Deep learning model based on primary tumor to predict lymph node status in clinical stage IA lung adenocarcinoma:a multicenter study

Objective:To develop a deep learning model to predict lymph node(LN)status in clinical stage IA lung adeno-carcinoma patients.Methods:This diagnostic study included 1,009 patients with pathologically confirmed clinical stage T1N0M0 lung adenocarcinoma from two independent datasets(699 from Cancer Hospital of Chinese Academy of Medical Sciences and 310 from PLA General Hospital)between January 2005 and December 2019.The Cancer Hospital dataset was randomly split into a training cohort(559 patients)and a validation cohort(140 patients)to train and tune a deep learning model based on a deep residual network(ResNet).The PLA Hospital dataset was used as a testing cohort to evaluate the generalization ability of the model.Thoracic radiologists manually segmented tumors and interpreted high-resolution computed tomography(HRCT)features for the model.The predictive performance was assessed by area under the curves(AUCs),accuracy,precision,recall,and F1 score.Subgroup analysis was performed to evaluate the potential bias of the study population.Results:A total of 1,009 patients were included in this study;409(40.5%)were male and 600(59.5%)were female.The median age was 57.0 years(inter-quartile range,IQR:50.0-64.0).The deep learning model achieved AUCs of 0.906(95%CI:0.873-0.938)and 0.893(95%CI:0.857-0.930)for predicting pN0 disease in the testing cohort and a non-pure ground glass nodule(non-pGGN)testing cohort,respectively.No significant difference was detected between the testing cohort and the non-pGGN testing cohort(P=0.622).The precisions of this model for predicting pN0 disease were 0.979(95%CI:0.963-0.995)and 0.983(95%CI:0.967-0.998)in the testing cohort and the non-pGGN testing cohort,respectively.The deep learning model achieved AUCs of 0.848(95%CI:0.798-0.898)and 0.831(95%CI:0.776-0.887)for predicting pN2 disease in the testing cohort and the non-pGGN testing cohort,respectively.No significant difference was detected between the testing cohort and the non-pGGN testing cohort(P=0.657).The recalls of this model for predicting pN2 disease were 0.903(95%CI:0.870-0.936)and 0.931(95%CI:0.901-0.961)in the testing cohort and the non-pGGN testing cohort,respectively.Conclusions:The superior performance of the deep learning model will help to target the extension of lymph node dissection and reduce the ineffective lymph node dissection in early-stage lung adenocarcinoma patients.

A novel recurrence-associated metabolic prognostic model for risk stratification and therapeutic response prediction in patients with stage Ⅰ lung adenocarcinoma

Objective:The proportion of patients with stageⅠlung adenocarcinoma(LUAD)has dramatically increased with the prevalence of low-dose computed tomography use for screening.Up to 30%of patients with stageⅠLUAD experience recurrence within 5 years after curative surgery.A robust risk stratification tool is urgently needed to identify patients who might benefit from adjuvant treatment.Methods:In this first investigation of the relationship between metabolic reprogramming and recurrence in stageⅠLUAD,we developed a recurrence-associated metabolic signature(RAMS).This RAMS was based on metabolism-associated genes to predict cancer relapse and overall prognoses of patients with stageⅠLUAD.The clinical significance and immune landscapes of the signature were comprehensively analyzed.Results:Based on a gene expression profile from the GSE31210 database,functional enrichment analysis revealed a significant difference in metabolic reprogramming that distinguished patients with stageⅠLUAD with relapse from those without relapse.We then identified a metabolic signature(i.e.,RAMS)represented by 2 genes(ACADM and RPS8)significantly related to recurrence-free survival and overall survival times of patients with stageⅠLUAD using transcriptome data analysis of a training set.The training set was well validated in a test set.The discriminatory power of the 2 gene metabolic signature was further validated using protein values in an additional independent cohort.The results indicated a clear association between a high risk score and a very poor patient prognosis.Stratification analysis and multivariate Cox regression analysis showed that the RAMS was an independent prognostic factor.We also found that the risk score was positively correlated with inflammatory response,the antigen-presenting process,and the expression levels of many immunosuppressive checkpoint molecules(e.g.,PD-L1,PD-L2,B7-H3,galectin-9,and FGL-1).These results suggested that high risk patients had immune response suppression.Further analysis revealed that anti-PD-1/PD-L1 immunotherapy did not have significant benefits for high risk patients.However,the patients could respond better to chemotherapy.Conclusions:This study is the first to highlight the relationship between metabolic reprogramming and recurrence in stageⅠLUAD,and is the first to also develop a clinically feasible signature.This signature may be a powerful prognostic tool and help further optimize the cancer therapy paradigm.

