Article(id=1322165000442065121, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322164984558243894, articleNumber=null, orderNo=null, doi=10.12102/j.issn.1009-6493.2026.01.008, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1742745600000, receivedDateStr=2025-03-24, revisedDate=1763136000000, revisedDateStr=2025-11-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1793158300742, onlineDateStr=2026-10-28, pubDate=1767974400000, pubDateStr=2026-01-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793158300742, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793158300742, creator=13701087609, updateTime=1793158300742, updator=13701087609, issue=Issue{id=1322164984558243894, tenantId=1146029695717560320, journalId=1220038315760373764, year='2026', volume='40', issue='1', pageStart='1', pageEnd='176', issueExtLink='null', onlineDate='null', pubDate='1767974400000', pubDateStr='2026-01-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793158296955, creator='13701087609', updateTime=1793158296955, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=60, endPage=70, ext={EN=ArticleExt(id=1322165000676946146, articleId=1322165000442065121, tenantId=1146029695717560320, journalId=1220038315760373764, language=EN, title=Construction of a prediction model for the preoperative frailty risk of breast cancer patients based on interpretable machine learning algorithms, columnId=1220689484526572183, journalTitle=Chinese Nursing Research, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=
Objective To analyze the influencing factors of preoperative frailty in breast cancer patients and to develop a risk prediction model.
Methods A total of 583 inpatients scheduled for surgical treatment in the breast surgery departments of two Grade A tertiary hospitals in Binzhou city,Shandong province,were selected between August 2024 and January 2025.They were randomly divided into a training set(408 cases) and a validation set(175 cases) in a 7∶3 ratio.Variables were screened using both Lasso regression and the Boruta algorithm.Four machine learning algorithms-support vector machine,decision tree,light gradient boosting machine,and extreme gradient boosting-were employed to develop prediction models.Model performance was compared based on accuracy,precision,sensitivity,specificity,F1-score,and the area under the receiver operating characteristic(ROC) curve(AUC).And the optimal model was interpreted using the SHAP method.
Results The incidence of preoperative frailty in breast cancer patients was 26.93%.Compared to the support vector machine,decision tree,and light gradient boosting machine models,the extreme gradient boosting model demonstrated the best performance,with an AUC of 0.909,accuracy of 0.829,precision of 0.646,sensitivity of 0.857,specificity of 0.818, and an F1-score of 0.737.The SHAP bar plot identified the top five influencing factors as age,hemoglobin,albumin,neutrophil percentage,and comorbidities.
Conclusions The extreme gradient boosting model exhibits the best predictive performance and can serve as a reliable tool for healthcare providers to effectively assess and scientifically manage preoperative frailty in breast cancer patients.
