Email Alert | RSS

北京大学学报（医学版） ›› 2022, Vol. 54 ›› Issue (4): 636-643. doi: 10.19723/j.issn.1671-167X.2022.04.009

• 论著 • 上一篇    下一篇

代谢综合征与肾透明细胞癌患者预后的相关性

左美妮,杜依青,于路平,戴翔,徐涛*()   

  1. 北京大学人民医院泌尿外科，北京 10044
  • 收稿日期:2022-03-19 出版日期:2022-08-18 发布日期:2022-08-11
  • 通讯作者: 徐涛 E-mail:xutao@pkuph.edu.com
  • 基金资助:
    国家自然科学基金(81872086);北京大学人民医院研究与发展基金(RDY2018-18)

Correlation between metabolic syndrome and prognosis of patients with clear cell renal cell carcinoma

Mei-ni ZUO,Yi-qing DU,Lu-ping YU,Xiang DAI,Tao XU*()   

  1. Department of Urology, Peking University People's Hospital, Beijing 100044, China
  • Received:2022-03-19 Online:2022-08-18 Published:2022-08-11
  • Contact: Tao XU E-mail:xutao@pkuph.edu.com
  • Supported by:
    the National Natural Science Foundation of China(81872086);the Peking University People's Hospital Scientific Research Developments Funds(RDY2018-18)

RICH HTML

   

PDF (PC)

摘要：

目的: 探讨肾透明细胞癌(clear cell renal cell carcinoma，ccRCC)手术后患者中代谢综合征(metabolic syndrome，MetS)与ccRCC预后的相关性。方法: 选择2009年1月—2014年11月于北京大学人民医院行根治性肾切除术或部分肾切除术患者的病例资料进行回顾性分析，共收集到342例ccRCC患者，记录患者的临床资料和病理资料，以及治疗前的实验室检查结果。将患者分为合并MetS组及未合并MetS组，对两组患者的总生存期(overall survival，OS)、肿瘤特异性生存期(cancer-specific survival，CSS)和无进展生存期(progression-free survival，PFS)进行单变量Cox回归分析与亚组分析。对两组患者以及各亚组的OS、CSS以及PFS使用Kaplan-Meier法绘制生存曲线进行生存分析。结果: 单变量Cox回归分析发现，MetS是ccRCC术后OS [风险比(hazard ratio，HR)=0.551，95%CI：0.321~0.949，P=0.031]、CSS(HR=0.460，95%CI 0.234~0.905，P=0.025)以及PFS(HR=0.585，95%CI：0.343~0.998，P=0.049)的保护因素。在肿瘤直径≤4 cm的亚组，MetS与术后OS(HR= 0.857，95%CI：0.389~1.890，P=0.702)、CSS(HR=1.129，95%CI：0.364~3.502，P=0.833)以及PFS(HR=1.554，95%CI：0.625~3.864，P=0.343)无明显相关性。在肿瘤直径>4 cm的亚组，MetS是ccRCC术后OS(HR=0.377，95%CI：0.175~0.812，P=0.013)、CSS(HR=0.280，95%CI：0.113~0.690，P=0.006)以及PFS(HR=0.332，95%CI：0.157~0.659，P=0.002)的保护因素；肥胖是术后CSS(HR=0.464，95%CI：0.219~0.981，P=0.044)和PFS(HR=0.445，95%CI：0.238~0.833，P=0.011)的保护因素。Kaplan-Meier生存分析显示，合并MetS较未合并MetS的患者术后远期生存更佳，二者OS(P=0.029)、CSS(P=0.021)以及PFS(P=0.046)差异均具有统计学意义；对肿瘤直径≤4 cm的亚组，合并MetS与未合并MetS的ccRCC患者术后OS(P=0.702)、CSS(P=0.833)以及PFS(P=0.339)差异均无统计学意义；对肿瘤直径> 4 cm的亚组，合并MetS的患者OS(P=0.010)、CSS(P=0.003)以及PFS(P=0.001)均高于未合并MetS的患者。结论: MetS是ccRCC患者术后OS、CSS和PFS的保护因素，该现象在肿瘤直径>4 cm亚组中更为显著；MetS的组分中肥胖与ccRCC术后OS以及CSS相关。

