The value of serum inflammatory index combined with chest CT in differential diagnosis of benign and malignant pulmonary nodules

doi:10.19983/j.issn.2096-8493.20250065

Abstract

Abstract:

Objective: To analyze the value of serum inflammatory indexes combined with chest CT on differential diagnosis of benign and malignant pulmonary nodules. Methods: Two hundred and fifty-three patients with lung nodules who visited the Third People’s Hospital of Kunming from August 2022 to August 2024 were enrolled as study subjects, all of whom were diagnosed by CT-guided percutaneous lung puncture technique after admission to the hospital, with clear pathological examination results. Among them, 127 patients with lung cancer were deemed as the malignant lung nodule group, and 126 patients with benign lung nodules were deemed as the benign lung nodule group. The patients’ medical history, imaging data, serum inflammatory markers and other data were collected to explore the differences between the two groups in cell count-related indexes, cytokines, and acute-phase reactive proteins, and then these statistically significant different indexes were used as independent variables to be included in binary logistic regression analysis to screen out independent risk factors of lung cancer, and finally, receiver operating characteristic curve (ROC) was used to evaluate these risk factors’ diagnostic value in the differentiation of malignant and benign lung nodules. Results: The number of nodules, nodule diameter, lobular sign, burr sign, vascular bundle sign, CT value, NLR, LMR, SII, IL-5, IL-2, IL-6, IL-1β, IL-10, IFN-γ, IL-8, IL-17, TNF-α, CRP, PCT, and SAA were statistically significantly different in benign and malignant lung nodules (P<0.05). The result of binary logistic regression analysis showed the nodule diameter being 8-15 mm (OR=10.268, 95%CI: 1.719-61.321), nodule diameter being 15-30 mm (OR=59.194, 95%CI: 11.155-314.124), burr sign positive (OR=27.373, 95%CI: 3.901-192.055),LMR (OR=0.469, 95%CI: 0.282-0.779), IL-5(OR=1.557, 95%CI: 1.145-2.118), IL-2(OR=0.831, 95%CI: 0.748-0.924), SAA (OR=2.625, 95%CI: 1.407-4.897) and PCT (OR=1.763, 95%CI: 1.240-2.507) were related factors to differentiate benign and malignant nodules. Using ROC curve analysis, the AUC (95%CI) of nodule diameter, burr sign, LMR, IL-5, IL-2, SAA, and PCT for distinguishing benign and malignant nodules were 0.732 (0.669-0.795), 0.649 (0.581-0.717), 0.398 (0.532-0.672), 0.516 (0.445-0.588), 0.380 (0.311-0.450), 0.773 (0.715-0.830), and 0.821 (0.767-0.874), respectively. The AUC (95%CI) for distinguishing benign and malignant lung nodules by combined test metrics reached 0.983 (0.971-0.995). Conclusion: The combination of serum inflammatory index and chest CT examination has good differential diagnostic value in distinguishing benign and malignant nodules.

Key words: Sarcoidosis, pulmonary, Neutrophil, Lymphocyte, Monocyte, C-reactive protein, Procalcitonin, Tomography, X-ray computed

CLC Number:

R734.2

Xu Siyun, Lu Nihong. The value of serum inflammatory index combined with chest CT in differential diagnosis of benign and malignant pulmonary nodules[J]. Journal of Tuberculosis and Lung Disease , 2025, 6(5): 516-524. doi: 10.19983/j.issn.2096-8493.20250065

