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Analysis of influencing factors of postoperative complications of breast cancer based on two-level logistic random effects model |
Liu Mengyang, Tian Yuan, An Ning, Zhang Liyuan, Wei Li, Liu Meina. |
Department of Biostatistics, Harbin Medical University, Harbin 150081, China
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Abstract Objective To analyze the influencing factors of postoperative complications of breast cancer based on hospital level and patient level with the use of the twolevel logistic random effect model, so as to provide a basis for improving the quality of breast cancer treatment in the hospital and improving the prognosis of patients. Methods information questionnaire was formulated of breast cancer patients′ medical records, and the information of breast cancer patients′ cases was collected; univariate analysis was performed on the related factors of postoperative complications of breast cancer by t-test or chi-square test. The hospital as the two-level unit, the patient as the one-level unit, whether patients with postoperative complications as outcome variables, and the influence factors of complications as the explained variable, factors with statistical significance in univariate analysis included, two-level logistic random effect model was used for multivariate influencing factor analysis. Results Totally 3 224 patients were collected; the incidence of postoperative complications of breast cancer was 22.52%; the results of two-level Logistic random effect model showed that the hospital level random effect had statistical significance in the zero model (P<0.05). Among the explanatory variables at hospital level, hospital type (OR=0.130, 95%CI: 0.027-0.638) was statistically significant. Among the explanatory variables for patient level, age (OR=0.983, 95%CI: 0.972-0.994), residence (OR=0.671, 95%CI: 0.534-0.843), preoperative cytological examination (OR=1.973, 95%CI:1.397-2.787) and axillary lymph node metastasis (OR=1.435, 95%CI:1.168-1.762) were statistically significant (P<0.05). Conclusion The younger the age, and women living in the city are the high-risk group of complications after breast cancer; in the process of postoperative
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Received: 20 May 2021
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[1]陈莉莉,石菊芳,刘玉琴,等.基于人群的乳腺癌预后参数研究现状[J].中华乳腺病杂志(电子版),2018,12(6):370-372.
[2]施丽娜,费杨虹虹,司婷婷,等.保乳手术和根治性手术治疗乳腺癌的疗效及对患者神经降压素和神经降压素受体1的影响[J].中国妇幼保健,2021,36(9):2175-2178.
[3]BERGER E R, BILIMORIA K Y, KINNIER C V, et al. Assessment of hospital-level adjusted breast cancer sentinel lymph node positivity rates[J]. J Surg Oncol, 2019, 119(1):101-108.
[4]包晓蔷,刘美娜,王玉鹏.基于评价指标的乳腺癌治疗质量影响因素分析[J].中国医院统计,2020,27(5):397-402.
[5]钱莎莎,邢健男,王璐.多水平统计模型分析方法及其应用[J].中国公共卫生,2017,33(9):1414-1416.
[6]BARILI F, PAROLARI A, KAPPETEIN P A, et al. Statistical Primer: Heterogeneity, random or fixed-effects model analyses?[J]. Interact Cardiovasc Thorac Surg, 2018, 27(3):317-321.
[7]强福林, 张一心, 蔡晶, 等. 肿瘤专科医院的SWOT分析与思考[C]//中国医院管理学会肿瘤医院管理分会,卫生部全国肿瘤防治研究办公室,中国抗癌协会肿瘤医院管理专业委员会.第十九届全国肿瘤医院管理学术研讨会论文汇编.北京:中国医院管理学会肿瘤医院管理分会,2009.
[8]ESKELINEN M, SELANDER T, OLLONEN P, et al. Moderate/severe depression (MADRS) can affect the quality of life and outcome among patients admitted to breast cancer diagnosis unit[J]. Anticancer Res, 2017, 37(5):2641-2647.
[9]孙丽丽,黄磊,徐倩,等.乳腺癌术后化疗患者生命质量现状及影响因素的研究[J].现代预防医学,2016,43(21):4024-4028.
[10]CAHIR C, THOMAS A A, DOMBROWSKI S U, et al. Urban-rural variations in quality of life in breast cancer survivors prescribed endocrine therapy[J]. Int J Environ Res Public Health, 2017, 14(4):E394.
[11]HE N, XIE C M, WEI W D, et al. A new, preoperative, MRI-based scoring system for diagnosing malignant axillary lymph nodes in women evaluated for breast cancer[J]. Eur J Radiol, 2012, 81(10):2602-2612. |
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