Article(id=1292135484948504718, tenantId=1146029695717560320, journalId=1246415772164075586, issueId=1292135444850955150, articleNumber=null, orderNo=null, doi=10.13699/j.cnki.1001-6821.2026.09.011, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1769702400000, receivedDateStr=2026-01-30, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1785998706327, onlineDateStr=2026-08-06, pubDate=1778947200000, pubDateStr=2026-05-17, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1785998706327, onlineIssueDateStr=2026-08-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1785998706327, creator=13701087609, updateTime=1785998706327, updator=13701087609, issue=Issue{id=1292135444850955150, tenantId=1146029695717560320, journalId=1246415772164075586, year='2026', volume='42', issue='9', pageStart='1201', pageEnd='1350', issueExtLink='null', onlineDate='null', pubDate='1778947200000', pubDateStr='2026-05-17', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1785998696767, creator='13701087609', updateTime=1786014392260, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1292201276780081469, tenantId=1146029695717560320, journalId=1246415772164075586, issueId=1292135444850955150, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1292201276784275774, tenantId=1146029695717560320, journalId=1246415772164075586, issueId=1292135444850955150, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1264, endPage=1270, ext={EN=ArticleExt(id=1292135485145637007, articleId=1292135484948504718, tenantId=1146029695717560320, journalId=1246415772164075586, language=EN, title=Clinical trial of PD-1 inhibitor-induced liver injury in tumor patients, columnId=1246531407326105792, journalTitle=Chinese Journal of Clinical Pharmacology, columnName=Clinical and Basic Bridging Research, runingTitle=null, highlight=null, articleAbstract=
Objective

To observe clinical features of programmed cell death protein-1 (PD-1) inhibitor-induced liver injury in tumor patients and analyze its influencing factors.

Methods

Tumor patients treated with PD-1 inhibitors were enrolled. The clinical data were analyzed. The occurrence of liver injury during treatment was assessed according to CTCAE V5.0 criteria. Clinicopathological features of patients with liver injury were summarized. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for liver injury in tumor patients, and a nomogram prediction model was constructed receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were employed to evaluate validity of the model.

Results

The incidence of PD-1 inhibitor-induced liver injury among the 310 patients enrolled was 11.94% (37 cases/310 cases). Grade 1, grade 2, grade 3 and grade 4 liver injuries were observed in 12 cases (32.43%), 15 cases (40.54%), 8 cases (21.62%) and 2 cases (5.41%), respectively. Clinical types included cholestatic type in 23 cases (62.16%), abnormal liver biochemistry type in 12 cases (32.43%), and hepatocellular injury type in 2 cases (5.41%). The median time to the occurrence of liver injury was 28.50 (5.00-217.00) d. After drug withdrawal or symptomatic treatment, liver function recovered, and the mean recovery time was (21.45±6.94) d. Multivariate logistic regression analysis found female gender [odds rotio (OR)=2.36, 95% confidence interval (CI)=1.11-4.99], history of comorbid liver disease (OR=2.62, 95%CI=1.10-6.24), and liver metastasis (OR=3.10, 95%CI=1.28-7.49) as independent risk factors influencing the occurrence of liver injury in tumor patients (all P<0.05). ROC analysis showed that the area under curve (AUC) (95%CI) of the nomogram prediction model for predicting liver injury was 0.86 (0.82-0.90), with sensitivity of 78.38% and specificity of 83.52%. Hosmer-Lemeshow test showed good goodness-of-fit (χ2=12.58, P>0.05). Validation with Bootstrap revealed good agreement between the calibration curve and the actual curve (Brier score=0.09). DCA demonstrated that the nomogram prediction model provided clinical benefit when the threshold was between 0.05 and 0.99.

Conclusion

PD-1 inhibitor-induced liver injury is relatively common in tumor patients. Female gender, history of liver disease and liver metastasis are associated with its occurrence. The nomogram prediction model constructed based on these factors exhibits good predictive performance and can provide reference for early identification of high-risk patients.

, authors=Wen-jie LU, Xing GAO, Ling ZHANG, authorsList=Wen-jie LU, Xing GAO, Ling ZHANG, authorCompany=null, correspAuthors=Ling ZHANG, authorNote=null, correspAuthorsNote=null, 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=1292135485435043984, articleId=1292135484948504718, tenantId=1146029695717560320, journalId=1246415772164075586, language=CN, title=PD-1抑制剂致肿瘤患者肝损伤的临床研究, columnId=1246531407485489349, journalTitle=中国临床药理学杂志, columnName=临床与基础桥接研究, runingTitle=null, highlight=null, articleAbstract=
目的

