山东大学学报 (医学版) ›› 2017, Vol. 55 ›› Issue (12): 56-61.doi: 10.6040/j.issn.1671-7554.0.2017.425
柳晓涓1,2,丁荔洁1,2,康凤玲1,2,周苗1,2,薛付忠1,2
LIU Xiaojuan1,2, DING Lijie1,2, KANG Fengling1,2, ZHOU Miao1,2, XUE Fuzhong1,2
摘要: 目的 构建健康管理人群支气管哮喘的风险预测模型。 方法 基于健康管理队列人群,针对队列基线中无支气管哮喘的77 493人健康体检对象随访,随访结局为支气管哮喘;采用单因素Cox回归模型筛选预测因子,单因素有意义的变量进入多因素Cox回归,采用向后消除法筛选变量,利用筛选出的预测因子构建Cox风险预测模型;采用ROC曲线下的面积评估模型判别准确度,十折交叉验证评估模型稳定性。 结果 随访9年期间134人被诊断为支气管哮喘。总发病密度48.28/10万人年。最终纳入模型的变量包括:年龄、嗜酸性粒细胞计数、低密度脂蛋白胆固醇、鼻炎史、气管/支气管炎史、慢性阻塞性肺疾病史。ROC曲线下面积(95%CI)为0.725(0.673~0.778),十折交叉验证ROC曲线下面积(95%CI)为0.707(0.647~0.767)。 结论 本研究构建的支气管哮喘风险预测模型可用于预测体检人群的支气管哮喘发病风险。
中图分类号:
[1] | Horak F, Doberer D, Eber E, et al. Diagnosis and management of asthma-Statement on the 2015 GINA Guidelines[J]. Wien Klin Wochenschr, 2016, 128(15-16): 541-554. |
[2] | Bateman ED, Hurd SS, Barnes PJ, et al. Global strategy for asthma management and prevention: GINA executive summary[J]. Eur Respir J, 2008, 31(1): 143-178. |
[3] | 苏楠. 我国8省市支气管哮喘患者控制水平的流行病学调查[J]. 中华内科杂志, 2014, 53(8): 601-606. SU Nan. An epidemiological survey of current asthma control status in China[J]. Chin J Intern Med, 2014, 53(8): 601-606. |
[4] | Lang DM. Severe asthma: epidemiology, burden of illness, and heterogeneity[J]. Allergy Asthma Proc, 2015, 36(6): 418-424. |
[5] | Barnes PJ. Severe asthma: advances in current management and future therapy[J]. J Allergy Clin Immunol, 2012, 129(1): 48-59. |
[6] | Himes BE, Dai Y, Kohane IS, et al. Prediction of chronic obstructive pulmonary disease(COPD)in asthma patients using electronic medical records[J]. J Am Med Inform Assoc, 2009, 16(3): 371-379. |
[7] | Wildman MJ, Sanderson C, Groves J, et al. Predicting mortality for patients with exacerbations of COPD and Asthma in the COPD and Asthma Outcome Study(CAOS)[J]. QJM, 2009, 102(6): 389-399. |
[8] | Corren J. Asthma phenotypes and endotypes: an evolving paradigm for classification[J]. Discov Med, 2013, 15(83): 243-249. |
[9] | Matsui T. Sudden asthma death: etiology and prevention[J]. Nihon Rinsho, 2005, 63(7): 1214-1219. |
[10] | Gullach AJ, Risgaard B, Lynge TH, et al. Sudden death in young persons with uncontrolled asthma-a nationwide cohort study in Denmark[J]. BMC Pulm Med, 2015, 15:35. doi:10.1186/s12890-015-0033-z. |
[11] | Iribarren C, Tolstykh IV, Miller MK, et al. Adult asthma and risk of coronary heart disease, cerebrovascular disease, and heart failure: a prospective study of 2 matched cohorts[J]. Am J Epidemiol, 2012, 176(11): 1014-1024. |
[12] | Tattersall MC, Guo M, Korcarz CE, et al. Asthma predicts cardiovascular disease events: the multi-ethnic study of atherosclerosis[J]. Arterioscler Thromb Vasc Biol, 2015, 35(6): 1520-1525. |
