中西医结合治疗晚期非小细胞肺癌队列疗效预测模型的建立 : = ESTABLISHMENT OF A PREDICTIVE MODEL FOR THE CLINICAL EFFECT OF INTEGRATED TRADITIONAL CHINESE AND WESTERN MEDICINE THERAPY IN TREATMENT OF ADVANCED NON-SMALL CELL LUNG CANCER
目的用回顾性队列的数据建立疗效预测模型,为中西医结合治疗非小细胞肺癌(NSCLC)提供疗效预测工具。方法采用回顾性队列研究设计,收集并分析2016年6月1日—2018年9月30日在我院肿瘤中心住院治疗的714例ⅢB～ⅣB期NSCLC病人的资料。将病人的数据录入统计软件,采用单因素分析及多元回归分析筛选变量,建立疗效预测模型。结果多元回归分析显示,在调整了化疗、靶向治疗、放疗等因素后,接受中医药治疗依然能够降低26%的死亡风险,差异具有统计学意义(HR=0.74,95%CI=0.57～0.95,P<0.05)。列线图模型可以预测17.27个月的生存期,受试者工作特征曲线(ROC曲线)的曲线下面积(AUC)为0.65,预测的效能尚可。结论中医药治疗是NSCLC的保护因素。用回顾性队列研究的数据建立中西医结合治疗NSCLC早期预测模型是可行的。.
Objective To establish a predictive model for clinical effect based on retrospective cohort data, and to provide a predictive tool for the clinical effect of integrated traditional Chinese and Western medicine therapy in the treatment of non-small cell lung cancer(NSCLC). Methods A retrospective cohort study was designed to collect and analyze the data from 714 patients with stage ⅢB-ⅣB NSCLC who were hospitalized in Tumor Cancer in our hospital from June 1, 2016 to September 30, 2018. The patients' data were entered into a statistical software, and univariate analysis and multivariate regression analysis were used to screen out variables and establish a predictive model. Results The multivariate regression analysis showed that after adjustment for the factors such as chemotherapy, targeted therapy, and radiotherapy, traditional Chinese medicine treatment still reduced the risk of death by 26%(hazard ratio=0.74,95% confidence interval=0.57-0.95,P<0.05). The nomogram predicted a survival time of 17.27 months and had an area under the receiver operating characteristic curve of 0.65, which suggested fairly good predictive performance. Conclusion Traditional Chinese medicine treatment is a protective factor for NSCLC, and it is feasible to use the data of retrospective cohort study to establish an early predictive model for NSCLC treated by integrated traditional Chinese and Western medicine therapy..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019-11-20 17:12 2019 |
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| Erschienen: |
2019-11-20 17:12 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2019 |
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| Enthalten in: |
Qing dao da xue yi xue yuan xue bao - (2019), 06 vom: 20 17:12. Nov., Seite 661-666 Original Letters: Enthalten in 青岛大学医学院学报 (DE-600)2992861-8 (DE-600)2992861-8 山东省青岛市 |
| Reihe: |
China Academic Journals (CAJ), E, 医药卫生科技 = Medicine & Public Health |
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| Sprache: |
Chinesisch |
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| Weiterer Titel: |
ESTABLISHMENT OF A PREDICTIVE MODEL FOR THE CLINICAL EFFECT OF INTEGRATED TRADITIONAL CHINESE AND WESTERN MEDICINE THERAPY IN TREATMENT OF ADVANCED NON-SMALL CELL LUNG CANCER |
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| Beteiligte Personen: |
付源峰 [VerfasserIn] |
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| Links: |
oversea.cnki.net [lizenzpflichtig] |
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| Anmerkungen: |
Author info:FU Yuanfeng;LIN Jietao;HUANG Zijing;LUO Jiamin;HU Leihao;LIN Lizhu;the First Clinical Medical College of Guangzhou University of Traditional Chinese Medicine |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
CAJ644201649 |