Number of involved nodal stations: a better lymph node classification for clinical stage IA lung adenocarcinoma

Background:With the popularization of lung cancer screening,more early-stage lung cancers are being detected.This study aims to compare three types of N classifications,including location-based N classification(pathologic nodal classification[pN]),the number of lymph node stations(nS)-based N classification(nS classification),and the combined approach proposed by the International Association for the Study of Lung Cancer(IASLC)which incorporates both pN and nS classification to determine if the nS classification is more appropriate for early-stage lung cancer.Methods:We retrospectively reviewed the clinical data of lung cancer patients treated at the Cancer Hospital,Chinese Academy of Medical Sciences between 2005 and 2018.Inclusion criteria was clinical stage IA lung adenocarcinoma patients who underwent resection during this period.Sub-analyses were performed for the three types of N classifications.The optimal cutoffvalues for nS classification were determined with X-tile software.Kaplan‒Meier and multivariate Cox analyses were performed to assess the prognostic significance of the different N classifications.The prediction performance among the three types of N classifications was compared using the concordance index(C-index)and decision curve analysis(DCA).Results:Of the 669 patients evaluated,534 had pathological stage N0 disease(79.8%),82 had N1 disease(12.3%)and 53 had N2 disease(7.9%).Multivariate Cox analysis indicated that all three types of N classifications were independent prognostic factors for prognosis(all P<0.001).However,the prognosis overlaps between pN(N1 and N2,P=0.052)and IASLC-proposed N classification(N1b and N2a1[P=0.407],N2a1 and N2a2[P=0.364],and N2a2 and N2b[P=0.779]),except for nS classification subgroups(nS0 and nS1[P<0.001]and nS1 and nS>1[P=0.006]).There was no significant difference in the C-index values between the three N classifications(P=0.370).The DCA results demonstrated that the nS classification provided greater clinical utility.Conclusion:The nS classification might be a better choice for nodal classification in clinical stage IA lung adeno-carcinoma.

Low-depth whole genome sequencing reveals copy number variations associated with higher pathologic grading and more aggressive subtypes of lung non-mucinous adenocarcinoma

Objective:Histology grade,subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival.The aim of the study was to investigate the relationship between chromosomal instability,morphological subtypes and the grading system used in lung non-mucinous adenocarcinoma(LNMA).Methods:We developed a whole genome copy number variation(WGCNV)scoring system and applied next generation sequencing to evaluate CNVs present in 91 LNMA tumor samples.Results:Higher histological grades,aggressive subtypes and more advanced TNM staging were associated with an increased WGCNV score,particularly in CNV regions enriched for tumor suppressor genes and oncogenes.In addition,we demonstrate that 24-chromosome CNV profiling can be performed reliably from specific cell types(<100 cells)isolated by sample laser capture microdissection.Conclusions:Our findings suggest that the WGCNV scoring system we developed may have potential value as an adjunct test for predicting the prognosis of patients diagnosed with LNMA.

Prognostic value of ground glass opacity on computed tomography in pathological stage I pulmonary adenocarcinoma: A meta-analysis

BACKGROUND The clinical role of ground glass opacity(GGO)on computed tomography(CT)in stage I pulmonary adenocarcinoma patients currently remains unclear.AIM To explore the prognostic value of GGO on CT in lung adenocarcinoma patients who were pathologically diagnosed with tumor-node-metastasis stage I.METHODS A comprehensive and systematic search was conducted through the PubMed,EMBASE and Web of Science databases up to April 3,2021.The hazard ratio(HR)and corresponding 95%confidence interval(CI)were combined to assess the association between the presence of GGO and prognosis,representing overall survival and disease-free survival.Subgroup analysis based on the ratio of GGO was also conducted.STATA 12.0 software was used for statistical analysis.RESULTS A total of 12 studies involving 4467 patients were included.The pooled results indicated that the GGO predicted favorable overall survival(HR=0.44,95%CI:0.34-0.59,P<0.001)and disease-free survival(HR=0.35,95%CI:0.18-0.70,P=0.003).Subgroup analysis based on the ratio of GGO further demonstrated that the proportion of GGO was a good prognostic indicator in pathological stage I pulmonary adenocarcinoma patients,and patients with a higher ratio of GGO showed better prognosis than patients with a lower GGO ratio did.CONCLUSION This meta-analysis manifested that the presence of GGO on CT predicted favorable prognosis in tumor-node-metastasis stage I lung adenocarcinoma.Patients with a higher GGO ratio were more likely to have a better prognosis than patients with a lower GGO ratio.