, authors=Qing ZHANG
1, Ying ZHANG
2, Jianli DONG
3, Wenlong YU
2, Yinhuan XIONG
2, Jiayue ZHAO
1, Hongmei XU
1, authorsList=Qing ZHANG, Ying ZHANG, Jianli DONG, Wenlong YU, Yinhuan XIONG, Jiayue ZHAO, Hongmei XU, authorCompany=null, correspAuthors=Hongmei XU, authorNote=null, correspAuthorsNote=
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322165003919143164, articleId=1322165000442065121, tenantId=1146029695717560320, journalId=1220038315760373764, language=CN, title=基于可解释机器学习算法构建乳腺癌病人术前衰弱风险预测模型, columnId=1220689484681761433, journalTitle=护理研究, columnName=科研论著, runingTitle=null, highlight=null, articleAbstract=
目的 分析乳腺癌病人术前衰弱的影响因素并构建术前衰弱风险预测模型。
方法 选取2024年8月—2025年1月在山东省滨州市某2所三级甲等医院乳腺外科拟行手术治疗的住院病人583例,按照7∶3的比例随机分为训练集408例和验证集175例,基于LASSO回归和Boruta算法共同筛选变量,利用支持向量机、决策树、轻量梯度提升和极端梯度提升4种机器学习算法分别构建预测模型,采用准确度、精确度、敏感度、特异度、F1值和受试者工作特征(ROC)曲线下面积(AUC)比较各模型性能。基于Shaply加性解释(SHAP)算法对最优模型进行解释。
结果 乳腺癌病人术前衰弱的发生率为26.93%。与支持向量机、决策树、轻量梯度提升机模型比较,极端梯度提升模型性能最优,其AUC为0.909,准确度为0.829,精确度为0.646,敏感度为0.857,特异度为0.818,F1值为0.737。SHAP条形图显示,排名前5位的影响因素为年龄、血红蛋白、白蛋白、中性粒细胞百分比和合并症。
结论 极端梯度提升模型预测乳腺癌病人术前衰弱风险性能最佳,可为临床工作者有效评估和科学管理乳腺癌术前衰弱病人提供依据。
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1, 张英
2, 董建丽
3, 于文龙
2, 熊银环
2, 赵佳月
1, 许红梅
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3滨州医学院附属医院)])], figs=[ArticleFig(id=1322529735050121627, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 1, caption=
LASSO regression coefficient path, figureFileSmall=AeBnhhxIOQqon+2NrQ5Wlg==, figureFileBig=coIPe39DiszZmriHMzfbPQ==, tableContent=null), ArticleFig(id=1322529735125619100, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图1, caption=
LASSO回归系数路径, figureFileSmall=AeBnhhxIOQqon+2NrQ5Wlg==, figureFileBig=coIPe39DiszZmriHMzfbPQ==, tableContent=null), ArticleFig(id=1322529735247253917, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 2, caption=
LASSO regression cross-validation results, figureFileSmall=Q0K3RqDYnQdyldmk5eBJkw==, figureFileBig=5XA5ze+qxY0bLJZslh47Qg==, tableContent=null), ArticleFig(id=1322529735301779870, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图2, caption=
LASSO回归交叉验证结果, figureFileSmall=Q0K3RqDYnQdyldmk5eBJkw==, figureFileBig=5XA5ze+qxY0bLJZslh47Qg==, tableContent=null), ArticleFig(id=1322529735364694431, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 3, caption=
Boruta algorithm for variable selection, figureFileSmall=GvkabYLM9aWIPAwmkN+h4A==, figureFileBig=LC4YTsR+TePi7zg/vPdWGw==, tableContent=null), ArticleFig(id=1322529735461163424, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图3, caption=
Boruta算法筛选变量(绿色为Boruta算法确认的变量,红色为拒绝的变量)
, figureFileSmall=GvkabYLM9aWIPAwmkN+h4A==, figureFileBig=LC4YTsR+TePi7zg/vPdWGw==, tableContent=null), ArticleFig(id=1322529735536660897, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 4, caption=
Intersection of variables from the two algorithms, figureFileSmall=YDceoFHBsErJEys4966ayA==, figureFileBig=vjw6PiPrUZXI63fMuTUfUw==, tableContent=null), ArticleFig(id=1322529735599575458, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图4, caption=
