摘要
目的探讨癌症患者照护评估量表(CES)对乳腺癌晚期患者生存时间预估的价值。方法采用便利抽样法,选取2018年11月—2020年6月在青岛大学附属青岛市中心医院治疗的140例晚期乳腺癌患者及其140名居家照护者为研究对象。研究人员与晚期乳腺癌患者的居家照护者进行联系并约定时间和地点,使用癌症患者CES对研究对象进行一对一调查。采用Pearson相关分析晚期乳腺癌患者的生存时间和CES得分的相关性。采用多重线性回归分析晚期乳腺癌患者CES得分的影响因素。共发放140份问卷,其中133份有效,有效回收率为95.00%(133/140)。结果133例晚期乳腺癌患者中Luminal A型76例、Luminal B型19例、ERBB^(2+)型12例、Basal-like型26例。Luminal A型晚期乳腺癌患者生存时间最长,与ERBB^(2+)型、Basal-like型晚期乳腺癌患者比较,差异均有统计学意义(P<0.05);Luminal B型晚期乳腺癌的生存时间与Luminal A型、ERBB^(2+)型、Basal-like型晚期乳腺癌患者比较,差异均无统计学意义(P>0.05)。Luminal A型晚期乳腺癌患者CES评分最高,与Luminal B型、ERBB^(2+)型、Basal-like型晚期乳腺癌患者比较,差异均有统计学意义(P<0.05);Luminal B型晚期乳腺癌的CES评分与Luminal A型、ERBB^(2+)型和Basal-like型晚期乳腺癌患者比较,差异均无统计学意义(P>0.05)。Pearson相关分析显示,晚期乳腺癌患者的生存时间和CES得分呈正相关(r=0.892,P<0.05)。晚期乳腺癌患者CES赋权水平影响因素包括由医生提供的身体照护、心理健康照护、环境、医生对家属的解释或说明、协作和持续性、对患者家属的考虑、可用性、费用、由医生对患者的解释或说明、由护士提供的身体照护。结论癌症患者CES可以有效预估晚期乳腺癌患者的生存时间,晚期乳腺癌患者的分子分型不同,生存时间的预估效果也不同。
Objective To explore the value of Care Evaluation Scale(CES)in cancer patients for predicting survival time in patients with advanced breast cancer.Methods From November 2018 to June 2020,the convenient sampling was used to select 140 patients with advanced breast cancer who were treated in Qingdao Central Hospital Affiliated to Qingdao University and 140 home caregivers as the research objects.Researchers contacted home caregivers of patients with advanced breast cancer to set up a time and place to conduct one-on-one surveys of research objects using the Cancer Patient CES.Pearson correlation was used to analyze the correlation between survival time and CES score in patients with advanced breast cancer.Multiple stepwise regression analysis was used to analyze the influencing factors of CES scores in patients with advanced breast cancer.A total of 140 questionnaires were distributed,of which 133 were valid,and the effective recovery rate was 95.00%(133/140).Results Among the 133 patients with advanced breast cancer,76 were Luminal A,19 were Luminal B,12 were ERBB^(2+)and 26 were Basal-like.Luminal type A advanced breast cancer patients had the longest survival time,and the differences were statistically significant compared with those of ERBB^(2+)and Basal-like advanced breast cancer patients(P<0.05).There was no statistically significant difference in survival time between Luminal B type advanced breast cancer and Luminal A,ERBB^(2+)and Basal-like advanced breast cancer patients(P>0.05).Luminal type A advanced breast cancer patients had the highest CES score,and the differences were statistically significant compared with those of Luminal type B,ERBB^(2+)and Basal-like advanced breast cancer patients(P<0.05).There was no statistically significant difference in the CES score between Luminal B advanced breast cancer and Luminal A,ERBB^(2+)and Basal-like advanced breast cancer(P>0.05).Pearson correlation analysis found that the survival time of patients with advanced breast cancer was positively correlated with the CES score(r=0.892,P<0.05).The influencing factors of CES empowerment in patients with advanced breast cancer included physical care provided by doctors,mental health care,environment,explanation or instructions by doctors to family members,collaboration and persistence,consideration for family members,availability,cost,explanation or instructions by doctors to patients and physical care provided by nurses.Conclusions CES in cancer patients can effectively predict the survival time of patients with advanced breast cancer.The molecular types of patients with advanced breast cancer are different and the effect of predicting survival time is also different.
作者
刘久美
宋艳杰
申琳
肖春萍
Liu Jiumei;Song Yanjie;Shen Lin;Xiao Chunping(The First and Third Departments of Breast Surgery,Qingdao Central Hospital Affiliated to Qingdao University,Qingdao 266042,China;The Second Department of Gynecology and Breast Surgery,Qingdao Central Hospital Affiliated to Qingdao University,Qingdao 266042,China)
出处
《中华现代护理杂志》
2022年第28期3924-3929,共6页
Chinese Journal of Modern Nursing
关键词
乳腺肿瘤
乳腺癌晚期
癌症患者照护评估量表
生存时间
预估
Breast neoplasms
Advanced breast cancer
Care Evaluation Scale in cancer patients
Survival time
Estimation