| 94 | 0 | 52 |
| 下载次数 | 被引频次 | 阅读次数 |
目的 构建小细胞肺癌(SCLC)患者对铂类化疗耐药的预测模型，并评估该模型的效能和临床应用价值。方法 回顾性收集2014年2月至2024年2月在医院确诊为SCLC，且接受铂类化疗的176例患者数据。所有患者在治疗前均进行了血常规、生化等多项血液学检测。通过最小绝对收缩与选择算子(LASSO)算法筛选相关特征，随后使用单、多因素Logistic分析确定与铂类耐药相关的独立影响因素，并构建模型。模型效能和临床获益率通过受试者操作特征(ROC)曲线、校准曲线及决策曲线分析(DCA)进行验证。结果 LASSO-Logistic分析表明，白蛋白和中性粒细胞联合预后分级(ANPG)、神经元特异烯醇化酶(NSE)、血小板(PLT)、白蛋白与球蛋白比值(AGR)是SCLC患者铂类耐药的独立影响因素(P<0.05)。模型的验证结果显示其ROC曲线下面积(AUC)为0.809(95%CI:0.739-0.880)，模型的灵敏度、特异度、准确度分别为0.734、0.721、0.729。Hosmer-Lemeshow拟合优度检验结果显示模型拟合良好(χ2=8.549 2,P=0.381 7)。经Bootstrap法1 000次重抽样的校准曲线及DCA曲线显示，该模型的预测概率与实际预测概率一致性较高，并且具有较好的临床应用价值。结论 基于营养、炎症和肿瘤指标构建的列线图模型具有良好的预测能力，可为临床预测SCLC患者铂类化疗耐药性提供一定的指导价值。
Abstract：AIM To construct a nomogram model for predicting platinum-based chemotherapy resistance in small cell lung cancer(SCLC) and assess its efficacy and clinical value. METHODS A retrospective analysis was conducted on 176 SCLC patients, confirmed by pathology, who underwent platinum-based chemotherapy at the hospital from February 2014 to February 2024. All patients underwent pre-treatment hematological tests including blood routine and biochemical examinations. Feature selection was performed using the least absolute shrinkage and selection operator(LASSO) algorithm. Univariate and multivariate logistic regression analyses were used to identify independent factors influencing platinum resistance in SCLC, and a nomogram model was constructed. The model's efficacy and clinical benefit rate were evaluated using receiver operating characteristic(ROC) curves, calibration curves, and decision curve analysis(DCA). RESULTS LASSO-logistic regression analysis identified albumin and neutrophil combined prognostic grading(ANPG), neuron-specific enolase(NSE), platelet count(PLT), and albumin-to-globulin ratio(AGR) as independent factors predicting platinum resistance in SCLC(P < 0.05). The nomogram model constructed from these factors showed an area under the ROC curve(AUC) of 0.809(95% CI: 0.739-0.880), with sensitivity, specificity, and accuracy of 0.734, 0.721, and 0.729, respectively. The Hosmer-Lemeshow goodness-of-fit test demonstrated a good model fit(χ2=8.549 2,P=0.381 7). The calibration and DCA curves obtained through 1 000 resamples using the Bootstrap method showed high consistency between predicted and actual probabilities, indicating good clinical applicability. CONCLUSION The nomogram model based on nutritional, inflammatory, and tumor markers exhibits good predictive ability and can provide valuable guidance for predicting platinum resistance in SCLC patients.
[1]GAZDAR A F,BUNN P A,MINNA J D.Small-cell lung cancer:what we know,what we need to know and the path forward[J].Nat Rev Cancer,2017,17(12):725.
[2]SIEGEL R L,MILLER K D,WAGLE N S, et al.Cancer statistics,2023[J].CA Cancer J Clin,2023,73(1):17.
[3]FAIVRE C,EL CHEIKH R,BARBOLOSI D,et al.Mathematical optimisation of the cisplatin plus etoposide combination for managing extensive-stage small-cell lung cancer patients[J].Br J Cancer,2017,116(3):344.
[4]HERZOG B H,DEVARAKONDA S,GOVINDAN R.Overcoming chemotherapy resistance in SCLC[J].J Thorac Oncol,2021,16(12):2002.
[5]GAY C M,ALLISON STEWART C,PARK E M,et al.Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities[J].Cancer Cell,2021,39(3):346.
[6]SU Y P,LU C Y,ZHENG S F,et al.Precise prediction of the sensitivity of platinum chemotherapy in SCLC:establishing and verifying the feasibility of a CT-based radiomics nomogram[J].Front Oncol,2023,13:1006172.
[7]KLAPP V,áLVAREZ-ABRIL B,LEUZZI G,et al.The DNAdamage response and inflammation in cancer[J].Cancer Discov,2023,13(7):1521.
[8]GRETEN F R,GRIVENNIKOV S I.Inflammation and cancer:triggers,mechanisms,and consequences[J].Immunity,2019,51(1):27.
[9]HUANG Y,WANG H Y,HAO Y Z,et al.Myeloid PTEN promotes chemotherapy-induced NLRP3-inflammasome activation and antitumour immunity[J].Nat Cell Biol,2020,22(6):716.
[10]WANG C Y,JIN S,XU S Q,et al.High systemic immuneinflammation index(SII)represents an unfavorable prognostic factor for small cell lung cancer treated with etoposide and platinum-based chemotherapy[J].Lung,2020,198(2):405.
[11]JUNG S G,KIM J H,KIM H S,et al.Tumor response assessment by the single-lesion measurement per organ in small cell lung cancer[J].Chin J Cancer Res,2016,28(2):161.