两种算法取交集, figureFileSmall=YDceoFHBsErJEys4966ayA==, figureFileBig=vjw6PiPrUZXI63fMuTUfUw==, tableContent=null), ArticleFig(id=1322529735654101411, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 5, caption=
ROC curves of the models in the training set, figureFileSmall=NP7FwKjoXA+pqcyIxqKKQA==, figureFileBig=IMWQ6N/FqvsK5QSQ6bAJfg==, tableContent=null), ArticleFig(id=1322529735721210276, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图5, caption=
训练集ROC曲线, figureFileSmall=NP7FwKjoXA+pqcyIxqKKQA==, figureFileBig=IMWQ6N/FqvsK5QSQ6bAJfg==, tableContent=null), ArticleFig(id=1322529735800902053, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 6, caption=
ROC curves of the models in the validation set, figureFileSmall=CZCPSYHqmPRO4bCkza+AIA==, figureFileBig=oVwVfngDc5H2TVUey7fhdg==, tableContent=null), ArticleFig(id=1322529735863816614, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图6, caption=
验证集ROC曲线, figureFileSmall=CZCPSYHqmPRO4bCkza+AIA==, figureFileBig=oVwVfngDc5H2TVUey7fhdg==, tableContent=null), ArticleFig(id=1322529735943508391, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 7, caption=
SHAP bar plot, figureFileSmall=0o6FnML/H74ORKTLBlTWlw==, figureFileBig=dV2f8qy8qItg3G5ZjxhYCw==, tableContent=null), ArticleFig(id=1322529736031588776, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图7, caption=
SHAP条形图, figureFileSmall=0o6FnML/H74ORKTLBlTWlw==, figureFileBig=dV2f8qy8qItg3G5ZjxhYCw==, tableContent=null), ArticleFig(id=1322529736111280553, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 8, caption=
SHAP beeswarm plot, figureFileSmall=Cv2W3rSih9M+QDcJegc1dg==, figureFileBig=HgAz3c2lVqsXbO6KxcoIJA==, tableContent=null), ArticleFig(id=1322529736186778026, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图8, caption=
SHAP 蜂暖图, figureFileSmall=Cv2W3rSih9M+QDcJegc1dg==, figureFileBig=HgAz3c2lVqsXbO6KxcoIJA==, tableContent=null), ArticleFig(id=1322529736258081195, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 9, caption=
Single-instance explanation(high-risk frailty patient), figureFileSmall=9ilXFOnNp9ID21bgDPu0lQ==, figureFileBig=f+cu4N8ydsFzJhGOnKbiLQ==, tableContent=null), ArticleFig(id=1322529736333578668, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图9, caption=
单样本解释(衰弱高风险病人), figureFileSmall=9ilXFOnNp9ID21bgDPu0lQ==, figureFileBig=f+cu4N8ydsFzJhGOnKbiLQ==, tableContent=null), ArticleFig(id=1322529736396493229, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Figure 10, caption=
Single-instance explanation(low-risk frailty patient), figureFileSmall=Q+6qSkmPFZmsZlSA1ub4Sw==, figureFileBig=QNbvp14LpbLwYWvkPuvdWA==, tableContent=null), ArticleFig(id=1322529736459407790, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=图10, caption=
单样本解释(衰弱低风险病人), figureFileSmall=Q+6qSkmPFZmsZlSA1ub4Sw==, figureFileBig=QNbvp14LpbLwYWvkPuvdWA==, tableContent=null), ArticleFig(id=1322529736522322351, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Table 1, caption=
Univariate analysis of factors influencing preoperative frailty in breast cancer patients
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量 | 分类 | 非衰弱(n=426) | 衰弱(n=157) | 统计值 | P |
|---|