关键词: 代谢综合征, 肾透明细胞癌, 总生存期, 肿瘤特异性生存期, 无进展生存期

Abstract:

Objective: To investigate the effects of MetS on the prognosis of patients with clear cell renal cell carcinoma (ccRCC). Methods: Clinical and pathological data and the laboratory test of ccRCC 342 patients with diverticular stones who underwent ccRCC who underwent radical or partial nephrectomy were retrospectively collected and analyzed.The patients were divided into MetS group and non-MetS group, and the subgroups were defined according to the tumor size. The overall survival (OS), cancer-specific survival (CSS), and progression-free survival (PFS) of the two groups were analyzed by univariate Cox analysis, and the subgroup analyses were also performed. Kaplan-Meier survival curve and survival analysis for OS, CSS, and PFS of the two groups and the subgroups were conducted. Results: Univariate Cox analysis showed that MetS was a protective factor of postoperative OS [hazard ratio (HR)=0.551, 95%CI: 0.321-0.949, P=0.031], CSS (HR=0.460, 95%CI: 0.234-0.905, P=0.025), and PFS (HR 0.585, 95%CI: 0.343-0.998, P=0.049) in the patients with ccRCC. In the subgroup with tumor size≤4 cm, MetS was not associated with postoperative OS (HR=0.857, 95%CI: 0.389-1.890, P=0.702), CSS (HR=1.129, 95%CI: 0.364-3.502, P=0.833), and PFS (HR=1.554, 95%CI: 0.625-3.864, P=0.343). In the subgroup with tumor size>4 cm, Mets was a protective factor of postoperative OS (HR=0.377, 95%CI: 0.175-0.812, P=0.013), CSS (HR=0.280, 95%CI: 0.113-0.690, P=0.006), and PFS (HR=0.332, 95%CI: 0.157-0.659, P=0.002); Obesity was a protective factor of postoperative CSS (HR=0.464, 95%CI: 0.219-0.981, P=0.044), and PFS (HR=0.445, 95%CI: 0.238-0.833, P=0.011). Kaplan-Meier survival analysis showed that the long-term survival of patients with MetS was better than those without MetS in OS (P=0.029), CSS (P=0.021), and PFS (P=0.046); for the subgroup with tumor size≤4 cm, there was no significant difference in postoperative OS (P=0.702), CSS (P=0.833), and PFS (P=0.339) between patients with and without MetS; For the subgroup with tumor size>4 cm, the OS (P=0.010), CSS (P=0.003), and PFS (P=0.001) of patients with MetS were better than those without MetS. Conclusion: MetS was a protective factor of postoperative OS, CSS, and PFS in the patients with ccRCC, which was more obvious in subgroup with tumor size>4 cm. And obesity, the component of MetS, was correlated with postoperative OS and CSS.

Key words: Metabolic syndrome, Clear cell renal cell carcinoma, Overall survival, Cancer-specific survival, Progression-free survival

中图分类号: 

  • R737

表1

肾透明细胞癌患者基础数据"

Variable non-MetS
(n=184)		 MetS
(n=158)		 P
Age/years, n(%) 0.009
     < 60 111 (60.33) 73 (46.20)
    ≥60 73 (39.67) 85 (53.80)
Gender, n(%) < 0.001
    Male 146 (79.35) 81 (51.27)
    Female 38 (20.65) 77 (48.73)
Smoking, n(%) 0.097
    No 116 (63.04) 113 (71.52)
    Yes 68 (36.96) 45 (28.48)
Clinical manifestation, n(%) 0.790
    Incidental 128 (69.57) 112 (70.89)
    Symptomatic 56 (30.43) 46 (29.11)
Tumor size, n(%) 0.846
    ≤4 cm 116 (63.04) 98 (62.03)
    >4 cm 68 (36.96) 60 (37.97)
T stage, n(%) 0.083
    T1-T2 167 (90.76) 151 (95.57)
    T3-T4 17(9.24) 7(4.43)
Tumor grade, n(%) 0.536
    1-2 164 (89.13) 144 (91.14)
    3-4 20 (10.87) 14 (8.86)