Figures/Tables 6

检测指标	良性组 (126例)	恶性组(127例)			Z值	P值
检测指标	良性组 (126例)	腺癌(87例)	鳞癌(25例)	小细胞癌(15例)	Z值	P值
NLR[M(Q₁,Q₃)]	2.50 (1.86,3.56)	2.59 (1.90,4.73)	4.04 (3.17,7.02)^ab	3.73 (2.31,6.25)	19.979	<0.001
LMR[M(Q₁,Q₃)]	3.34 (2.54,4.58)	3.06 (2.10,4.42)^a	2.27 (1.28,3.14)^ab	2.49 (1.33,2.93)	19.259	<0.001
PLR[M(Q₁,Q₃)]	165.52 (125.87,206.43)	165.58 (115.34,238.68)	227.52 (147.18,368.42)	150.89 (89.23,293.87)	6.166	0.104
SII[×10⁹g/L,M(Q₁,Q₃)]	582.06 (392.98,854.01)	640.19 (363.59,1155.42)	1390.96 (889.04,2486.67)^ab	711.47 (414.28,1384.94)	18.224	<0.001
IL-5[pg/ml,M(Q₁,Q₃)]	2.68 (1.93,4.37)	2.93 (2.03,4.04)	5.46 (2.57,10.13)^ab	2.20 (0.88,3.30)^c	15.235	0.002
IFN-α[pg/ml,M(Q₁,Q₃)]	2.81 (1.84,4.04)	2.52 (1.52,4.12)	2.67 (2.22,3.15)	2.09 (1.48,2.65)	4.386	0.223
IL-2[pg/ml,M(Q₁,Q₃)]	6.20 (2.67,21.61)	4.68 (2.21,8.09)^a	3.65 (2.15,4.87)^a	9.25 (4.69,16.81)^c	19.389	<0.001
IL-6[pg/ml,M(Q₁,Q₃)]	3.82 (1.46,9.08)	9.82 (4.46,18.02)^a	20.33 (6.04,34.15)^a	18.92 (11.94,72.95)^a	41.903	<0.001
IL-1β[pg/ml,M(Q₁,Q₃)]	5.48 (3.07,12.39)	9.72 (3.74,16.95)	6.76 (3.90,8.30)	23.28 (16.16,30.40)^abc	21.607	<0.001
IL-10[pg/ml,M(Q₁,Q₃)]	3.30 (2.44,4.88)	2.85 (1.96,4.53)	1.86 (1.67,2.26)^ab	4.86 (3.62,6.07)^bc	34.980	<0.001
IFN-γ[pg/ml,M(Q₁,Q₃)]	11.05 (5.48,17.78)	10.19 (5.69,19.60)	6.87 (5.31,7.60)^ab	9.27 (4.43,13.01)	15.529	0.001
IL-8[pg/ml,M(Q₁,Q₃)]	3.39 (1.73,9.41)	11.42 (4.41,19.77)^a	22.58 (8.55,29.34)^a	2.73 (1.69,4.51)^bc	31.181	<0.001
IL-17[pg/ml,M(Q₁,Q₃)]	4.13 (2.75,10.11)	2.90 (1.56,4.35)^a	4.45 (2.61,6.13)	7.12 (3.65,10.62)^b	29.143	<0.001
IL-12P70[pg/ml,M(Q₁,Q₃)]	2.01 (1.65,2.21)	2.00 (1.44,2.30)	1.53 (1.06,2.04)	2.05 (1.26,2.91)	4.878	0.197
TNF-α[pg/ml,M(Q₁,Q₃)]	2.64 (1.72,3.99)	4.00 (2.47,6.63)^a	2.33 (1.87,2.67)^b	2.32 (2.19,2.55)^ab	32.271	<0.001
CRP[mg/L,M(Q₁,Q₃)]	7.95 (1.64,28.03)	11.09 (2.77,24.43)	29.41 (11.46,67.74)^a	14.06 (8.60,43.37)	12.121	0.007
PCT[ng/ml,M(Q₁,Q₃)]	0.09 (0.04,0.16)	1.26 (0.45,2.41)^a	0.33 (0.10,0.98)^a	0.10 (0.06,0.12)^b	102.644	<0.001
SAA[mg/L,M(Q₁,Q₃)]	24.15 (3.40,101.77)	236.26 (75.62,322.80)^a	144.39 (36.70,254.35)^a	112.78 (73.08,129.19)	61.595	<0.001