| 年龄[M(P25,P75),岁] | | 55.00(47.00,60.00) | 62.00(55.00,69.00) | Z=-8.001 | <0.001 |
| BMI[M(P25,P75),kg/m2] | | 24.59(22.89,26.00) | 24.67(22.78,25.89) | Z=-0.248 | 0.804 |
| 臂围[M(P25,P75),cm] | | 27.00(25.00,28.00) | 26.00(25.00,28.00) | Z=-2.526 | 0.012 |
| 小腿围[M(P25,P75),cm] | | 35.00(34.00,36.00) | 35.00(33.00,36.00) | Z=-0.515 | 0.607 |
| 臀围[M(P25,P75),cm] | | 100.00(95.25,103.00) | 97.00(93.00,102.00) | Z=-3.175 | <0.001 |
| 文化程度[例(%)] | 小学及以下 | 227(53.29) | 111(70.70) | χ2=17.094 | <0.001 |
| 初中 | 104(24.41) | 28(17.83) |
| 高中或中专 | 48(11.27) | 13(8.28) |
| 专科及以上 | 47(11.03) | 5(3.18) |
| 婚姻状况[例(%)] | 已婚 | 395(92.72) | 136(86.62) | χ2=5.253 | 0.022 |
| 非婚(未婚/离异/丧偶) | 31(7.28) | 21(13.38) |
| 个人月收入[例(%)] | <3 000元 | 237(55.63) | 110(70.06) | | |
| 3 000~6 000元 | 126(29.58) | 31(19.75) | χ2=9.921 | 0.007 |
| >6 000元 | 63(14.79) | 16(10.19) | | |
| 吸烟史[例(%)] | 否 | 404(94.84) | 140(89.17) | χ2=5.895 | 0.015 |
| 是 | 22(5.16) | 17(10.83) |
| 饮酒史[例(%)] | 否 | 394(92.49) | 147(93.63) | χ2=0.224 | 0.636 |
| 是 | 32(7.51) | 10(6.37) |
| 跌倒史[例(%)] | 否 | 392(92.02) | 130(82.80) | χ2=10.401 | <0.001 |
| 是 | 34(7.98) | 27(17.20) |
| 独居[例(%)] | 否 | 403(94.60) | 136(86.62) | χ2=10.461 | <0.001 |
| 是 | 23(5.40) | 21(13.38) |
| 睡眠[例(%)] | 正常 | 300(70.42) | 93(59.24) | χ2=0.011 | 0.535 |
| 困难 | 126(29.58) | 64(40.76) |
| 付费方式[例(%)] | 新型农村合作医疗 | 229(53.76) | 85(54.14) | | |
| 城镇居民医保 | 59(13.85) | 33(21.02) | χ2=5.896 | 0.052 |
| 离休/职工医保 | 138(32.39) | 39(24.84) | | |
| 锻炼情况[例(%)] | 无规律锻炼 | 255(59.86) | 109(69.43) | χ2=7.472 | 0.006 |
| 规律锻炼 | 171(40.14) | 48(30.57) |
| 合并症[例(%)] | ≤1种 | 192(45.07) | 39(24.84) | χ2=19.625 | <0.001 |
| ≥2种 | 234(54.93) | 118(75.16) |
| 多重用药[例(%)] | 否 | 384(90.14) | 119(75.80) | χ2=19.939 | <0.001 |
| 是 | 42(9.86) | 38(24.20) |
| 自理[例(%)] | 独立 | 407(95.54) | 112(71.34) | χ2=68.701 | <0.001 |
| 非独立 | 19(4.46) | 45(28.66) |
| 营养状况[例(%)] | 正常 | 353(82.86) | 102(64.97) | χ2=21.441 | <0.001 |
| 存在风险/营养不良 | 73(17.14) | 55(35.03) |
| 焦虑[例(%)] | 否 | 326(76.53) | 104(66.24) | χ2=6.268 | 0.012 |
| 是 | 100(23.47) | 53(33.76) |
| 抑郁[例(%)] | 否 | 335(78.64) | 109(69.43) | χ2=5.361 | 0.021 |
| 是 | 91(21.36) | 48(30.57) |
| 社会支持[M(P25,P75),分] | | 44.00(40.00,48.00) | 41.00(37.00,46.00) | Z=-5.219 | <0.001 |
| 病理分型[例(%)] | 非浸润性 | 83(19.48) | 24(15.29) | χ2=1.349 | 0.246 |
| 浸润性 | 343(80.52) | 133(84.71) |
| TNM分期[例(%)] | Ⅰ期 | 117(27.46) | 28(17.83) | | |
| Ⅱ期 | 249(58.45) | 88(56.05) | χ2=13.976 | <0.001 |
| Ⅲ期/Ⅳ期 | 60(14.08) | 41(26.11) | | |
| 术前化疗[例(%)] | 否 | 333(78.17) | 104(66.24) | χ2=8.694 | 0.003 |
| 是 | 93(21.83) | 53(33.76) |
| 血红蛋白[M(P25,P75),g/L] | | 129.00(120.00,136.00) | 116.00(108.50,127.00) | Z=-8.592 | <0.001 |
| 白细胞计数[M(P25,P75),×109/L] | | 4.70(4.20,5.40) | 4.70(4.24,5.21) | Z=-0.672 | 0.502 |
| 红细胞计数[M(P25,P75),×1012/L] | | 4.25(3.80,4.60) | 3.83(3.60,4.20) | Z=-6.055 | <0.001 |
| 中性粒细胞百分比[M(P25,P75),%] | | 56.98(53.08,62.32) | 61.10(56.90,66.26) | Z=-5.736 | <0.001 |
| 淋巴细胞绝对值[M(P25,P75),×109/L] | | 1.90(1.60,2.20) | 1.90(1.70,2.30) | Z=-1.405 | 0.160 |
| 白蛋白[M(P25,P75),g/L] | | 42.50(39.62,44.41) | 39.50(36.90,43.26) | Z=-6.155 | <0.001 |