地榆升白片在Ⅱ期非小细胞肺癌术后化疗中对骨髓保护作用的研究

目的：观察地榆生白片在Ⅱ期非小细胞肺癌术后化疗中对骨髓的保护作用。方法：回顾90例Ⅱ期非小细胞肺癌术后患者，以规律口服地榆升白片的为预防组，未口服的为对照组，观察两组化疗完成时间，骨髓抑制程度及重组人粒细胞刺激因子用量。结果：预防组4周期化疗的平均时间为（100．0±0．59）d，对照组平均时间为（118．3±1．39）d，差畀有统计学意义（P〈0．05）。重组人粒细胞刺激因子的用量预防组平均（3．04±0．15）支，对照组平均（6．03±0．29）支，差异有统计学意义（P〈0．05）。在第3周期化疗中，预防组中发生Ⅱ度以上骨髓抑制发生率为61．3％，对照组为82．1％，差异有统计学意义（P〈0．05）。在第4周期化疗中，预防组中发生Ⅱ度以上骨髓抑制发生率为74．1％，对照组为92．8％，差异有统计学意义（P〈0．05）。结论：地榆生白片能够缩短Ⅱ期非小细胞肺癌患者术后4周期化疗的完成时间，减少重组人粒细胞刺激因子用量，降低Ⅱ度以上骨髓抑制的发生率，在Ⅱ期非小细胞肺癌患者术后化疗中起到了重要的骨髓保护作用，降低化疗风险，进而提高患者的生存期。

丹参酮ⅡA诱导人肺腺癌A549细胞凋亡

目的探讨丹参酮ⅡA(TanshinoneⅡA,TanⅡA)抗人肺腺癌A549作用及其可能作用机制。方法通过细胞形态学和MTT法观察TanⅡA对A549细胞增殖的影响;应用Hoechest33258和PI双染法观察细胞凋亡;采用荧光分光光度计检测细胞内钙及线粒体膜电位;RT-PCR检测Bad和MT-1A mRNA的表达。结果 TanⅡA能抑制A549细胞增殖,且随TanⅡA剂量的增加和作用时间的延长而增强,TanⅡA作用A549细胞24、48和72h的IC50分别为117.85、14.87和6.89μmol·L-1。TanⅡA作用A549细胞24h后,A549细胞出现染色质聚集等典型的凋亡形态学改变,且随TanⅡA剂量的增加,A549细胞凋亡百分率逐渐增大。TanⅡA作用后,A549细胞的细胞内钙升高、线粒体膜电位降低、Bad mRNA表达增加、MT-1A mRNA表达下调。结论 TanⅡA具有抗A549作用,其诱导细胞凋亡可能与钙依赖性通路和MT-1A表达下调有关。

黄芪多糖注射液对Ⅱ-Ⅲ期非小细胞肺癌放疗患者免疫功能影响研究

目的:观察黄芪多糖注射液对Ⅱ-Ⅲ期非小细胞肺癌放疗患者免疫功能的影响。方法:80例随机分为对照组和观察组各40例。两组均进行放疗,观察组加用黄芪多糖注射液治疗。结果:经治疗后观察组CD4+、CD4+/CD8+明显高于对照组,Karnofsky评分、SF-36评分明显高于对照组,组间比较差异有统计学意义(P<0.05)。结论:黄芪多糖注射液可有效改善Ⅱ-Ⅲ期非小细胞肺癌放疗患者免疫功能。