表2

预测总生存期的单因素Cox回归分析"

CovariatesOS CSS PFS
HR(95%CI) P HR(95%CI) P HR(95%CI) P
Age (≥ 60 years vs. < 60 years) 1.709 (1.013-2.885) 0.045 1.061 (0.570-1.973) 0.852 0.983 (0.589-1.640) 0.947
Gender (male vs. female) 2.075 (1.099-3.918) 0.024 1.634 (0.798-3.342) 0.179 1.754 (0.962-3.195) 0.067
Smoking (yes vs.no) 1.249 (0.735-2.124) 0.411 0.999 (0.515-1.936) 0.998 1.059 (0.617-1.816) 0.836
Clinical manifestation (symptomatic vs. incidental) 2.127 (1.267-3.571) 0.004 2.142 (1.149-3.996) 0.017 2.307 (1.381-3.853) 0.001
Tumor size (>4 cm vs.≤4 cm) 2.354 (1.399-3.961) 0.001 4.055 (2.062-7.975) < 0.001 3.895 (2.255-6.730) < 0.001
T stage (T3-T4 vs. T1-T2) 2.156 (0.977-4.759) 0.057 2.183 (0.854-5.582) 0.103 2.014 (0.914-4.440) 0.083
Tumor grade (3-4 vs. 1-2) 2.166 (1.122-4.182) 0.021 2.780 (1.323-5.840) 0.007 2.246 (1.166-4.326) 0.016
MetS (yes vs. no) 0.551 (0.321-0.949) 0.031 0.460 (0.234-0.905) 0.025 0.585 (0.343-0.998) 0.049
Obesity (yes vs. no) 0.511 (0.304-0.859) 0.011 0.532 (0.285-0.993) 0.048 0.629 (0.377-1.049) 0.075
Hypertension (yes vs. no) 0.887 (0.512-1.535) 0.667 0.820 (0.428-1.572) 0.550 0.949 (0.549-1.639) 0.851
Diabetes mellitus (yes vs. no) 1.262 (0.754-2.114) 0.376 1.045 (0.562-1.944) 0.890 0.839 (0.501-1.407) 0.506
Hyper TG (yes vs. no) 0.727 (0.357-1.481) 0.380 0.574 (0.225-1.465) 0.246 0.805 (0.408-1.589) 0.532
Low HDL-C (yes vs. no) 1.021 (0.579-1.799) 0.943 0.969 (0.492-1.908) 0.928 1.211 (0.673-2.177) 0.523

图1

代谢综合征与RCC患者预后的相关性分析"

表3

不同肿瘤直径亚组分析与OS"