观察肿瘤患者程序性细胞死亡蛋白-1(PD-1)抑制药致肝损伤的临床特点,并分析其影响因素。

方法

以我院收治的使用PD-1抑制药的肿瘤患者入选为研究对象,收集患者的临床资料,根据CTCAE V5.0标准评估患者治疗期间肝损伤发生情况,对肝损伤患者的临床病理特征进行汇总分析;单因素及多因素Logistic回归分析法分析影响肿瘤患者发生肝损伤的独立危险因素并构建列线图预测模型;用受试者工作特征(ROC)曲线、校准曲线、决策曲线(DCA)对预测模型的有效性进行评价。

结果

共纳入310例患者,PD-1抑制药致肝损伤发生率为11.94%(37例/310例);其中,1级肝损伤12例(32.43%)、2级肝损伤15例(40.54%)、3级肝损伤8例(21.62%)、4级肝损伤2例(5.41%);临床分型包括胆汁淤积型23例(62.16%)、肝生化学检查异常型12例(32.43%)、肝细胞损伤型2例(5.41%);发生肝损伤的中位时间为28.50(5.00~217.00)d,患者经停药或对症处理后肝功能恢复,平均恢复时间为(21.45±6.94)d。多因素Logistic回归分析显示,女性[比值比(OR)=2.36,95%置信区间(CI)=1.11~4.99]、合并肝疾病病史(OR=2.62,95% CI=1.10~6.24)、肿瘤肝转移(OR=3.10,95%CI=1.28~7.49)均为影响肿瘤患者发生肝损伤的独立危险因素(均P<0.05)。ROC分析示,列线图风险预测模型预测肝损伤的曲线下面积(AUC)(95%CI)、敏感度和特异度分别为0.86(0.82~0.90)、78.38%和83.52%;Homser-Lemeshow检验显示拟合优度良好(χ2=12.58,P>0.05);Bootstrap法验证显示,校准曲线与实际曲线一致性良好(Brier评分=0.09)。DCA分析示,在阈值为0.05~0.99时,该列线图预测模型可使患者临床获益。

结论

PD-1抑制药致肝损伤在肿瘤患者中较为常见,患者性别、肝疾病病史、肝转移与PD-1抑制药致肝损伤的发生有关;基于以上指标构建的列线图风险预测模型具有良好预测效能,可以为临床早期识别肝损伤高风险患者提供参考。

, authors=卢文洁, 高杏, 张玲, authorsList=卢文洁, 高杏, 张玲, authorCompany=null, correspAuthors=张玲, authorNote=

卢文洁(1993-),女,主管药师,主要从事药学的研究和工作

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张玲,主管药师 MP: 15050834325 E-mail:
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PD-1抑制剂致肿瘤患者肝损伤的临床研究
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卢文洁 , 高杏 , 张玲
中国临床药理学杂志 | 临床与基础桥接研究 2026,42(9): 1264-1270
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中国临床药理学杂志 |临床与基础桥接研究 2026 , 42 (9) : 1264 -1270
PD-1抑制剂致肿瘤患者肝损伤的临床研究
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卢文洁, 高杏, 张玲
作者信息
  • 徐州医科大学 附属医院 药学部,江苏 徐州 221006
通讯作者:
张玲,主管药师 MP: 15050834325 E-mail:
作者简介:

卢文洁(1993-),女,主管药师,主要从事药学的研究和工作

Clinical trial of PD-1 inhibitor-induced liver injury in tumor patients
Wen-jie LU, Xing GAO, Ling ZHANG
Affiliations
  • Department of Pharmacy, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221006, Jiangsu Province, China
出版时间: 2026-05-17 doi: 10.13699/j.cnki.1001-6821.2026.09.011
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目的

观察肿瘤患者程序性细胞死亡蛋白-1(PD-1)抑制药致肝损伤的临床特点,并分析其影响因素。

方法

以我院收治的使用PD-1抑制药的肿瘤患者入选为研究对象,收集患者的临床资料,根据CTCAE V5.0标准评估患者治疗期间肝损伤发生情况,对肝损伤患者的临床病理特征进行汇总分析;单因素及多因素Logistic回归分析法分析影响肿瘤患者发生肝损伤的独立危险因素并构建列线图预测模型;用受试者工作特征(ROC)曲线、校准曲线、决策曲线(DCA)对预测模型的有效性进行评价。