Ⅰ-ⅡA期肺腺癌根治术后复发转移危险因素分析及预测模型构建

目的分析Ⅰ-ⅡA期肺腺癌根治术后复发转移的危险因素,构建Ⅰ-ⅡA期肺腺癌根治术后复发转移的预测模型。方法行肺癌根治术并经病理确诊为Ⅰ-ⅡA期LUAD患者205例,收集患者的临床资料,包括性别、年龄、吸烟史、术前肺功能、肿瘤位置、肿瘤最大直径、淋巴结清扫数目、术后病理见微乳头结构、胸膜侵犯、脉管癌栓、辅助化疗情况、术前血清癌胚抗原(CEA)水平、术前中性粒细胞计数与淋巴细胞比值(NLR)、术前预后营养指数(PNI),统计患者术后复发转移情况;采用Kaplan-Meier法绘制生存曲线,联合log-rank法分析Ⅰ-ⅡA期LUAD术后复发转移的相关因素;采用COX比例风险模型分析Ⅰ-ⅡA期LUAD术后复发转移的独立危险因素。使用R语言软件构建Ⅰ-ⅡA期LUAD根治术后复发转移风险预测列线图。采用Bootstrap法对列线图进行内部验证,计算该列线图的C-index值;绘制列线图的ROC曲线,评价列线图的区分度;采用校准曲线评价列线图的一致性。结果肿瘤最大直径、术后病理见微乳头结构、术前肺功能、术前血清CEA水平、术前NLR、术前PNI与Ⅰ-ⅡA期LUAD根治术后复发转移有关(P均<0.05),其中肿瘤最大直径>3 cm、术前血清CEA>5 ng/mL、术前NLR>2.285、术前PNI≤46.625是Ⅰ-ⅡA期LUAD根治术后复发转移的独立危险因素(P均<0.05)。构建了Ⅰ-ⅡA期LUAD根治术后复发转移风险预测列线图。列线图的C-index值为0.814(95%CI为0.751~0.877),该列线图预测Ⅰ-ⅡA期LUAD根治术后2年、3年、5年复发转移的ROC的AUC分别为0.757(95%CI为0.641~0.874)、0.696(95%CI为0.595~0.797)、0.675(95%CI为0.589~0.762),Ⅰ-ⅡA期LUAD根治术后复发转移风险预测列线图的校准曲线均接近参考线。结论Ⅰ-ⅡA期LUAD根治术后复发转移的独立危险因素为肿瘤最大直径>3 cm、术前血清CEA>5 ng/mL、术前NLR>2.285、术前PNI≤46.625。成功构建了Ⅰ-ⅡA期LUAD根治术后复发转移风险预测模型,且模型的区分度与一致性均较好。

钙调蛋白依赖性蛋白激酶Ⅱ在维拉帕米逆转肺腺癌顺铂化疗耐药中的作用

目的探讨钙调蛋白依赖性蛋白激酶Ⅱ(CaMKⅡ)在维拉帕米逆转肺腺癌顺铂化疗耐药中的作用。方法在肺腺癌细胞系(A549)中,采用CCK-8法检测维拉帕米逆转顺铂耐药的能力,采用流式细胞仪Annexin V-FITC/PI法检测维拉帕米逆转顺铂耐药中凋亡水平的效果,采用Western blotting检测逆转耐药过程中P-CaMKⅡ/CaMKⅡ蛋白表达水平的变化。结果在肺腺癌细胞系(A549)中,单药顺铂组、顺铂联合维拉帕米组的细胞增长抑制率分别为(55. 00±2. 60)%、(32. 30±1. 80)%,差异有统计学意义(P <0. 05)。凋亡实验表明,单药顺铂组细胞凋亡率为10. 30%,顺铂联合维拉帕米组为21. 60%,差异有统计学意义(P <0. 05)。Western blotting结果显示,在A549细胞中,顺铂联合维拉帕米组P-CaMKⅡ/Ca MKⅡ的表达明显低于单药顺铂组。结论在肺腺癌细胞中,CaMKⅡ参与维拉帕米逆转化疗耐药的过程。