CovariatesTumor size≤4 cm Tumor size>4 cm
HR(95%CI) P HR(95%CI) P
Age (≥ 60 years vs. < 60 years) 3.129 (1.306-7.494) 0.010 1.099 (0.553-2.182) 0.788
Gender (male vs. female) 2.943 (1.010-8.575) 0.048 1.596 (0.719-3.545) 0.251
Smoking (yes vs.no) 1.398 (0.628-3.113) 0.412 1.123 (0.551-2.287) 0.750
Clinical manifestation(symptomatic vs.incidental) 2.064 (0.890-4.787) 0.091 1.534 (0.770-3.054) 0.223
T stage (T3-T4 vs. T1-T2) 2.305 (0.541-9.815) 0.259 1.649 (0.634-4.288) 0.305
Tumor grade (3-4 vs. 1-2) 2.503 (0.855-7.327) 0.094 1.618 (0.701-3.736) 0.259
MetS (yes vs. no) 0.857 (0.389-1.890) 0.702 0.377 (0.175-0.812) 0.013
Obesity (yes vs. no) 0.517 (0.234-1.142) 0.103 0.506 (0.255-1.004) 0.051
Hypertension (yes vs. no) 0.905 (0.399-2.051) 0.811 0.734 (0.349-1.545) 0.416
Diabetes mellitus (yes vs. no) 1.879 (0.829-4.260) 0.131 1.069 (0.535-2.133) 0.851
Hyper TG (yes vs. no) 0.460 (0.138-1.539) 0.208 1.299 (0.534-3.157) 0.564
Low HDL-C (yes vs. no) 0.993 (0.428-2.305) 0.988 0.936 (0.434-2.019) 0.866

表4

不同肿瘤直径亚组分析与CSS"

CovariatesTumor size≤4 cm Tumor size>4 cm
HR(95%CI) P HR(95%CI) P
Age (≥ 60 years vs. < 60 years) 2.388 (0.719-7.930) 0.155 0.726 (0.340-1.550) 0.408
Gender (male vs. female) 1.113 (0.335-3.698) 0.861 1.906 (0.772-4.704) 0.162
Smoking (yes vs.no) 0.420 (0.092-1.919) 0.263 1.316 (0.616-2.811) 0.478
Clinical manifestation(symptomatic vs.incidental) 0.882 (0.193-4.027) 0.871 1.752 (0.828-3.707) 0.143
T stage (T3-T4 vs. T1-T2) 0.047 (0.000-24607) 0.649 2.011 (0.760-3.321) 0.159
Tumor grade (3-4 vs. 1-2) 2.853 (0.624-13.032) 0.176 2.054 (0.872-4.840) 0.100
MetS (yes vs. no) 1.129 (0.364-3.502) 0.833 0.280 (0.113-0.690) 0.006
Obesity (yes vs. no) 0.692 (0.223-2.148) 0.524 0.464 (0.219-0.981) 0.044
Hypertension (yes vs. no) 1.054 (0.317-3.505) 0.931 0.597 (0.275-1.294) 0.191
Diabetes mellitus (yes vs. no) 3.067 (0.830-11.335) 0.093 0.798 (0.369-1.730) 0.568
Hyper TG (yes vs. no) 0.317 (0.041-2.457) 0.272 0.947 (0.328-2.739) 0.921
Low HDL-C (yes vs. no) 1.356 (0.366-5.018) 0.648 0.727 (0.328-1.610) 0.431

表5

不同肿瘤直径亚组分析与PFS"

CovariatesTumor size≤4 cm Tumor size>4 cm
HR(95%CI) P HR(95%CI) P
Age (≥ 60 years vs. < 60 years) 1.642 (0.660-4.082) 0.286 0.750 (0.398-1.413) 0.374
Gender (male vs. female) 1.601 (0.576-4.445) 0.367 1.716 (0.817-3.606) 0.154
Smoking (yes vs.no) 0.393 (0.115-1.349) 0.138 1.483 (0.792-2.779) 0.218
Clinical manifestation(symptomatic vs.incidental) 1.586 (0.571-4.408) 0.376 1.656 (0.887-3.091) 0.113
T stage (T3-T4 vs. T1-T2) 0.047 (0.000-1409) 0.561 1.826 (0.806-4.141) 0.149
Tumor grade (3-4 vs. 1-2) 0.767 (0.102-5.750) 0.796 2.115 (1.033-4.330) 0.041
MetS (yes vs. no) 1.554 (0.625-3.864) 0.343 0.332 (0.157-0.659) 0.002
Obesity (yes vs. no) 1.182 (0.465-3.004) 0.726 0.445 (0.238-0.833) 0.011
Hypertension (yes vs. no) 1.137 (0.432-2.996) 0.794 0.691 (0.356-1.339) 0.273
Diabetes mellitus (yes vs. no) 2.229 (0.847-5.867) 0.104 0.586 (0.298-1.154) 0.122
Hyper TG (yes vs. no) 0.933 (0.310-2.811) 0.902 0.953 (0.399-2.276) 0.913
Low HDL-C (yes vs. no) 3.925 (0.906-17.004) 0.068 0.676 (0.349-1.312) 0.248