References 31

[1]	Cao W, Qin K, Li F, et al. Comparative study of cancer profiles between 2020 and 2022 using global cancer statistics (GLOBOCAN) Comparative study of cancer profiles between J Natl Cancer Cent, 2024, 4(2):128-134. doi:10.1016/j.jncc.2024.05.001.
[2]	Han B, Zheng R, Zeng H, et al. Cancer incidence and mortality in China, 2022. J Natl Cancer Cent, 2024, 4(1): 47-53. doi:10.1016/j.jncc.2024.01.006.
[3]	中华医学会肿瘤学分会. 中华医学会肺癌临床诊疗指南(2024版). 中华医学杂志, 2024, 104(34):3175-3213. doi:10.3760/cma.j.cn112137-20240511-01092.
[4]	姚俊, 宋晓. 吉西他滨和顺铂方案联合康莱特注射液治疗晚期非小细胞肺癌的临床分析. 临床和实验医学杂志, 2017, 16(12):1195-1198. doi:10.3969/j.issn.1671-4695.2017.12.018.
[5]	Liu ZL, Zhu WR, Zhou WC, et al. Traditional Chinese medi-cinal herbs combined with epidermal growth factor receptor tyrosine kinase inhibitor for advanced non-small cell lung cancer: a systematic review and meta-analysis. J Integr Med, 2014, 12(4):346-358. doi:10.1016/S2095-4964(14)60034-0.
[6]	朱严严. 肿瘤标志物联合胸部影像学在肺癌早期诊断中的价值研究. 现代医用影像学, 2023, 32(8):1503-1505. doi:10.3969/j.issn.1006-7035.2023.08.033.
[7]	Jonas DE, Reuland DS, Reddy SM, et al. Screening for Lung Cancer With Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA, 2021, 325(10):971-987. doi:10.1001/jama.2021.0377.
[8]	Zhou Y, Tao L, Qiu J, et al. Tumor biomarkers for diagnosis, prognosis and targeted therapy. Signal Transduct Target Ther, 2024, 9(1):132. doi:10.1038/s41392-024-01823-2.
[9]	李源, 闵旭红, 王彬, 等. CT引导下经皮肺部病灶穿刺活检常见并发症影响因素与处理. 安徽医学, 2023, 44(6):697-701. doi:10.3969/j.issn.1000-0399.2023.06.017.
[10]	Bouras E, Karhunen V, Gill D, et al. Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis. BMC Med, 2022, 20(1):3. doi:10.1186/s12916-021-02193-0.
[11]	Marozzi M, Parnigoni A, Negri A, et al. Inflammation, Extracellular Matrix Remodeling, and Proteostasis in Tumor Microenvironment. Int J Mol Sci, 2021, 22(15):8102. doi:10.3390/ijms22158102.
[12]	Lim JS, Ibaseta A, Fischer MM, et al. Intratumoural heterogeneity generated by Notch signalling promotes small-cell lung cancer. Nature, 2017, 545(7654):360-364. doi:10.1038/nature22323.
[13]	Xu K, Zhang C, Du T, et al. Progress of exosomes in the diagnosis and treatment of lung cancer. Biomed Pharmacother, 2021, 134:111111. doi:10.1016/j.biopha.2020.111111.
[14]	Walter JE, Heuvelmans MA, de Jong PA, et al. Occurrence and lung cancer probability of new solid nodules at incidence screening with low-dose CT: analysis of data from the randomi-sed, controlled NELSON trial. Lancet Oncol, 2016, 17(7):907-916. doi:10.1016/S1470-2045(16)30069-9.
[15]	De Koning HJ, van der Aalst CM, de Jong PA, et al. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med, 2020, 382(6):503-513. doi:10.1056/NEJMoa1911793.
[16]	Lancaster HL, Heuvelmans MA, Oudkerk M. Low-dose computed tomography lung cancer screening: Clinical evidence and implementation research. J Intern Med, 2022, 292(1):68-80. doi:10.1111/joim.13480.
[17]	Song M, Zhang Q, Song C, et al. The advanced lung cancer inflammation index is the optimal inflammatory biomarker of overall survival in patients with lung cancer. J Cachexia Sarcopenia Muscle, 2022, 13(5):2504-2514. doi:10.1002/jcsm.13032.
[18]	Pelosi G, Sonzogni A, Viale G. The classification of lung carcinoma: time to change the morphology-based approach?. Int J Surg Pathol, 2010, 18(3):161-172. doi:10.1177/1066896910361736.
[19]	Tammemagi M, Ritchie AJ, Atkar-Khattra S, et al. Predicting Malignancy Risk of Screen-Detected Lung Nodules-Mean Diameter or Volume. J Thorac Oncol, 2019, 14(2):203-211. doi:10.1016/j.jtho.2018.10.006.
[20]	谢惠杰, 邹红, 吴赓, 等. 血常规炎症指标联合血清肿瘤标志物在肺癌诊断中的价值分析. 检验医学与临床, 2023, 20(6):758-763. doi:10.3969/j.issn.1672-9455.2023.06.010.
[21]	汤欣. 螺旋CT引导下经皮肺穿刺活检对不同大小肺结节及良恶性诊断的效能. 影像研究与医学应用, 2024, 8(17):179-181,184. doi:10.3969/j.issn.2096-3807.2024.17.057.
[22]	李婷, 黄麟洲, 张仕勇, 等. 肺部磨玻璃结节的高分辨CT征象及其评估肿瘤恶性侵袭程度的价值. 广西医学, 2024, 46(6):828-833. doi:10.11675/j.issn.0253-4304.2024.06.08.
[23]	许健, 李锋, 周芳, 等. 孤立性肺结节患者MSCT征象特点及其筛查价值分析. 中国CT和MRI杂志, 2021, 19(4):57-59. doi:10.3969/j.issn.1672-5131.2021.04.019.
[24]	蒋雨珂, 李长毅. 新型炎症标志物在肺癌中的应用. 现代医药卫生, 2024, 40(1):111-116,121. doi:10.3969/j.issn.1009-5519.2024.01.022.
[25]	Zhai B, Chen J, Wu J, et al. Predictive value of the hemoglobin, albumin, lymphocyte, and platelet (HALP) score and lymphocyte-to-monocyte ratio (LMR) in patients with non-small cell lung cancer after radical lung cancer surgery. Ann Transl Med, 2021, 9(12):976. doi:10.21037/atm-21-2120.
[26]	Sun H, Lee HS, Kim SH, et al. IL-2 can signal via chemokine receptors to promote regulatory T cells’ suppressive function. Cell Rep, 2023, 42(8):112996. doi:10.1016/j.celrep.2023.112996.
[27]	Hou Y, Xiang B, Yang Z, et al. Down-regulation of interleukin-2 predicts poor prognosis and associated with immune escape in lung adenocarcinoma. Int J Immunopathol Pharmacol, 2023, 37:3946320231202748. doi:10.1177/03946320231202748.
[28]	韩翔, 张培, 王娟, 等. 肺癌组织中嗜酸细胞浸润及白细胞介素5表达的意义. 中华医学杂志, 2011, 91(14):956-960. doi:10.3760/cma.j.issn.0376-2491.2011.14.005.
[29]	Cremona M, Calabrò E, Randi G, et al. Elevated levels of the acute-phase serum amyloid are associated with heightened lung cancer risk. Cancer, 2010, 116(5):1326-1335. doi:10.1002/cncr.24868.
[30]	Sung HJ, Ahn JM, Yoon YH, et al. Identification and validation of SAA as a potential lung cancer biomarker and its involvement in metastatic pathogenesis of lung cancer. J Proteome Res, 2011, 10(3):1383-1395. doi:10.1021/pr101154j.
[31]	Chaftari AM, Hachem R, Reitzel R, et al. Role of Procalcitonin and Interleukin-6 in Predicting Cancer, and Its Progression Independent of Infection. PLoS One, 2015, 10(7):e0130999. doi:10.1371/journal.pone.0130999.