[12]MICKE P,FALDUM A,METZ T,et al.Staging small cell lung cancer:Veterans Administration Lung Study Group versus International Association for the Study of Lung Cancer:what limits limited disease?[J].Lung Cancer,2002,37(3):271.
[13]PAVLOU M,AMBLER G,SEAMAN S R,et al.How to develop a more accurate risk prediction model when there are few events[J].BMJ,2015,351:h3868.
[14]WANG S D,YANG L,CI B,et al.Development and validation of a nomogram prognostic model for SCLC patients[J].J Thorac Oncol,2018,13(9):1338.
[15]PARK H,TSENG S C,SHOLL L M,et al.Molecular characterization and therapeutic approaches to small cell lung cancer:imaging implications[J].Radiology,2022,305(3):512.
[16]JEFFREY PETTY W,PAZ-ARES L.Emerging strategies for the treatment of small cell lung cancer:a review[J].JAMA Oncol,2023,9(3):419.
[17]KEY T J,BRADBURY K E,PEREZ-CORNAGO A,et al.Diet,nutrition,and cancer risk:what do we know and what is the way forward?[J].BMJ,2020,368:m511.
[18]N?ST T H,ALCALA K,URBAROVA I,et al.Systemic inflammation markers and cancer incidence in the UK Biobank[J].Eur J Epidemiol,2021,36(8):841.
[19]KURISHIMA K,WATANABE H, ISHIKAWA H,et al.Modified Glasgow prognostic score in patients with small-cell lung cancer[J].Mol Clin Oncol,2017,7(1):121.
[20]WANG Z T,WANG Y J,ZHANG X M,et al.Pretreatment prognostic nutritional index as a prognostic factor in lung cancer:review and meta-analysis[J].Clin Chim Acta,2018,486:303.
[21]GALVANO A,PERI M,GUARINI A A,et al.Analysis of systemic inflammatory bio markers in neuroendocrine carcinomas of the lung:prognostic and predictive significance of NLR, LDH,ALI,and LIPI score[J].Ther Adv Med Oncol,2020,12:1758835920942378.
[22]ZHOU T,ZHAO Y Y,ZHAO S,et al.Comparison of the prognostic value of systemic inflammation response markers in small cell lungcancer patients[J].J Cancer,2019,10(7):1685.
[23]HONG S D,ZHOU T,FANG W F,et al.The prognostic nutritional index(PNI)predicts overall survival of small-cell lung cancer patients[J].Tumour Biol,2015,36(5):3389.
[24]ZHANG L,LIU D,LI L,et al.The important role of circulating CYFRA21-1 in metastasis diagnosis and prognostic value compared with carcinoembryonic antigen and neuron-specific enolase in lung cancer patients[J].BMC Cancer,2017,17(1):96.
[25]SUN H F,HU P P,SHEN H C,et al.Albumin and neutrophil combined prognostic grade as a new prognostic factor in non-small cell lung cancer:results from a large consecutive cohort[J].PLoS One,2015,10(12):e0144663.
[26]PAONE G,DE ANGELIS G,MUNNO R,et al.Discriminant analysis on small cell lung cancer and non-small cell lung cancer by means of NSE and CYFRA-21.1[J].Eur Respir J,1995,8(7):1136.
[27]DU J,LI Y C,WANG L,et al.Selective application of neuroendocrine markers in the diagnosis and treatment of small cell lung cancer[J].Clin Chim Acta,2020,509:295.
[28]FALANGA A,MARCHETTI M,VIGNOLI A.Coagulation and cancer:biological and clinical aspects[J].J Thro mb Haemost,2013, 11(2):223.
[29]ZHANG J,ZHANG Y L,MA K X,et al.Efficacy and safety of adjunctive anticoagulation in patients with lung cancer without indication for anticoagulants:a systematic review and metaanalysis[J].Thorax,2013,68(5):442.
[30]ZHANG M,MO J H, HUANG W,et al.The ovarian cancerassociated microbiome contributes to the tumor's inflammatory microenvironment[J].Front Cell Infect Microbiol,2024,14:1440742.
[31]LIANG C W,KAN J,WANG J L,et al.Nasopharyngeal carcinomaassociated inflammatory cytokines:ongoing biomarkers[J].Front Immunol,2024, 15:1448012.
[32]LLOP-TALAVERON J,BADIA-TAHULL M B,LEIVA-BADOSA E.An inflammation-based prognostic score,the C-reactive protein/albumin ratio predicts the morbidity and mortality of patients on parenteral nutrition[J].Clin Nutr,2018,37(5):1575.
[33]AZAB B N,BHATT V R,VONFROLIO S,et al.Value of the pretreatment albumin to globulin ratio in predicting long-term mortality in breast cancer patients[J].Am J Surg,2013,206(5):764.
[34]SALCICCIA S,FRISENDA M,BEVILACQUA G,et al.Prognostic value of albumin to globulin ratio in non-metastatic and metastatic prostate cancer patients:a meta-analysis and systematic review[J].Int J Mol Sci,2022,23(19):11501.
[35]LV G Y,AN L,SUN X D,et al.Pretreatment albumin to globulin ratio can serve as a prognostic marker in human cancers:a metaanalysis[J].Clin Chim Acta,2018,476:81.
基本信息:
DOI：10.19577/j.1007-4406.2025.12.007
中图分类号:R734.2
引用信息:
[1]叶若雷,苏燕萍,张莹,等.小细胞肺癌铂类化疗耐药性预测模型的构建及效能评估[J].中国临床药学杂志,2025,34(12):926-933.DOI:10.19577/j.1007-4406.2025.12.007.
基金信息:
浙江省医药卫生科技计划项目（编号2023KY418）; 丽水市级自筹类公益性技术应用研究项目（编号2023SJZC092）