图2

不同肿瘤直径亚组中代谢综合征与RCC患者预后的相关性分析"

1 Bray F , Ferlay J , Soerjomataram I , et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2018, 68 (6): 394- 424.
doi: 10.3322/caac.21492
2 Ozbek E , Otunctemur A , Sahin S , et al. Renal cell carcinoma is more aggressive in Turkish patients with the metabolic syndrome[J]. Asian Pac J Cancer Prev, 2013, 14 (12): 7351- 7354.
doi: 10.7314/APJCP.2013.14.12.7351
3 Chakiryan NH, Jiang DD, Gillis KA, et al. Real-world survival outcomes associated with first-line immunotherapy, targeted therapy, and combination therapy for metastatic clear cell renal cell carcinoma[J]. JAMA Netw Open, 2021, 4(5): e2111329[2022-03-01]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8150693/.
4 Jonasch E , Walker CL , Rathmell WK . Clear cell renal cell carcinoma ontogeny and mechanisms of lethality[J]. Nat Rev Nephrol, 2021, 17 (4): 245- 261.
doi: 10.1038/s41581-020-00359-2
5 Zhang GM , Zhu Y , Ye DW . Metabolic syndrome and renal cell carcinoma[J]. World J Surg Oncol, 2014, 12, 236.
doi: 10.1186/1477-7819-12-236
6 Yao F , Bo Y , Zhao L , et al. Prevalence and influencing factors of metabolic syndrome among adults in China from 2015 to 2017[J]. Nutrients, 2021, 13 (12): 4475.
doi: 10.3390/nu13124475
7 Bovolini A , Garcia J , Andrade MA , et al. Metabolic syndrome pathophysiology and predisposing factors[J]. Int J Sports Med, 2021, 42 (3): 199- 214.
doi: 10.1055/a-1263-0898
8 Ewertz M , Jensen MB , Gunnarsdóttir K , et al. Effect of obesity on prognosis after early-stage breast cancer[J]. J Clin Oncol, 2011, 29 (1): 25- 31.
doi: 10.1200/JCO.2010.29.7614
9 Qi J , An R , Bhatti P , et al. Anti-hypertensive medications and risk of colorectal cancer: A systematic review and meta-analysis[J]. Cancer Causes Control, 2022, 33 (6): 801- 812.
doi: 10.1007/s10552-022-01570-1
10 Yang X, Li X, Dong Y, et al. Effects of metabolic syndrome and its components on the prognosis of endometrial cancer[J]. Front Endocrinol (Lausanne), 2021, 12: 780769[2022-03-01]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8717682/.
11 Bulut S , Aktas BK , Erkmen AE , et al. Metabolic syndrome prevalence in renal cell cancer patients[J]. Asian Pac J Cancer Prev, 2014, 15 (18): 7925- 7928.
doi: 10.7314/APJCP.2014.15.18.7925
12 Yu Y , Gong L , Ye J . The role of aberrant metabolism in cancer: Insights into the interplay between cell metabolic reprogramming, metabolic syndrome, and cancer[J]. Front Oncol, 2020, 10, 942.
