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整合临床和组织病理学因素的局部晚期非小细胞肺癌患者新辅助放化疗及切除术后长期生存的预后模型

Prognostic model for long-term survival of locally advanced non-small-cell lung cancer patients after neoadjuvant radiochemotherapy and resection integrating clinical and histopathologic factors.

作者信息

Pöttgen Christoph, Stuschke Martin, Graupner Britta, Theegarten Dirk, Gauler Thomas, Jendrossek Verena, Freitag Lutz, Jawad Jehad Abu, Gkika Eleni, Wohlschlaeger Jeremias, Welter Stefan, Hoiczyk Matthias, Schuler Martin, Stamatis Georgios, Eberhardt Wilfried

机构信息

Department of Radiotherapy, West German Cancer Center, University of Duisburg-Essen, Essen, Germany.

German Cancer Consortium (DKTK), Heidelberg, Germany.

出版信息

BMC Cancer. 2015 May 6;15:363. doi: 10.1186/s12885-015-1389-4.

DOI:10.1186/s12885-015-1389-4
PMID:25943191
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4428235/
Abstract

BACKGROUND

Outcome of consecutive patients with locally advanced non-small cell lung cancer and histopathologically proven mediastional lymph node metastases treated with induction chemotherapy, neoadjuvant radiochemotherapy and thoracotomy at the West German Cancer Center between 08/2000 and 06/2012 was analysed. A clinico-pathological prognostic model for survival was built including partial or complete response according to computed tomography imaging (CT) as clinical parameters as well as pathologic complete remission (pCR) and mediastinal nodal clearance (MNC) as histopathologic factors.

METHODS

Proportional hazard analysis (PHA) and recursive partitioning analysis (RPA) were used to identify prognostic factors for survival. Long-term survival was defined as survival ≥ 36 months.

RESULTS

A total of 157 patients were treated, median follow-up was 97 months. Among these patients, pCR and MNC were observed in 41 and 85 patients, respectively. Overall survival was 56 ± 4% and 36 ± 4% at 24 and 60 months, respectively. Sensitivities of pCR and MNC to detect long-term survivors were 38% and 61%, specificities were 84% and 52%, respectively. Multivariable survival analysis revealed pCR, cN3 category, and gender, as prognostic factors at a level of α < 0.05. Considering only preoperative available parameters, CT response became significant. Classifying patients with a predicted hazard above the median as high risk group and the remaining as low risk patients yielded better separation of the survival curves by the inclusion of histopathologic factors than by preoperative factors alone (p < 0.0001, log rank test). Using RPA, pCR was identified as the top prognostic factor above clinical factors (p = 0.0006). No long term survivors were observed in patients with cT3-4 cN3 tumors without pCR.

CONCLUSIONS

pCR is the dominant histopathologic response parameter and improves prognostic classifiers, based on clinical parameters. The validated prognostic model can be used to estimate individual prognosis and forms a basis for patient selection for treatment intensification.

摘要

背景

分析了2000年8月至2012年6月期间在西德癌症中心接受诱导化疗、新辅助放化疗及开胸手术治疗的连续性局部晚期非小细胞肺癌且经组织病理学证实有纵隔淋巴结转移患者的预后情况。构建了一个生存的临床病理预后模型,纳入根据计算机断层扫描成像(CT)得出的部分或完全缓解作为临床参数,以及病理完全缓解(pCR)和纵隔淋巴结清扫(MNC)作为组织病理学因素。

方法

采用比例风险分析(PHA)和递归划分分析(RPA)来确定生存的预后因素。长期生存定义为生存≥36个月。

结果

共治疗157例患者,中位随访时间为97个月。在这些患者中,分别有41例和85例观察到pCR和MNC。24个月和60个月时的总生存率分别为56±4%和36±4%。pCR和MNC检测长期生存者的敏感性分别为38%和61%,特异性分别为84%和52%。多变量生存分析显示,在α<0.05水平时,pCR、cN3类别和性别为预后因素。仅考虑术前可用参数时,CT反应具有显著性。将预测风险高于中位数的患者分类为高风险组,其余患者分类为低风险患者,与仅采用术前因素相比,纳入组织病理学因素能更好地分离生存曲线(p<0.0001,对数秩检验)。使用RPA,pCR被确定为高于临床因素的首要预后因素(p = 0.0006)。在无pCR的cT3-4 cN3肿瘤患者中未观察到长期生存者。

结论

pCR是主要的组织病理学反应参数,可改善基于临床参数的预后分类器。经验证的预后模型可用于估计个体预后,并为选择强化治疗的患者提供依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/7b3706fd270a/12885_2015_1389_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/bd40694ec95c/12885_2015_1389_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/75577f1001fd/12885_2015_1389_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/c6003911dcf9/12885_2015_1389_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/7b3706fd270a/12885_2015_1389_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/bd40694ec95c/12885_2015_1389_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/75577f1001fd/12885_2015_1389_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/c6003911dcf9/12885_2015_1389_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a17/4428235/7b3706fd270a/12885_2015_1389_Fig4_HTML.jpg

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