| 总蛋白[M(P25,P75),g/L] | | 69.80(66.90,74.47) | 70.10(66.92,74.60) | Z=-0.057 | 0.955 |
| 低密度脂蛋白胆固醇[M(P25,P75),mmol/L] | | 2.58(2.34,2.96) | 2.63(1.98,2.96) | Z=-0.953 | 0.341 |
), ArticleFig(id=1322529736618791344, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=表1, caption=
乳腺癌病人术前衰弱影响因素的单因素分析
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量 | 分类 | 非衰弱(n=426) | 衰弱(n=157) | 统计值 | P |
|---|
| 年龄[M(P25,P75),岁] | | 55.00(47.00,60.00) | 62.00(55.00,69.00) | Z=-8.001 | <0.001 |
| BMI[M(P25,P75),kg/m2] | | 24.59(22.89,26.00) | 24.67(22.78,25.89) | Z=-0.248 | 0.804 |
| 臂围[M(P25,P75),cm] | | 27.00(25.00,28.00) | 26.00(25.00,28.00) | Z=-2.526 | 0.012 |
| 小腿围[M(P25,P75),cm] | | 35.00(34.00,36.00) | 35.00(33.00,36.00) | Z=-0.515 | 0.607 |
| 臀围[M(P25,P75),cm] | | 100.00(95.25,103.00) | 97.00(93.00,102.00) | Z=-3.175 | <0.001 |
| 文化程度[例(%)] | 小学及以下 | 227(53.29) | 111(70.70) | χ2=17.094 | <0.001 |
| 初中 | 104(24.41) | 28(17.83) |
| 高中或中专 | 48(11.27) | 13(8.28) |
| 专科及以上 | 47(11.03) | 5(3.18) |
| 婚姻状况[例(%)] | 已婚 | 395(92.72) | 136(86.62) | χ2=5.253 | 0.022 |
| 非婚(未婚/离异/丧偶) | 31(7.28) | 21(13.38) |
| 个人月收入[例(%)] | <3 000元 | 237(55.63) | 110(70.06) | | |
| 3 000~6 000元 | 126(29.58) | 31(19.75) | χ2=9.921 | 0.007 |
| >6 000元 | 63(14.79) | 16(10.19) | | |
| 吸烟史[例(%)] | 否 | 404(94.84) | 140(89.17) | χ2=5.895 | 0.015 |
| 是 | 22(5.16) | 17(10.83) |
| 饮酒史[例(%)] | 否 | 394(92.49) | 147(93.63) | χ2=0.224 | 0.636 |
| 是 | 32(7.51) | 10(6.37) |
| 跌倒史[例(%)] | 否 | 392(92.02) | 130(82.80) | χ2=10.401 | <0.001 |
| 是 | 34(7.98) | 27(17.20) |
| 独居[例(%)] | 否 | 403(94.60) | 136(86.62) | χ2=10.461 | <0.001 |
| 是 | 23(5.40) | 21(13.38) |
| 睡眠[例(%)] | 正常 | 300(70.42) | 93(59.24) | χ2=0.011 | 0.535 |
| 困难 | 126(29.58) | 64(40.76) |
| 付费方式[例(%)] | 新型农村合作医疗 | 229(53.76) | 85(54.14) | | |
| 城镇居民医保 | 59(13.85) | 33(21.02) | χ2=5.896 | 0.052 |
| 离休/职工医保 | 138(32.39) | 39(24.84) | | |
| 锻炼情况[例(%)] | 无规律锻炼 | 255(59.86) | 109(69.43) | χ2=7.472 | 0.006 |
| 规律锻炼 | 171(40.14) | 48(30.57) |
| 合并症[例(%)] | ≤1种 | 192(45.07) | 39(24.84) | χ2=19.625 | <0.001 |
| ≥2种 | 234(54.93) | 118(75.16) |
| 多重用药[例(%)] | 否 | 384(90.14) | 119(75.80) | χ2=19.939 | <0.001 |
| 是 | 42(9.86) | 38(24.20) |
| 自理[例(%)] | 独立 | 407(95.54) | 112(71.34) | χ2=68.701 | <0.001 |
| 非独立 | 19(4.46) | 45(28.66) |
| 营养状况[例(%)] | 正常 | 353(82.86) | 102(64.97) | χ2=21.441 | <0.001 |
| 存在风险/营养不良 | 73(17.14) | 55(35.03) |
| 焦虑[例(%)] | 否 | 326(76.53) | 104(66.24) | χ2=6.268 | 0.012 |
| 是 | 100(23.47) | 53(33.76) |
| 抑郁[例(%)] | 否 | 335(78.64) | 109(69.43) | χ2=5.361 | 0.021 |
| 是 | 91(21.36) | 48(30.57) |
| 社会支持[M(P25,P75),分] | | 44.00(40.00,48.00) | 41.00(37.00,46.00) | Z=-5.219 | <0.001 |
| 病理分型[例(%)] | 非浸润性 | 83(19.48) | 24(15.29) | χ2=1.349 | 0.246 |
| 浸润性 | 343(80.52) | 133(84.71) |
| TNM分期[例(%)] | Ⅰ期 | 117(27.46) | 28(17.83) | | |
| Ⅱ期 | 249(58.45) | 88(56.05) | χ2=13.976 | <0.001 |
| Ⅲ期/Ⅳ期 | 60(14.08) | 41(26.11) | | |
| 术前化疗[例(%)] | 否 | 333(78.17) | 104(66.24) | χ2=8.694 | 0.003 |
| 是 | 93(21.83) | 53(33.76) |
| 血红蛋白[M(P25,P75),g/L] | | 129.00(120.00,136.00) | 116.00(108.50,127.00) | Z=-8.592 | <0.001 |
| 白细胞计数[M(P25,P75),×109/L] | | 4.70(4.20,5.40) | 4.70(4.24,5.21) | Z=-0.672 | 0.502 |