结果

共纳入310例患者,PD-1抑制药致肝损伤发生率为11.94%(37例/310例);其中,1级肝损伤12例(32.43%)、2级肝损伤15例(40.54%)、3级肝损伤8例(21.62%)、4级肝损伤2例(5.41%);临床分型包括胆汁淤积型23例(62.16%)、肝生化学检查异常型12例(32.43%)、肝细胞损伤型2例(5.41%);发生肝损伤的中位时间为28.50(5.00~217.00)d,患者经停药或对症处理后肝功能恢复,平均恢复时间为(21.45±6.94)d。多因素Logistic回归分析显示,女性[比值比(OR)=2.36,95%置信区间(CI)=1.11~4.99]、合并肝疾病病史(OR=2.62,95% CI=1.10~6.24)、肿瘤肝转移(OR=3.10,95%CI=1.28~7.49)均为影响肿瘤患者发生肝损伤的独立危险因素(均P<0.05)。ROC分析示,列线图风险预测模型预测肝损伤的曲线下面积(AUC)(95%CI)、敏感度和特异度分别为0.86(0.82~0.90)、78.38%和83.52%;Homser-Lemeshow检验显示拟合优度良好(χ2=12.58,P>0.05);Bootstrap法验证显示,校准曲线与实际曲线一致性良好(Brier评分=0.09)。DCA分析示,在阈值为0.05~0.99时,该列线图预测模型可使患者临床获益。

结论

PD-1抑制药致肝损伤在肿瘤患者中较为常见,患者性别、肝疾病病史、肝转移与PD-1抑制药致肝损伤的发生有关;基于以上指标构建的列线图风险预测模型具有良好预测效能,可以为临床早期识别肝损伤高风险患者提供参考。

免疫检查点抑制药  /  程序性细胞死亡蛋白-1  /  肿瘤疾病  /  免疫治疗  /  免疫相关药物不良反应  /  肝损伤
Objective

To observe clinical features of programmed cell death protein-1 (PD-1) inhibitor-induced liver injury in tumor patients and analyze its influencing factors.

Methods

Tumor patients treated with PD-1 inhibitors were enrolled. The clinical data were analyzed. The occurrence of liver injury during treatment was assessed according to CTCAE V5.0 criteria. Clinicopathological features of patients with liver injury were summarized. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for liver injury in tumor patients, and a nomogram prediction model was constructed receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were employed to evaluate validity of the model.

Results

The incidence of PD-1 inhibitor-induced liver injury among the 310 patients enrolled was 11.94% (37 cases/310 cases). Grade 1, grade 2, grade 3 and grade 4 liver injuries were observed in 12 cases (32.43%), 15 cases (40.54%), 8 cases (21.62%) and 2 cases (5.41%), respectively. Clinical types included cholestatic type in 23 cases (62.16%), abnormal liver biochemistry type in 12 cases (32.43%), and hepatocellular injury type in 2 cases (5.41%). The median time to the occurrence of liver injury was 28.50 (5.00-217.00) d. After drug withdrawal or symptomatic treatment, liver function recovered, and the mean recovery time was (21.45±6.94) d. Multivariate logistic regression analysis found female gender [odds rotio (OR)=2.36, 95% confidence interval (CI)=1.11-4.99], history of comorbid liver disease (OR=2.62, 95%CI=1.10-6.24), and liver metastasis (OR=3.10, 95%CI=1.28-7.49) as independent risk factors influencing the occurrence of liver injury in tumor patients (all P<0.05). ROC analysis showed that the area under curve (AUC) (95%CI) of the nomogram prediction model for predicting liver injury was 0.86 (0.82-0.90), with sensitivity of 78.38% and specificity of 83.52%. Hosmer-Lemeshow test showed good goodness-of-fit (χ2=12.58, P>0.05). Validation with Bootstrap revealed good agreement between the calibration curve and the actual curve (Brier score=0.09). DCA demonstrated that the nomogram prediction model provided clinical benefit when the threshold was between 0.05 and 0.99.

Conclusion

PD-1 inhibitor-induced liver injury is relatively common in tumor patients. Female gender, history of liver disease and liver metastasis are associated with its occurrence. The nomogram prediction model constructed based on these factors exhibits good predictive performance and can provide reference for early identification of high-risk patients.

immune checkpoint inhibitor  /  programmed cell death protein-1  /  neoplastic disease  /  immunotherapy  /  immune-related adverse drug reaction  /  liver injury
卢文洁, 高杏, 张玲. PD-1抑制剂致肿瘤患者肝损伤的临床研究. 中国临床药理学杂志, 2026 , 42 (9) : 1264 -1270 . DOI: 10.13699/j.cnki.1001-6821.2026.09.011
Wen-jie LU, Xing GAO, Ling ZHANG. Clinical trial of PD-1 inhibitor-induced liver injury in tumor patients[J]. Chinese Journal of Clinical Pharmacology, 2026 , 42 (9) : 1264 -1270 . DOI: 10.13699/j.cnki.1001-6821.2026.09.011

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doi: 10.13699/j.cnki.1001-6821.2026.09.011
  • 接收时间:2026-01-30
  • 首发时间:2026-08-06
  • 出版时间:2026-05-17
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  • 收稿日期:2026-01-30
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    徐州医科大学 附属医院 药学部,江苏 徐州 221006

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张玲,主管药师 MP: 15050834325 E-mail:
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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