简单肺功能评价对Ⅰ、Ⅱ期非小细胞肺癌术式选择的价值

目的 探讨简单肺功能评价对Ⅰ、Ⅱ期非小细胞肺癌手术患者手术方式选择的指导价值。方法 选取Ⅰ、Ⅱ期非小细胞肺癌手术患者60例,应用常规肺功能检查仪检测患者的最大通气量（maximum voluntary ventilation,MVV）、肺活量（vital capacity,VC）、用力肺活量（forced vital capacity,FVC）、第1秒用力呼气容积（forced expiratory volume in one second,FEV1）,评价患者的通气功能,并选择相应的手术方法。同时观察患者肺功能水平与术后并发症的相关性。结果 肺功能指标中MVV〉80.0%、VC〉96.5%、FVC〉48.1%、FEV1〉2.4 L的24例患者实施左或右全肺切除术,MVV为47.5%-77.8%、VC为41.8%-97.5%、FVC为51.8%-74.3%、FEV1为2.3-3.0 L的20例行单肺叶切除术,而MVV〈41.7%、VC为36.3%-94.7%、FVC为30.1%-57.8%、FEV1为0.7-1.0 L的4例不适行任何开胸手术。在呼吸衰竭、死亡严重并发症方面,正常通气功能组发生率低于轻中度损伤与重度损伤组（P〈0.05）,但轻中度损伤与重度损伤组比较差异无统计学意义。肺部感染、心律失常与低氧血症的发生率随着肺通气功能损伤程度的加重而增高（P〈0.05）。结论 对Ⅰ、Ⅱ期非小细胞肺癌手术患者术前简单评估肺功能,可积极指导患者术式的选择,同时肺通气功能较差的患者术后并发症较严重,应提前有效预防。

电视胸腔镜与传统开胸肺叶切除术治疗Ⅰ～Ⅱ期非小细胞肺癌的效果及对CRP水平的影响

目的探讨电视胸腔镜与传统开胸肺叶切除术治疗Ⅰ~Ⅱ期非小细胞肺癌的效果及对患者CRP水平的影响。方法选择我院2014年3月至2016年12月收治的Ⅰ~Ⅱ期非小细胞肺癌患者94例作为研究对象,随机分为对照组和观察组,每组47例。对照组给予传统开腹肺叶切除术治疗,观察组给予电视胸腔镜肺叶切除术。比较两组患者治疗前、后CRP水平、并发症及预后情况。结果治疗后1、3 d,两组患者的CRP水平较治疗前明显升高,但观察组明显低于对照组(P<0.05)。观察组心律失常、支气管胸膜瘘和肺部感染发生率均低于对照组(P<0.05)。观察组术后1年生存率为76.60%,高于对照组的59.57%,但差异无统计学意义(P>0.05)。结论Ⅰ~Ⅱ期非小细胞肺癌患者行电视胸腔镜肺叶切除术治疗临床效果理想,值得推广和应用。

^(18)F-FDG PET/CT原发灶代谢参数对肺腺癌临床分期的预测价值

目的:探讨基于^(18)F-脱氧葡萄糖(FDG)PET/CT代谢参数对肺腺癌临床分期的预测价值。方法:回顾性分析经病理确诊的86例肺腺癌患者的临床和影像资料。86例中早期组54例,进展期组32例。测量原发灶最大径、最大标准化摄取值(SUV_(max))、平均标准摄取值(SUV_(mean)),以相对阈值法(40%为阈值)测量肿瘤代谢体积(MTV)及糖酵解总量(TLG)。采用单因素及多因素logistic回归分析对进展期肺腺癌的危险因素进行分析,并生成相应的预测模型。通过ROC曲线分析各参数及模型预测进展期肺腺癌的价值。结果:进展期组中央型肺癌、有肺癌相关症状、血清癌胚抗原(CEA)≥5.00μg/L的构成比,以及原发灶最大径、SUV_(max)、MTV、TLG均大于早期组,差异均有统计学意义(均P<0.01)。多因素分析显示,有肺癌相关症状、血清CEA≥5.00μg/L、SUV_(max)均为进展期肺腺癌的独立危险因素(均P<0.01)。ROC曲线分析显示,各代谢参数对进展期肺腺癌均有良好的预测效能,其中以TLG的AUC最大,达0.782,最佳界值为14.27 g,敏感度为90.6%,特异度为61.1%。logistic回归模型诊断进展期肺腺癌的AUC为0.854(95%CI 0.773~0.934),敏感度、特异度和准确率分别为78.1%、79.6%和79.0%。结论:^(18)F-FDG PET/CT原发灶代谢参数对进展期肺腺癌具有良好的预测效能,联合临床特征能提高对肺腺癌临床分期的诊断效能,为临床提供指导。