| 红细胞计数[M(P25,P75),×1012/L] | | 4.25(3.80,4.60) | 3.83(3.60,4.20) | Z=-6.055 | <0.001 |
| 中性粒细胞百分比[M(P25,P75),%] | | 56.98(53.08,62.32) | 61.10(56.90,66.26) | Z=-5.736 | <0.001 |
| 淋巴细胞绝对值[M(P25,P75),×109/L] | | 1.90(1.60,2.20) | 1.90(1.70,2.30) | Z=-1.405 | 0.160 |
| 白蛋白[M(P25,P75),g/L] | | 42.50(39.62,44.41) | 39.50(36.90,43.26) | Z=-6.155 | <0.001 |
| 总蛋白[M(P25,P75),g/L] | | 69.80(66.90,74.47) | 70.10(66.92,74.60) | Z=-0.057 | 0.955 |
| 低密度脂蛋白胆固醇[M(P25,P75),mmol/L] | | 2.58(2.34,2.96) | 2.63(1.98,2.96) | Z=-0.953 | 0.341 |
), ArticleFig(id=1322529736690094513, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Table 2, caption=
Comparison of baseline characteristics between the training set and the validation set
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量 | 分类 | 训练集(n=408) | 验证集(n=175) | 统计值 | P |
|---|
| 衰弱情况[例(%)] | 非衰弱 | 300(73.53) | 126(72.00) | χ2=0.146 | 0.703 |
| 衰弱 | 108(26.47) | 49(28.00) |
| 年龄[M(P25,P75),岁] | | 56.50(49.00,63.00) | 56.00(48.00,62.00) | Z=-0.961 | 0.337 |
| BMI[M(P25,P75),kg/m2] | | 24.63(22.84,25.89) | 24.67(22.87,26.37) | Z=-0.912 | 0.362 |
| 臂围[M(P25,P75),cm] | | 27.00(25.00,28.00) | 27.00(25.00,28.00) | Z=-0.152 | 0.879 |
| 小腿围[M(P25,P75),cm] | | 35.00(34.00,36.00) | 35.00(33.00,36.00) | Z=-1.044 | 0.297 |
| 臀围[M(P25,P75),cm] | | 99.00(95.00,103.00) | 99.00(94.00,103.00) | Z=-0.084 | 0.933 |
| 文化程度[例(%)] | 小学及以下 | 239(58.58) | 99(56.57) | χ2=5.246 | 0.155 |
| 初中 | 99(24.26) | 33(18.86) |
| 高中或中专 | 37(9.07) | 24(13.71) |
| 专科及以上 | 33(8.09) | 19(10.86) |
| 婚姻状况[例(%)] | 已婚 | 369(90.44) | 162(92.57) | χ2=0.684 | 0.408 |
| 非婚(未婚/离异/丧偶) | 39(9.56) | 13(7.43) |
| 个人月收入[例(%)] | <3 000元 | 243(59.56) | 104(59.43) | | |
| 3 000~6 000元 | 110(26.96) | 47(26.86) | χ2=0.006 | 0.997 |
| >6 000元 | 55(13.48) | 24(13.71) | | |
| 吸烟史[例(%)] | 否 | 376(92.16) | 168(96.00) | χ2=2.898 | 0.089 |
| 是 | 32(7.84) | 7(4.00) |
| 饮酒史[例(%)] | 否 | 378(92.65) | 163(93.14) | χ2=0.045 | 0.832 |
| 是 | 30(7.35) | 12(6.86) |
| 跌倒史[例(%)] | 否 | 364(89.22) | 158(90.29) | χ2=0.150 | 0.699 |
| 是 | 44(10.78) | 17(9.71) |
| 独居[例(%)] | 否 | 378(92.65) | 161(92.00) | χ2=0.073 | 0.786 |
| 是 | 30(7.35) | 14(8.00) |
| 睡眠[例(%)] | 正常 | 269(65.93) | 124(70.86) | χ2=1.353 | 0.245 |
| 困难 | 139(34.07) | 51(29.14) |
| 付费方式[例(%)] | 新型农村合作医疗 | 219(53.68) | 95(54.29) | | |
| 城镇居民医保 | 70(17.16) | 22(12.57) | χ2=2.278 | 0.320 |
| 离休/职工医保 | 119(29.17) | 58(33.14) | | |
| 锻炼情况[例(%)] | 无规律锻炼 | 260(63.73) | 104(59.43) | χ2=0.964 | 0.326 |
| 规律锻炼 | 148(36.27) | 71(40.57) |
| 合并症[例(%)] | ≤1种 | 159(38.97) | 72(41.14) | χ2=0.243 | 0.623 |
| ≥2种 | 249(61.03) | 103(58.86) |
| 多重用药[例(%)] | 否 | 353(86.52) | 150(85.71) | χ2=0.067 | 0.796 |
| 是 | 55(13.48) | 25(14.29) |
| 自理[例(%)] | 独立 | 360(88.24) | 159(90.86) | χ2=0.861 | 0.353 |
| 非独立 | 48(11.76) | 16(9.14) |
| 营养状况[例(%)] | 正常 | 315(77.21) | 140(80.00) | χ2=0.558 | 0.455 |
| 存在风险/营养不良 | 93(22.79) | 35(20.00) |
| 焦虑[例(%)] | 否 | 307(75.25) | 123(70.29) | χ2=1.556 | 0.212 |
| 是 | 101(24.75) | 52(29.71) |
| 抑郁[例(%)] | 否 | 309(75.74) | 135(77.14) | χ2=0.134 | 0.715 |
| 是 | 99(24.26) | 40(22.86) | | |
| 社会支持[M(P25,P75),分] | | 44.00(39.00,47.00) | 44.00(39.00,48.00) | Z=-0.375 | 0.708 |
