病可能影响LMR与乳腺癌风险之间的关联方向或强度。见表3。
3　讨论
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本研究评估了LMR与女性乳腺癌患病率的关联，显示二者之间存在显著的宽U形非线性关联：LMR中等水平时风险最低，偏低或偏高均与风险升高相关；亚组与交互作用分析提示糖尿病可能修饰该关联，经过多模型调整多种混杂因素后非线性关系仍稳健。既往研究多聚焦乳腺癌患者LMR的预后意义，普遍报道低LMR与较差生存相关，高LMR提示较好预后[20-21]，低LMR常提示机体处于慢性全身性炎症和/或适应性免疫功能低下状态，常作为多种癌症的不良预后指标[7,22]。Hasan等[23]发现，鳞状细胞癌患者LMR显著低于良性病变及非典型增生组，进一步支持LMR在肿瘤相关潜在价值。与其他炎症指标相比，本研究从一般人群层面补充了LMR在乳腺癌风险评估中的证据。中性粒细胞/淋巴细胞比值和血小板/淋巴细胞比值在多研究中被证实与乳腺癌不良预后及复发风险增加相关[24]。相比之下，LMR综合反映了抗肿瘤免疫效应和促肿瘤炎性/髓系通路（单核细胞-肿瘤相关巨噬细胞轴）的平衡，低LMR在多种实体瘤中被证实为独立不良预后因子[25]。本研究在一般人群中观察到LMR与乳腺癌风险的U形关系，提示其在不同疾病阶段中可能反应不同的免疫炎症特征，但尚不能据此判断其相对其它指标的优劣。
LMR偏低通常反映外周血淋巴细胞减少和/或单核细胞增多，提示适应性免疫功能受损并伴随持续的髓系炎性激活。研究显示，乳腺癌患者外周血中CD4+和CD8+T细胞数量及亚群比例异常，调节性T细胞（Treg）比例升高，与肿瘤负荷及分期密切相关。晚期或转移性患者常伴有外周单核细胞增多及效应T细胞衰竭表型，提示髓系细胞扩增及其免疫抑制作用参与肿瘤进展[26]。慢性炎症贯穿肿瘤发生、发展及转移，癌细胞、基质细胞及炎性细胞相互作用，形成促肿瘤的炎性肿瘤微环境[4]。活性氧通路在此过程中发挥关键作用[27]。单核细胞及中性粒细胞释放的TNF-α、IL-6、IL-1β等促炎因子[28]水平升高，可促进细胞增殖、抑制凋亡并诱导DNA损伤和血管生成[29]。同时，淋巴细胞数量减少或功能受损削弱免疫能力，增加乳腺癌风险。高LMR端乳腺癌风险升高是本研究的独特发现，其机制尚需进一步阐明。高LMR可能反映单核细胞相对减少，研究[30]显示炎症性单核细胞在肿瘤内T细胞刺激中发挥核心作用，可获取肿瘤细胞抗原激活T细胞，促进抗肿瘤免疫反应。肿瘤微环境中MAPK、PGE2等信号通路异常可抑制Ⅰ型干扰素产生，破坏炎性单核细胞的状态并抑制T细胞刺激，促成免疫逃逸。当LMR异常升高时，单核细胞减少可能意味着“炎症性单核细胞-T细胞”轴功能受损；同时，表面“增多”的淋巴细胞可能以功能衰竭或免疫抑制性亚群（如Treg、耗竭型CD8+ T细胞）为主，而非有效抗肿瘤细胞。这可能反映对亚临床肿瘤或慢性刺激的补偿性但无效的免疫反应，从而解释LMR升高与乳腺癌风险增加的现象[31]，类似的非线性关联在其他非肿瘤疾病中亦有报道[32]。
本研究发现糖尿病状态修饰LMR与乳腺癌风险的关系。糖尿病相关的高血糖、胰岛素抵抗和慢性低度炎症可影响免疫功能，改变LMR所反映的炎症免疫平衡[33-34]。本研究中，该关联主要见于无糖尿病人群，在糖尿病患者中明显减弱，提示代谢异常可能是LMR用于乳腺癌风险评估时须考虑的修饰因素。既往研究显示，低LMR在糖尿病或肥胖合并高血压人群中与全因及心血管死亡风险升高相关[35-36]，且糖尿病本身与乳腺癌发病风险增加相关[37]。但仍需前瞻性队列验证。
本研究优势在于基于NHANES全国代表性人群数据库，系统调整多种协变量并检验结果稳健性，探索了非线性关系及交互作用。然而，本研究为横断面设计限制了因果推断；部分重要乳腺癌危险因素缺乏；LMR仅基于一次性血常规检测，未能评估动态变化；且缺乏肿瘤分期、亚型和预后信息。
综上，本研究揭示了LMR与乳腺癌风险的非线性U型关系，并确定了阈值；阈值以下，LMR增加与乳腺癌风险降低相关；阈值以上，LMR增加则与乳腺癌风险升高相关。
基金
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  • 2025年江苏省研究生科研创新计划(KYCX25_2224)
文献
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2026年第53卷第5期
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doi: 10.20043/j.cnki.MPM.202509108
  • 接收时间：2025-09-10
  • 首发时间：2026-11-02
  • 出版时间：2026-03-10
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  • 收稿日期：2025-09-10
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2025年江苏省研究生科研创新计划(KYCX25_2224)
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    1.南京中医药大学附属医院，江苏 南京 210029
    2.江苏省中医院乳腺外科，江苏 南京 210029

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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
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
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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