doi: 10.3389/fonc.2020.00942
13 Luzzago S , Palumbo C , Rosiello G , et al. Metabolic syndrome predicts worse perioperative outcomes in patients treated with partial nephrectomy for renal cell carcinoma[J]. Urology, 2020, 140, 91- 97.
doi: 10.1016/j.urology.2020.02.019
14 Zhang Y , Wu T , Xie J , et al. Effects of metabolic syndrome on renal function after radical nephrectomy in patients with renal cell carcinoma[J]. Int Urol Nephrol, 2021, 53 (10): 2127- 2135.
doi: 10.1007/s11255-020-02759-6
15 Kriegmair MC , Mandel P , Porubsky S , et al. Metabolic syndrome negatively impacts the outcome of localized renal cell carcinoma[J]. Horm Cancer, 2017, 8 (2): 127- 134.
doi: 10.1007/s12672-017-0289-2
16 Liu Z , Wang H , Zhang L , et al. Metabolic syndrome is associated with improved cancer-specific survival in patients with localized clear cell renal cell carcinoma[J]. Transl Androl Urol, 2019, 8 (5): 507- 518.
doi: 10.21037/tau.2019.10.04
17 Eskelinen TJ , Kotsar A , Tammela TLJ , et al. Components of metabolic syndrome and prognosis of renal cell cancer[J]. Scand J Urol, 2017, 51 (6): 435- 441.
doi: 10.1080/21681805.2017.1352616
18 Du Y , Yang W , Liu H , et al. Perirenal fat as a new independent prognostic factor in patients with surgically treated clear cell renal cell carcinoma[J]. Clin Genitourin Cancer, 2022, 20 (1): e75- e80.
doi: 10.1016/j.clgc.2021.10.006
19 Ford E S . Prevalence of the metabolic syndrome defined by the International Diabetes Federation among adults in the U.S[J]. Diabetes Care, 2005, 28 (11): 2745- 2749.
doi: 10.2337/diacare.28.11.2745
20 Liu M , Wang J , Jiang B , et al. Increasing prevalence of metabolic syndrome in a Chinese elderly population: 2001-2010[J]. PLoS One, 2013, 8 (6): e66233.
doi: 10.1371/journal.pone.0066233
21 Capitanio U , Bensalah K , Bex A , et al. Epidemiology of renal cell carcinoma[J]. Eur Urol, 2019, 75 (1): 74- 84.
doi: 10.1016/j.eururo.2018.08.036
22 Miricescu D , Balan DG , Tulin A , et al. PI3K/AKT/mTOR signalling pathway involvement in renal cell carcinoma pathogenesis (Review)[J]. Exp Ther Med, 2021, 21 (5): 540.
doi: 10.3892/etm.2021.9972
23 Silva A , Pereira SS , Monteiro MP , et al. Effect of metabolic syndrome and individual components on colon cancer characteristics and prognosis[J]. Front Oncol, 2021, 11, 631257.
doi: 10.3389/fonc.2021.631257
24 Mallik R , Chowdhury TA . Metformin in cancer[J]. Diabetes Res Clin Pract, 2018, 143, 409- 419.