| 病理分型[例(%)] | 非浸润性 | 74(18.14) | 33(18.86) | χ2=0.042 | 0.837 |
| 浸润性 | 334(81.86) | 142(81.14) |
| TNM分期[例(%)] | Ⅰ期 | 105(25.74) | 40(22.86) | | |
| Ⅱ期 | 231(56.62) | 106(60.57) | χ2=0.821 | 0.663 |
| Ⅲ期/Ⅳ期 | 72(17.65) | 29(16.57) | | |
| 术前化疗[例(%)] | 否 | 302(74.02) | 135(77.14) | χ2=0.636 | 0.425 |
| 是 | 106(25.98) | 40(22.86) |
| 血红蛋白[M(P25,P75),g/L] | | 127.00(116.00,133.75) | 125.00(115.50,134.00) | Z=-0.426 | 0.670 |
| 白细胞计数[M(P25,P75),×109/L] | | 4.70(4.20,5.36) | 4.70(4.30,5.30) | Z=-0.383 | 0.701 |
| 红细胞计数[M(P25,P75),×1012/L] | | 4.20(3.70,4.60) | 4.20(3.70,4.50) | Z=-0.392 | 0.695 |
| 中性粒细胞百分比[M(P25,P75),%] | | 57.83(53.90,63.60) | 58.63(55.23,64.10) | Z=-0.590 | 0.555 |
| 淋巴细胞绝对值[M(P25,P75),×109/L] | | 1.90(1.60,2.20) | 1.90(1.60,2.20) | Z=-0.230 | 0.818 |
| 白蛋白[M(P25,P75),g/L] | | 42.10(38.96,44.02) | 42.26(39.40,44.50) | Z=-1.118 | 0.264 |
| 总蛋白[M(P25,P75),g/L] | | 69.87(66.80,74.40) | 69.60(67.40,74.60) | Z=-0.440 | 0.660 |
| 低密度脂蛋白胆固醇[M(P25,P75),mmol/L] | | 2.58(2.15,2.98) | 2.63(2.34,2.96) | Z=-0.385 | 0.700 |
), ArticleFig(id=1322529736761397682, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=表2, caption=
训练集与验证集基线资料比较
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量 | 分类 | 训练集(n=408) | 验证集(n=175) | 统计值 | P |
|---|
| 衰弱情况[例(%)] | 非衰弱 | 300(73.53) | 126(72.00) | χ2=0.146 | 0.703 |
| 衰弱 | 108(26.47) | 49(28.00) |
| 年龄[M(P25,P75),岁] | | 56.50(49.00,63.00) | 56.00(48.00,62.00) | Z=-0.961 | 0.337 |
| BMI[M(P25,P75),kg/m2] | | 24.63(22.84,25.89) | 24.67(22.87,26.37) | Z=-0.912 | 0.362 |
| 臂围[M(P25,P75),cm] | | 27.00(25.00,28.00) | 27.00(25.00,28.00) | Z=-0.152 | 0.879 |
| 小腿围[M(P25,P75),cm] | | 35.00(34.00,36.00) | 35.00(33.00,36.00) | Z=-1.044 | 0.297 |
| 臀围[M(P25,P75),cm] | | 99.00(95.00,103.00) | 99.00(94.00,103.00) | Z=-0.084 | 0.933 |
| 文化程度[例(%)] | 小学及以下 | 239(58.58) | 99(56.57) | χ2=5.246 | 0.155 |
| 初中 | 99(24.26) | 33(18.86) |
| 高中或中专 | 37(9.07) | 24(13.71) |
| 专科及以上 | 33(8.09) | 19(10.86) |
| 婚姻状况[例(%)] | 已婚 | 369(90.44) | 162(92.57) | χ2=0.684 | 0.408 |
| 非婚(未婚/离异/丧偶) | 39(9.56) | 13(7.43) |
| 个人月收入[例(%)] | <3 000元 | 243(59.56) | 104(59.43) | | |
| 3 000~6 000元 | 110(26.96) | 47(26.86) | χ2=0.006 | 0.997 |
| >6 000元 | 55(13.48) | 24(13.71) | | |
| 吸烟史[例(%)] | 否 | 376(92.16) | 168(96.00) | χ2=2.898 | 0.089 |
| 是 | 32(7.84) | 7(4.00) |
| 饮酒史[例(%)] | 否 | 378(92.65) | 163(93.14) | χ2=0.045 | 0.832 |
| 是 | 30(7.35) | 12(6.86) |
| 跌倒史[例(%)] | 否 | 364(89.22) | 158(90.29) | χ2=0.150 | 0.699 |
| 是 | 44(10.78) | 17(9.71) |
| 独居[例(%)] | 否 | 378(92.65) | 161(92.00) | χ2=0.073 | 0.786 |
| 是 | 30(7.35) | 14(8.00) |
| 睡眠[例(%)] | 正常 | 269(65.93) | 124(70.86) | χ2=1.353 | 0.245 |
| 困难 | 139(34.07) | 51(29.14) |
| 付费方式[例(%)] | 新型农村合作医疗 | 219(53.68) | 95(54.29) | | |
| 城镇居民医保 | 70(17.16) | 22(12.57) | χ2=2.278 | 0.320 |
| 离休/职工医保 | 119(29.17) | 58(33.14) | | |
| 锻炼情况[例(%)] | 无规律锻炼 | 260(63.73) | 104(59.43) | χ2=0.964 | 0.326 |
| 规律锻炼 | 148(36.27) | 71(40.57) |
| 合并症[例(%)] | ≤1种 | 159(38.97) | 72(41.14) | χ2=0.243 | 0.623 |
| ≥2种 | 249(61.03) | 103(58.86) |
| 多重用药[例(%)] | 否 | 353(86.52) | 150(85.71) | χ2=0.067 | 0.796 |
| 是 | 55(13.48) | 25(14.29) |