PFKP在肺腺癌组织中的表达及其与预后的关系

目的:探索磷酸果糖激酶血小板型(platelet-type phosphofructokinase,PFKP)在肺腺癌(adenocarcinoma of lung,LUAD)中的关键作用。方法:利用癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库观察PFKP在肺腺癌组织和癌旁组织中的表达情况。采用免疫组化检测临床样本肺腺癌组织和癌旁组织PFKP表达情况。利用TCGA数据库进一步探讨PFKP的表达及其在LUAD预后和免疫浸润中的作用。结果:PFKP在LUAD中高表达,且PFKP高表达与临床病理特征(AJCC分期和TNM分期)及不良预后相关。Kaplan-Meier生存分析和ROC曲线分析进一步证实,PFKP高表达组患者的中位总生存时间显著低于低表达组,且在1年、3年和5年生存预测中呈现出高度预测性。富集分析表明,PFKP的生物学功能参与到抗肿瘤药物代谢的过程中。此外PFKP与肿瘤微环境和免疫治疗密切相关。本研究筛选出一批对PFKP高表达的LUAD患者敏感性较高的临床药物和正在被研究的抑制剂。结论:PFKP在LUAD发生发展中的关键作用和其作为潜在药物治疗靶标的可能性,使其成为肺癌研究和治疗的重要靶标。

那不勒斯预后评分对青年肺腺癌患者预后的预测价值分析

目的探讨那不勒斯预后评分(NPS)对青年肺腺癌患者的预后预测价值。方法回顾性分析2017年11月至2022年12月收治的青年肺腺癌患者110例的临床资料,根据NPS分为低危组(0分)27例、中危组(1~2分)58例和高危组(3~4分)25例,比较3组患者临床资料。采用Kaplan-Meier和Cox回归分析评估NPS对预后的影响。结果3组TNM分期、乳酸脱氢酶、SII、癌胚抗原水平及手术、化疗、靶向治疗患者所占比例比较差异有统计学意义(P<0.05,P<0.01);年龄、性别、吸烟史、婚姻状态、体质量指数、血小板/淋巴细胞比率、神经元特异性烯醇化酶比较差异无统计学意义(P>0.05)。Kaplan-Meier生存分析曲线显示高危组患者总生存期和无进展生存期明显短于低危组和中危组(P<0.01)。TNM分期、手术、化疗和NPS分级是影响青年肺腺癌患者总生存期的独立影响因素(P<0.05,P<0.01)。结论NPS对青年肺腺癌患者的预后有良好预测价值。

正元胶囊联合培美曲塞+顺铂方案治疗晚期肺腺癌的临床分析

目的观察正元胶囊联合培美曲塞^(+)顺铂(AP)方案治疗晚期肺腺癌的临床效果。方法纳入该院2019年2月至2022年2月收治的80例晚期肺腺癌患者为研究对象,采用随机数字表法分为2组。对照组40例予AP方案治疗,治疗组40例在对照组基础上予正元胶囊治疗,2组均3周为1个疗程,共治疗4个疗程。统计2组实体瘤疗效,比较2组治疗前和治疗4个疗程后肿瘤标志物水平[细胞角蛋白19片段抗原(CYFRA21-1)、癌胚抗原(CEA)、糖类抗原125(CA125)]、免疫功能指标[CD4^(+)、CD8^(+)、自然杀伤(NK)细胞]、生活质量[卡氏功能状态评分(KPS)],对比2组治疗期间不良反应发生情况,随访1年记录患者生存情况。结果治疗组实体瘤缓解率47.50%(19/40),对照组实体瘤缓解率25.00%(10/40),治疗组疗效优于对照组(P<0.05)。2组治疗后血清CYFRA21-1、CEA、CA125水平均较本组治疗前降低(P<0.05),且治疗组治疗后均低于对照组(P<0.05)。治疗组治疗后CD4^(+)、NK细胞均较本组治疗前升高(P<0.05),对照组治疗后CD4^(+)、NK细胞均降低(P<0.05)。治疗组治疗后CD4^(+)、NK细胞水平均高于对照组(P<0.05)。2组治疗后KPS评分均较本组治疗前升高(P<0.05),且治疗组治疗后高于对照组(P<0.05)。治疗组无进展生存时间为(14.03±4.38)个月,对照组为(10.48±4.52)个月,治疗组高于对照组(P<0.05)。随访期间,治疗组总生存率60.00%(24/40),对照组总生存率25.00%(10/40);经Log-rank检验,治疗组总生存率高于对照组(P<0.05)。结论晚期肺腺癌采用正元胶囊联合AP方案治疗效果显著,可改善患者免疫功能和生活质量,降低肿瘤标志物水平,延长生存时间,且不会增加不良反应。