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| 245 | 1 | 0 | |a 中西医结合治疗晚期非小细胞肺癌队列疗效预测模型的建立 |b = ESTABLISHMENT OF A PREDICTIVE MODEL FOR THE CLINICAL EFFECT OF INTEGRATED TRADITIONAL CHINESE AND WESTERN MEDICINE THERAPY IN TREATMENT OF ADVANCED NON-SMALL CELL LUNG CANCER |
| 246 | 3 | 1 | |a ESTABLISHMENT OF A PREDICTIVE MODEL FOR THE CLINICAL EFFECT OF INTEGRATED TRADITIONAL CHINESE AND WESTERN MEDICINE THERAPY IN TREATMENT OF ADVANCED NON-SMALL CELL LUNG CANCER |
| 264 | 1 | |c 2019-11-20 17:12 | |
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| 500 | |a Author info:FU Yuanfeng;LIN Jietao;HUANG Zijing;LUO Jiamin;HU Leihao;LIN Lizhu;the First Clinical Medical College of Guangzhou University of Traditional Chinese Medicine | ||
| 520 | |a 目的用回顾性队列的数据建立疗效预测模型,为中西医结合治疗非小细胞肺癌(NSCLC)提供疗效预测工具。方法采用回顾性队列研究设计,收集并分析2016年6月1日—2018年9月30日在我院肿瘤中心住院治疗的714例ⅢB～ⅣB期NSCLC病人的资料。将病人的数据录入统计软件,采用单因素分析及多元回归分析筛选变量,建立疗效预测模型。结果多元回归分析显示,在调整了化疗、靶向治疗、放疗等因素后,接受中医药治疗依然能够降低26%的死亡风险,差异具有统计学意义(HR=0.74,95%CI=0.57～0.95,P<0.05)。列线图模型可以预测17.27个月的生存期,受试者工作特征曲线(ROC曲线)的曲线下面积(AUC)为0.65,预测的效能尚可。结论中医药治疗是NSCLC的保护因素。用回顾性队列研究的数据建立中西医结合治疗NSCLC早期预测模型是可行的。 | ||
| 520 | |a Objective To establish a predictive model for clinical effect based on retrospective cohort data, and to provide a predictive tool for the clinical effect of integrated traditional Chinese and Western medicine therapy in the treatment of non-small cell lung cancer(NSCLC). Methods A retrospective cohort study was designed to collect and analyze the data from 714 patients with stage ⅢB-ⅣB NSCLC who were hospitalized in Tumor Cancer in our hospital from June 1, 2016 to September 30, 2018. The patients' data were entered into a statistical software, and univariate analysis and multivariate regression analysis were used to screen out variables and establish a predictive model. Results The multivariate regression analysis showed that after adjustment for the factors such as chemotherapy, targeted therapy, and radiotherapy, traditional Chinese medicine treatment still reduced the risk of death by 26%(hazard ratio=0.74,95% confidence interval=0.57-0.95,P<0.05). The nomogram predicted a survival time of 17.27 months and had an area under the receiver operating characteristic curve of 0.65, which suggested fairly good predictive performance. Conclusion Traditional Chinese medicine treatment is a protective factor for NSCLC, and it is feasible to use the data of retrospective cohort study to establish an early predictive model for NSCLC treated by integrated traditional Chinese and Western medicine therapy. | ||
| 610 | 2 | 4 | |a 广州中医药大学第一临床医学院 |
| 610 | 2 | 4 | |a 广州中医药大学第一附属医院肿瘤中心 |
| 650 | 4 | |a 呼吸系肿瘤 | |
| 650 | 4 | |a 肿瘤学 | |
| 650 | 4 | |a 医药、卫生 | |
| 650 | 4 | |a Combination of Traditional Chinese Medicine With Western Medicine | |
| 650 | 4 | |a Oncology | |
| 650 | 4 | |a 医药卫生科技 | |
| 650 | 4 | |a Medicine & Public Health | |
| 650 | 4 | |a 癌,非小细胞肺 | |
| 650 | 4 | |a 中草药 | |
| 650 | 4 | |a 药物疗法,联合 | |
| 650 | 4 | |a 队列研究 | |
| 650 | 4 | |a 模型,统计学 | |
| 650 | 4 | |a 列线图 | |
| 650 | 4 | |a carcinoma,non-small-cell lung | |
| 650 | 4 | |a drugs,chinese herbal | |
| 650 | 4 | |a drug therapy,combination | |
| 650 | 4 | |a cohort studies | |
| 650 | 4 | |a models,statistical | |
| 650 | 4 | |a nomograms | |
| 700 | 0 | |a 林洁涛 |4 oth | |
| 700 | 0 | |a 黄子菁 |4 oth | |
| 700 | 0 | |a 罗嘉敏 |4 oth | |
| 700 | 0 | |a 胡磊颢 |4 oth | |
| 700 | 0 | |a 林丽珠 |4 oth | |
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