[13] | Liu DW, Zhen XG, Liang Y, et al. Persistent asthma increases the risk of chronic kidney disease: a retrospective cohort study of 2354 patients with asthma[J]. Chin Med J(Engl), 2013, 126(21): 4093-4099. |
[14] | Huang HL, Ho SY, Li CH, et al. Bronchial asthma is associated with increased risk of chronic kidney disease[J]. BMC Pulm Med, 2014, 14: 80. doi: 10.1186/1471-2466-14-80. |
[15] | Taylor DR. Biomarkers of inflammation in asthma: a clinical perspective[J]. Semin Respir Crit Care Med, 2012, 33(6): 620-629. |
[16] | Bannier MA, van de Kant KD, Jobsis Q, et al. Biomarkers to predict asthma in wheezing preschool children[J]. Clin Exp Allergy, 2015, 45(6): 1040-1050. |
[17] | Zein JG, Dweik RA, Comhair SA, et al. Asthma is more severe in older adults[J]. PLoS One, 2015, 10(7): e0133490. doi: 10.1371/journal.pone.0133490. |
[18] | Tamimi A, Serdarevic D, Hanania NA. The effects of cigarette smoke on airway inflammation in asthma and COPD: therapeutic implications[J]. Respir Med, 2012, 106(3): 319-328. |
[19] | Liu T, Valdez R, Yoon PW, et al. The association between family history of asthma and the prevalence of asthma among US adults: National Health and Nutrition Examination Survey, 1999—2004[J]. Genet Med, 2009, 11(5): 323-328. |
[20] | Pescatore AM, Dogaru CM, Duembgen L, et al. A simple asthma prediction tool for preschool children with wheeze or cough[J]. J Allergy Clin Immunol, 2014, 133(1): 111-118. |
[21] | Klaassen EM, van de Kant KD, Jöbsis Q, et al. Exhaled biomarkers and gene expression at preschool age improve asthma prediction at 6 years of age[J]. Am J Respir Crit Care Med, 2015, 191(2): 201-207. |
[22] | Devulapalli CS, Carlsen KC, Håland G, et al. Severity of obstructive airways disease by age 2 years predicts asthma at 10 years of age[J]. Thorax, 2008, 63(1): 8-13. |
[23] | van der Mark LB, van Wonderen KE, Mohrs J, et al. Predicting asthma in preschool children at high risk presenting in primary care: development of a clinical asthma prediction score[J]. Prim Care Respir J, 2014, 23(1): 52-59. |
[24] | Luo G, Nkoy FL, Stone BL, et al. A systematic review of predictive models for asthma development in children[J]. BMC Med Inform Decis Mak, 2015, 15: 99. doi: 10.1186/s12911-015-0224-9. |
[25] | 中华医学会呼吸病学分会哮喘学组. 支气管哮喘防治指南(2016年版)[J]. 中华结核和呼吸杂志, 2016, 39(9): 1-24. |
[26] | Scichilone N, Rizzo M, Benfante A, et al. Serum low density lipoprotein subclasses in asthma[J]. Respir Med, 2013, 107(12): 1866-1872. |