doi: 10.1016/j.diabres.2018.05.023
25 Parker AS , Lohse CM , Cheville JC , et al. Greater body mass index is associated with better pathologic features and improved outcome among patients treated surgically for clear cell renal cell carcinoma[J]. Urology, 2006, 68 (4): 741- 746.
doi: 10.1016/j.urology.2006.05.024
26 Wu X , Wang Q , Wang Z , et al. Association of extrarenal invasion patterns and tumor size with the differences in survival outcomes of t3a renal cell carcinoma: a proposal modified T3a stage system is needed[J]. Int J Gen Med, 2022, 15, 367- 378.
doi: 10.2147/IJGM.S344215
27 Dinatale RG , Xie W , Becerra MF , et al. The association between small primary tumor size and prognosis in metastatic renal cell carcinoma: Insights from two independent cohorts of patients who underwent cytoreductive nephrectomy[J]. Eur Urol Oncol, 2020, 3 (1): 47- 56.
doi: 10.1016/j.euo.2019.10.002
[1] 郑生旗,花天池,殷桂草,张伟,姚曳,李一帆. 甘油三酯葡萄糖指数与男性肾结石风险的关联[J]. 北京大学学报（医学版）, 2024, 56(4): 610-616.
[2] 苏俊琪,王晓颖,孙志强. 舌鳞状细胞癌根治性切除术后患者预后预测列线图的构建与验证[J]. 北京大学学报（医学版）, 2024, 56(1): 120-130.
[3] 刘耘充,吴宗龙,葛力源,杜坦,吴雅倩,宋一萌,刘承,马潞林. 肾透明细胞癌中核蛋白1对阿昔替尼耐药的作用及机制[J]. 北京大学学报（医学版）, 2023, 55(5): 781-792.
[4] 崔孟杰,马奇,陈曼曼,马涛,王鑫鑫,刘婕妤,张奕,陈力,蒋家诺,袁雯,郭桐君,董彦会,马军,星一. 不同生长模式与7~17岁儿童青少年代谢综合征的关系[J]. 北京大学学报（医学版）, 2023, 55(3): 415-420.
[5] 蔡天玉,朱振鹏,徐纯如,吉星,吕同德,郭振可,林健. 成纤维细胞生长因子受体2在肾透明细胞癌中的表达及意义[J]. 北京大学学报（医学版）, 2022, 54(4): 628-635.
[6] 刘淼, 何耀, 姜斌, 吴蕾, 王建华, 杨姗姗, 王义艳, 李小鹰. 北京某社区老年人群肱踝脉搏波传导速度与代谢综合征的现况研究[J]. 北京大学学报（医学版）, 2014, 46(3): 429-434.
[7] 闫睿, 栾庆先, 刘力笙, 王兴宇, 李蓬, 沙月琴. 代谢综合征相关线粒体基因单核苷酸多态性与慢性牙周炎的关系[J]. 北京大学学报（医学版）, 2014, 46(2): 264-268.
[8] 陶庆梅, 王胜锋, 孙凤, 陶秋山, 曹纯铿, 詹思延. 北京健康体检人群γ-谷氨酰转肽酶水平与代谢综合征的关联分析[J]. 北京大学学报（医学版）, 2013, 45(03): 364-369.
[9] 于卓人*, 刘丽笙, 栾庆先, 王兴宇, 李蓬, 沙月琴, 刘曦. 北京石景山区老年人群牙周炎与代谢综合征的相关性探讨[J]. 北京大学学报（医学版）, 2012, 44(4): 633-638.
[10] 陈天娇, 季成叶. 北京市中学生腰围与体质指数及代谢综合征相关性状分析[J]. 北京大学学报（医学版）, 2012, 44(3): 355-358.
[11] 李蓬, 张大鹍, 张继睿, 陈力. 伴牙周炎的代谢综合征者动脉硬化早期指标的检测[J]. 北京大学学报（医学版）, 2011, 43(1): 34-39.
[12] 和璐. 牙周炎和代谢综合征[J]. 北京大学学报（医学版）, 2011, 43(1): 13-17.
[13] 胡卫红, 乔杰, 王黎娜, 同军. 多囊卵巢综合征患者代谢综合征的发生及临床特征的相关性[J]. 北京大学学报（医学版）, 2010, 42(2): 159-163.
[14] 刘靖, 杨靓, 孙宁玲, 马济顺, 胡大一. 微量白蛋白尿及假性血友病因子与高血压代谢综合征的关系[J]. 北京大学学报（医学版）, 2007, 39(6): 587-590.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
ISSN 1671-167X
CN 11-4691/R
主管单位：中华人民共和国教育部
主办单位：北京大学
地址： 北京市海淀区学院路38号 北京大学医学部 《北京大学学报（医学版）》
邮编：100191
电话：010-82801551
Email： xbbjb2@bjmu.edu.cn

《北京大学学报（医学版）》
微信公众号
版权所有 © 2018 《北京大学学报（医学版）》编辑部