| 自理[例(%)] | 独立 | 360(88.24) | 159(90.86) | χ2=0.861 | 0.353 |
| 非独立 | 48(11.76) | 16(9.14) |
| 营养状况[例(%)] | 正常 | 315(77.21) | 140(80.00) | χ2=0.558 | 0.455 |
| 存在风险/营养不良 | 93(22.79) | 35(20.00) |
| 焦虑[例(%)] | 否 | 307(75.25) | 123(70.29) | χ2=1.556 | 0.212 |
| 是 | 101(24.75) | 52(29.71) |
| 抑郁[例(%)] | 否 | 309(75.74) | 135(77.14) | χ2=0.134 | 0.715 |
| 是 | 99(24.26) | 40(22.86) | | |
| 社会支持[M(P25,P75),分] | | 44.00(39.00,47.00) | 44.00(39.00,48.00) | Z=-0.375 | 0.708 |
| 病理分型[例(%)] | 非浸润性 | 74(18.14) | 33(18.86) | χ2=0.042 | 0.837 |
| 浸润性 | 334(81.86) | 142(81.14) |
| TNM分期[例(%)] | Ⅰ期 | 105(25.74) | 40(22.86) | | |
| Ⅱ期 | 231(56.62) | 106(60.57) | χ2=0.821 | 0.663 |
| Ⅲ期/Ⅳ期 | 72(17.65) | 29(16.57) | | |
| 术前化疗[例(%)] | 否 | 302(74.02) | 135(77.14) | χ2=0.636 | 0.425 |
| 是 | 106(25.98) | 40(22.86) |
| 血红蛋白[M(P25,P75),g/L] | | 127.00(116.00,133.75) | 125.00(115.50,134.00) | Z=-0.426 | 0.670 |
| 白细胞计数[M(P25,P75),×109/L] | | 4.70(4.20,5.36) | 4.70(4.30,5.30) | Z=-0.383 | 0.701 |
| 红细胞计数[M(P25,P75),×1012/L] | | 4.20(3.70,4.60) | 4.20(3.70,4.50) | Z=-0.392 | 0.695 |
| 中性粒细胞百分比[M(P25,P75),%] | | 57.83(53.90,63.60) | 58.63(55.23,64.10) | Z=-0.590 | 0.555 |
| 淋巴细胞绝对值[M(P25,P75),×109/L] | | 1.90(1.60,2.20) | 1.90(1.60,2.20) | Z=-0.230 | 0.818 |
| 白蛋白[M(P25,P75),g/L] | | 42.10(38.96,44.02) | 42.26(39.40,44.50) | Z=-1.118 | 0.264 |
| 总蛋白[M(P25,P75),g/L] | | 69.87(66.80,74.40) | 69.60(67.40,74.60) | Z=-0.440 | 0.660 |
| 低密度脂蛋白胆固醇[M(P25,P75),mmol/L] | | 2.58(2.15,2.98) | 2.63(2.34,2.96) | Z=-0.385 | 0.700 |
), ArticleFig(id=1322529736874643891, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=EN, label=Table 3, caption=
Performance evaluation of the four machine learning models in the training set and validation set
, figureFileSmall=null, figureFileBig=null, tableContent=
| 项目 | 模型 | 准确度 | 精确度 | 敏感度 | 特异度 | F1值 | AUC |
|---|
| 训练集 | 支持向量机 | 0.860 | 0.722 | 0.769 | 0.893 | 0.744 | 0.895 |
| 决策树 | 0.897 | 0.694 | 0.893 | 0.898 | 0.781 | 0.924 |
| 轻量梯度提升机 | 0.838 | 0.672 | 0.759 | 0.867 | 0.713 | 0.883 |
| 极端梯度提升机 | 0.878 | 0.704 | 0.926 | 0.860 | 0.800 | 0.954 |
| 验证集 | 支持向量机 | 0.834 | 0.717 | 0.674 | 0.897 | 0.695 | 0.878 |
| 决策树 | 0.829 | 0.490 | 0.828 | 0.829 | 0.615 | 0.841 |
| 轻量梯度提升机 | 0.840 | 0.714 | 0.714 | 0.889 | 0.714 | 0.886 |
| 极端梯度提升机 | 0.829 | 0.646 | 0.857 | 0.818 | 0.737 | 0.909 |
), ArticleFig(id=1322529738552365492, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322165000442065121, language=CN, label=表3, caption=
4种机器学习模型在训练集和验证集的性能评价
, figureFileSmall=null, figureFileBig=null, tableContent=
| 项目 | 模型 | 准确度 | 精确度 | 敏感度 | 特异度 | F1值 | AUC |
|---|
| 训练集 | 支持向量机 | 0.860 | 0.722 | 0.769 | 0.893 | 0.744 | 0.895 |
| 决策树 | 0.897 | 0.694 | 0.893 | 0.898 | 0.781 | 0.924 |
| 轻量梯度提升机 | 0.838 | 0.672 | 0.759 | 0.867 | 0.713 | 0.883 |
| 极端梯度提升机 | 0.878 | 0.704 | 0.926 | 0.860 | 0.800 | 0.954 |
| 验证集 | 支持向量机 | 0.834 | 0.717 | 0.674 | 0.897 | 0.695 | 0.878 |
| 决策树 | 0.829 | 0.490 | 0.828 | 0.829 | 0.615 | 0.841 |
| 轻量梯度提升机 | 0.840 | 0.714 | 0.714 | 0.889 | 0.714 | 0.886 |
| 极端梯度提升机 | 0.829 | 0.646 | 0.857 | 0.818 | 0.737 | 0.909 |
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