构建可切除T2~T4期肺腺癌根治术后复发生存的列线图模型

目的分析可切除T_(2)~T_(4)期肺腺癌患者根治术后复发生存的影响因素及构建列线图模型。方法收集2019年1月至2022年12月间在泉州市第一医院行肺癌根治术的患者进行回顾性分析。共纳入400例连续患者,根据Zstats统计学软件生成随机序列号,将患者按7∶3分为训练集(n=280)和验证集(n=120)。记录患者的临床、病理、手术和随访信息,随访截至2024年5月31日,记录患者的无复发生存期(RFS)。采用单因素及多因素Cox风险比例回归模型分析影响肺腺癌患者RFS的因素。结果训练集患者中位随访时间为14.27个月,复发率为40.36%,验证集中位随访时间为14.10个月,复发率为50.83%。训练集与验证集的人口统计学和临床特征均衡可比(P>0.05)。单因素Cox回归及LASSO Cox分析,C反应蛋白-白蛋白比(CAR)、体质量指数(BMI)、分化程度、肿瘤大小、淋巴血管侵犯(LVI)、血小板与淋巴细胞比值(PLR)、癌胚抗原(CEA)是影响肺腺癌患者术后RFS的因素。多因素Cox回归分析结果显示,低分化/中-低分化、LVI、CAR≥1.09×10^(-3)是影响肺腺癌患者术后RFS的独立危险因素。根据上述结果,构建了3年和5年的RFS列线图预测模型。训练集中,RFS预测模型的C-index为0.783(95%CI:0.744~0.822),验证集采用RFS列线图模型对队列中每例患者进行评分,C-index为0.717(95%CI:0.651~0.784)。训练集和验证集中,预测3年及5年内RFS的时间依赖性受试者工作特征曲线下面积均>0.700。在训练集和验证集中列线图的校准曲线显示出预测和观察到的生存率高度一致。Kaplan-Meier法结果显示,在训练集及验证集中,低风险肺腺癌患者的RFS均显著长于高风险患者。结论本研究构建包含CAR、分化程度及LVI在内的预测肺腺癌患者根治术后RFS的列线图模型,该列线图模型可准确预测患者复发生存,有助于对高危患者进行适当的术后管理。

IB期肺腺癌患者辅助治疗方案的筛选

目的探索IB期肺腺癌患者的辅助治疗方案。方法收集2013年1月~2021年12月在我院行手术治疗的IB期肺腺癌患者,根据术后不同辅助治疗模式分为辅助靶向治疗组(EGFR-TKIs)、辅助化疗组(CT)和临床观察组(CO)。对比3组患者的临床资料和随访结果,无疾病生存期、总生存的分析采用Kaplan-Meier法并行log-rank检验,COX回归分析患者无疾病生存期(DFS)的预测因素。主要研究终点是5年DFS率,次要研究终点为DFS、3年总生存期(OS)以及辅助治疗的安全性。结果共纳入653例术后诊断为IB期肺腺癌患者,其中EGFR-TKIs组111例,CT组108例,CO组434例。中位随访时间43个月,TKIs组、CT组和CO组的5年DFS率分别为92.8%、80.7%及81.7%,TKIs组的5年DFS率显著高于CO组(P<0.01)。TKIs组、CT组和CO组的3年OS均无统计学差异。亚组分析显示,T3~4 cmN0M0中TKIs组、CT组和CO组的5年DFS率分别为92.6%、84.0%及81.4%,TKIs组的5年DFS率显著高于CO组(P<0.05),3组间的3年OS无统计学差异。而T2ViscPlN0M0中TKIs组、CT组和CO组的5年DFS率分别为95.1%、71.4%及83.5%,组间差异并无统计学意义,3组间的3年OS亦无统计学差异。多因素COX回归分析结果显示,年龄(P<0.05;HR 0.631,95%CI 0.401-0.993)、实性结节(P<0.01;HR 7.620,95%CI 3.037-19.121)、微乳头/实性成分(P<0.05;HR 1.776,95%CI 1.010-3.122)、脉管癌栓(P<0.05;HR 2.981,95%CI 1.198-7.419)及辅助治疗(P<0.01)是DFS的独立预测因素。安全性方面,皮疹、甲沟炎及腹泻仍然是靶向药物最常见的不良反应。化疗组不良反应主要为血液系统的抑制和胃肠道反应,3级以上不良反应率高于TKIs组(44.4%vs 9.0%)。结论辅助靶向治疗有助于提高T3~4 cmN0M0的IB期肺腺癌患者的DFS,但T2ViscPlN0M0患者并不能从靶向治疗中获益。辅助化疗并不能改善IB期肺腺癌患者的DFS和OS。

