Volume 29 Issue 10
Oct.  2025
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YE Yuanxin, LIU Lulu, PAN Ting, JIANG Haitao. The value of preoperative prediction of histological grade of lung adenocarcinoma based on clinical and CT features[J]. Chinese Journal of General Practice, 2025, 23(10): 1743-1747. doi: 10.16766/j.cnki.issn.1674-4152.004219
Citation: YE Yuanxin, LIU Lulu, PAN Ting, JIANG Haitao. The value of preoperative prediction of histological grade of lung adenocarcinoma based on clinical and CT features[J]. Chinese Journal of General Practice, 2025, 23(10): 1743-1747. doi: 10.16766/j.cnki.issn.1674-4152.004219

The value of preoperative prediction of histological grade of lung adenocarcinoma based on clinical and CT features

doi: 10.16766/j.cnki.issn.1674-4152.004219
Funds:

 LTGY24H180015

  • Received Date: 2024-09-15
  •   Objective  To explore the relationship between both CT imaging features as well as clinical information and the histological grading of lung invasive non-mucinous adenocarcinomas, to construct a model for predicting their histological grading, as well as to visualize the model.  Methods  Clinical and CT features of 313 patients with invasive non-mucinous lung adenocarcinoma treated at Zhejiang Cancer Hospital from July to December 2021 were collected. Patients were divided into moderate-to-low-grade and high-grade groups based on histological grading. Imaging and combined models were developed through statistical analyses. Nomograms were constructed, and receiver operating characteristic (ROC) curves were generated to calculate the area under the curve (AUC). The DeLong test was used to compare AUCs.  Results  Multivariate analysis showed that the long diameter of CT imaging, the long diameter of solid components, the proportion of solid, and air bronchogram were influencing factors of histological grade (P < 0.05). The imaging model achieved an AUC of 0.879. Multivariate analysis of clinical data and CT imaging signs showed that there were statistically significant differences in smoking, neuron-specific enolase (NSE), the long diameter of CT imaging, the long diameter of solid component, the proportion of solid, and air bronchogram (P < 0.05). The combined model yielded an AUC of 0.899. The DeLong test showed no statistically significant difference in AUC between the imaging and combined models (P=0.070).  Conclusion  CT imaging features, together with serum tumor markers, provide valuable predictive information for distinguishing moderate-to-low-grade from high-grade invasive non-mucinous lung adenocarcinoma, supporting their potential role in preoperative histological grading.

     

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  • [1]
    MOREIRA A L, OCAMPO P S S, XIA Y, et al. A grading system for invasive pulmonary adenocarcinoma: a proposal from the international association for the study of lung cancer pathology committee[J]. J Thorac Oncol, 2020, 15(10): 1599-1610.
    [2]
    HEGEDVS F, ZOMBORI-TÓTH N, KISS S, et al. Prognostic impact of the IASLC grading system of lung adenocarcinoma: a systematic review and meta-analysis[J]. Histopathology, 2024, 85(1): 51-61.
    [3]
    张炳太, 张雷, 刘军, 等. 胸腔镜下肺叶与肺段切除术治疗早期非小细胞肺癌的临床效果观察[J]. 中华全科医学, 2022, 20(3): 399-402. doi: 10.16766/j.cnki.issn.1674-4152.002362

    ZHANG B T, ZHANG L, LIU J, et al. Clinical effect observation of thoracoscopic lobectomy and segmentectomy in the treatment of early non-small cell lung cancer[J]. Chinese Journal of General Practice, 2022, 20(3): 399-402. doi: 10.16766/j.cnki.issn.1674-4152.002362
    [4]
    TASOUDIS P, LOUFOPOULOS G, MANAKI V, et al. Long term outcomes after lobar versus sublobar resection for patients with non-small cell lung cancer: systematic review and individual patient data meta-analysis[J]. Lung Cancer, 2024, 195: 107929. DOI: 10.1016/j.lungcan.2024.107929.
    [5]
    SU H, XIE H, DAI C, et al. Procedure-specific prognostic impact of micropapillary subtype may guide resection strategy in small-sized lung adenocarcinomas: a multicenter study[J]. Ther Adv Med Oncol, 2020, 12: 1758835920937893. DOI: 10.1177/1758835920937893.
    [6]
    陈昶, 朱余明, 姜格宁, 等. 肺段切除术和肺叶切除术治疗直径≤2 cm且术中冰冻证实微乳头和实性亚型阴性肺腺癌的多中心随机对照研究[J]. 中国胸心血管外科临床杂志, 2021, 28(11): 1292-1298.

    CHEN C H, ZHU Y M, JIANG G N, et al. Comparison of segmentectomy versus lobectomy for ≤2 cm lung adenocarcinoma with micropapillary and solid subtype negative by intraoperative frozen sections: a multi-center randomized controlled trial[J]. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2021, 28(11): 1292-1298.
    [7]
    薛阳, 杜学松, 杨博, 等. 基于最新浸润性肺腺癌分级系统的手术前CT影像特征分析及预后评估[J]. 放射学实践, 2023, 38(9): 1121-1128.

    XUE Y, DU X S, YANG B, et al. Analysis of preoperative CT image features and prognostic assessment based on the latest classification system for invasive lung adenocarcinoma[J]. Radiol Practice, 2023, 38(9): 1121-1128.
    [8]
    PHILLIPS W W, GILL R R, MAZZOLA E, et al. Impact of nodule density in women with sublobar resection for stage ⅠA adenocarcinoma[J]. Ann Thorac Surg, 2021, 112(4): 1067-1075.
    [9]
    JING W, LIU M, LI W, et al. Prognostic implication of consolidation-to-tumor ratio in early lung adenocarcinoma: a retrospective cross-sectional study[J]. Quant Imaging Med Surg, 2024, 14(5): 3366-3380.
    [10]
    LU L, ZHA Z, ZHANG P, et al. Neuron-specific enolase promotes stem cell-like characteristics of small-cell lung cancer by downregulating NBL1 and activating the BMP2/Smad/ID1 pathway[J]. Oncogenesis, 2022, 11(1): 21. DOI: 10.1038/s41389-022-00396-5.
    [11]
    YAN P, HAN Y, TONG A, et al. Prognostic value of neuron-specific enolase in patients with advanced and metastatic non-neuroendocrine non-small cell lung cancer[J]. Biosci Rep, 2021, 41(8): BSR20210866. DOI: 10.1042/BSR20210866.
    [12]
    XU C M, LUO Y L, LI S, et al. Multifunctional neuron-specific enolase: its role in lung diseases[J]. Biosci Rep, 2019, 39(11): BSR20192732. DOI: 10.1042/BSR20192732.
    [13]
    PARK S, LEE S M, KIM S, et al. Volume doubling times of lung adenocarcinomas: correlation with predominant histologic subtypes and prognosis[J]. Radiology, 2020, 295(3): 703-712.
    [14]
    LI Z, WU W, PAN X, et al. Serum tumor markers level and their predictive values for solid and micropapillary components in lung adenocarcinoma[J]. Cancer Med, 2022, 11(14): 2855-2864.
    [15]
    董浩, 邱勇刚, 汪鑫斌, 等. 基于高分辨率CT征象建立logistic回归模型对IA期肺腺癌高级别模式的预测价值[J]. 中国癌症杂志, 2023, 33(8): 768-775.

    DONG H, QIU Y G, WANG X B, et al. Predictive value of logistic regression model based on high-resolution CT signs for high-grade pattern in stage IA lung adenocarcinoma[J]. China Oncology, 2023, 33(8): 768-775.
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