[27] | Rasmussen F, Hancox RJ, Nair P, et al. Associations between airway hyperresponsiveness, obesity and lipoproteins in a longitudinal cohort[J]. Clin Respir J, 2013, 7(3): 268-275. |
[28] | Furuta GT, Atkins FD, Lee NA, et al. Changing roles of eosinophils in health and disease[J]. Ann Allergy Asthma Immunol, 2014, 113(1): 3-8. |
[29] | Brightling CE. Eosinophils, bronchitis and asthma: pathogenesis of cough and airflow obstruction[J]. Pulm Pharmacol Ther, 2011, 24(3): 324-327. |
[30] | Meijer RJ, Postma DS, Kauffman HF, et al. Accuracy of eosinophils and eosinophil cationic protein to predict steroid improvement in asthma[J]. Clin Exp Allergy, 2002, 32(7): 1096-1103. |
[31] | 张娟, 朱建波,赵铭山. 嗜酸性粒细胞在支气管哮喘发病中作用的研究进展[J]. 中外医疗, 2011, 30(8):179, 181. |
[32] | Khan DA. Allergic rhinitis and asthma: epidemiology and common pathophysiology[J]. Allergy Asthma Proc, 2014, 35(5): 357-361. |
[33] | Boulay ME, Morin A, Laprise C, et al. Asthma and rhinitis: what is the relationship?[J]. Curr Opin Allergy Clin Immunol, 2012, 12(5): 449-454. |
[34] | Nakagome K, Nagata M. Pathogenesis of airway inflammation in bronchial asthma[J]. Auris Nasus Larynx, 2011, 38(5): 555-563. |
[1] | 杨雪梅,李娟,王一凡,李培龙,王允山,杜鲁涛,王传新. 3-lncRNAs预后模型在HER2阳性乳腺癌预后评价中的意义[J]. 山东大学学报 (医学版), 2020, 58(5): 69-76. |
[2] | 杨丽萍,慕婷婷,杨玉娟,张宇,宋西成. 吸入性变应原对腺样体肥大合并支气管哮喘患儿肺功能影响[J]. 山东大学学报 (医学版), 2020, 58(3): 107-112. |
[3] | 李明卓,孙秀彬,王春霞,杨洋,刘新辉,刘言训,薛付忠,袁中尚. 血脂正常人群HDL-C纵向变化与冠心病的关联性分析:一项回顾性队列研究[J]. 山东大学学报 (医学版), 2019, 57(8): 110-116. |
[4] | 徐源佑,杨亚超,王春霞,马晓天,薛付忠,刘言训,王萍. 基于体检队列的胃炎风险预测模型[J]. 山东大学学报 (医学版), 2019, 57(6): 112-116. |
[5] | 周苗,卞伟玮,柳晓涓,康凤玲,薛付忠,刘静. 嗜碱性粒细胞百分比与慢性肾脏病关系的回顾性队列研究[J]. 山东大学学报 (医学版), 2018, 56(3): 85-90. |
[6] | 苏萍,杨亚超,杨洋,季加东,阿力木·达依木,李敏,薛付忠,刘言训. 健康管理人群2型糖尿病发病风险预测模型[J]. 山东大学学报(医学版), 2017, 55(6): 82-86. |
[7] | 李江冰,宋心红,林海燕,张冬芝,李向一,许艺博,王丽,薛付忠. 健康管理人群缺血性异常心电图的影响因素[J]. 山东大学学报(医学版), 2017, 55(6): 77-81. |
[8] | 张光,王广银,吴红彦, 张红玉,王停停,李吉庆,李敏,康凤玲,刘言训,薛付忠. 健康管理人群高脂血症风险预测模型[J]. 山东大学学报(医学版), 2017, 55(6): 72-76. |
[9] | 王春霞,许艺博,杨宁,夏冰,王萍,薛付忠. 基于健康管理队列的冠心病风险预测模型[J]. 山东大学学报(医学版), 2017, 55(6): 66-71. |
[10] | 李吉庆,赵焕宗,宋炳红,张理纯,李向一,陈亚飞,王萍,薛付忠. 基于健康管理队列的心血管事件风险预测模型[J]. 山东大学学报(医学版), 2017, 55(6): 56-60. |
[11] | 曹瑾,季晓康,孙秀彬,蒋正,薛付忠. γ-谷氨酰转肽酶与高尿酸血症关系的队列分析[J]. 山东大学学报(医学版), 2017, 55(6): 124-128. |
[12] | 孙苑潆,杨亚超,曲明苓,陈雁敏,李敏,王淑康,薛付忠,刘云霞. 健康管理人群代谢综合征发病风险预测模型[J]. 山东大学学报(医学版), 2017, 55(6): 87-92. |
[13] | 周苗,夏同耀,孙爱玲,李明,申振伟,卞伟玮,蒋正,康凤玲,柳晓涓,薛付忠,刘静. 健康管理人群慢性肾脏病风险预测模型[J]. 山东大学学报(医学版), 2017, 55(6): 98-103. |
[14] | 李敏,王春霞,夏冰,朱茜,孙苑潆,王淑康,薛付忠,贾红英. 健康管理人群脑卒中风险预测模型[J]. 山东大学学报(医学版), 2017, 55(6): 93-97. |
[15] | 于媛媛,王春霞,苏萍,孙苑潆,薛付忠,刘言训. 健康管理队列白内障发病风险预测模型[J]. 山东大学学报(医学版), 2017, 55(6): 104-107. |
|