基于CT影像学特征的肺腺癌组织分化程度分析及患者预后预测价值

目的:评估国际肺癌研究协会(International Association for the Study of Lung Cancer,IASLC)分级系统和传统计算机体层成像(computed tomography,CT)影像学特征之间的联系,并构建基于CT影像学特征的预后分层模型。方法:回顾并分析2019年1月—2022年5月南京市胸科医院收治的102例原发性病理(p)Ⅰ期(T1N0M0或T2aN0M0)肺腺癌(lung adenocarcinoma,LUAD)患者的病历。根据2020年IASLC分级系统对患者进行分级,比较了不同IASLC组织学分级之间以及复发组和未复发组之间的临床病理和影像学特征。Logistic回归分析用于确定IASLC分级相关的CT征象,并通过多变量Cox回归模型确定患者无病生存期(disease-free survival,DFS)的影响因素。结果:102例LUAD患者分为1级15例(14.7%),2级63例(61.8%)和3级24例(23.5%)。在30.4个月随访期间,16例(15.7%)患者复发。较高的CTR(OR=2.152,95%CI 1.530~3.264,P=0.005)和较高的CT值(OR=3.730,95%CI 2.841~6.353,P=0.001)是较高组织学分级的独立危险因素。联合上述2个独立因素预测IASLC 3级的曲线下面积(area under curve,AUC)为0.912(95%CI 0.877~0.937;P<0.001),与单独使用平均CT值或实变肿瘤比率(consolidation tumor ratio,CTR)的AUC差异无统计学意义。多变量Cox回归分析显示,年龄(HR=1.05,95%CI 1.02~1.09,P=0.003)、CTR(HR=2.81,95%CI 1.16~6.77,P=0.022)、CT值(HR=2.49,95%CI 1.19~5.25,P=0.016)、毛刺征(HR=5.96,95%CI 2.30~15.43,P<0.001)和组织学分级(HR=4.31,95%CI 2.28~8.14,P<0.001)是DFS的独立危险因素。结论:较大的CTR以及较高的平均CT值是较高IASLC组织学分级的独立预测因子。CTR(截断值<0.25和≥0.75)和平均CT值(截断值<-410 HU和≥-210 HU)可用作IASLC分级系统的术前替代物。

基于深度学习和多组学数据的肺腺癌分期预测研究

为解决癌症分期难以精准决策这一问题,对452例肺腺癌患者的信使核糖核酸(mRNA)转录数据、微核糖核酸(miRNA)转录数据和DNA甲基化3种组学数据进行集成融合,并采用随机森林算法进行分期预测。首先对从癌症基因组图谱(TCGA)数据库获取的3种组学数据进行预处理,将mRNA转录数据和DNA甲基化数据进行基因位点匹配,再使用4种不同的多组学集成策略对预处理后的组学数据进行集成,最后使用随机森林算法对集成后的数据进行分期预测并使用准确度、卡帕系数以及曲线下面积(AUC)作为预测效果的评价指标。研究结果显示,采用多组学集成策略在分期预测上具有更高的准确率,其中基于深度学习的集成策略的预测效果最好,评价指标分别为0.940、0.931和0.986,有希望应用于未来的肺腺癌分期预测中。