特征	良性组(126例)	恶性组(127例)	统计检验值	P值
年龄(岁,$\overline{x}$±s)	58.51±10.44	61.09±11.97	t=1.831	0.068
性别[例,构成比(%)]			χ²=0.244	0.621
男性	87(69.0)	84(66.1)
女性	39(31.0)	43(33.9)
结节数量[例,构成比(%)]			χ²=28.389	<0.001
孤立性	18(14.3)	57(44.9)
≥2个	108(85.7)	70(55.1)
结节直径[例,构成比(%)]			χ²=55.453	<0.001
5~8mm	98(77.8)	47(37.0)
8~15mm	16(12.7)	14(11.0)
15~30mm	12(9.5)	66(52.0)
分叶征[例,构成比(%)]			χ²=36.969	<0.001
是	6(4.8)	45(35.4)
否	120(95.2)	82(64.6)
毛刺征[例,构成比(%)]			χ²=35.620	<0.001
是	6(4.8)	44(34.6)
否	120(95.2)	83(65.4)
血管束集征[例,构成比(%)]			χ²=5.772	0.016
是	10(7.9)	23(18.1)
否	116(92.1)	104(81.9)
CT值(HU,$\overline{x}$±s)	-306.41±248.614	-359.51±154.73	t=2.038	0.043

自变量	赋值
结节数量	0=孤立性;1=结节数量≥2个
结节直径	1=5~8mm;2=8~15mm;3=15~30mm
毛刺征	1=是;0=否
分叶征	1=是;0=否
血管集束征	1=是;0=否

影响因素	β值	s${}_{\overline{x}}$值	Wald χ²值	OR值	95%CI值	P值
结节直径8~15mm	2.329	0.912	6.525	10.268	1.719~61.321	0.011
结节直径15~30mm	4.081	0.852	22.967	59.194	11.155~314.124	<0.001
毛刺征	3.310	0.994	11.085	27.373	3.901~192.055	0.001
LMR	-0.757	0.259	8.552	0.469	0.282~0.779	0.003
IL-5	0.443	0.157	7.962	1.557	1.145~2.118	0.005
Il-2	-0.185	0.054	11.830	0.831	0.748~0.924	0.001
SAA	0.965	0.318	9.201	2.625	1.407~4.897	0.002
PCT	0.567	0.180	9.970	1.763	1.240~2.507	0.002

检测项目	AUC值	AUC的95%CI值	P值	敏感度	特异度	正确指数	截断值
结节直径	0.732	0.669~0.795	<0.001	0.52	0.90	0.905	2.50
毛刺征	0.649	0.581~0.717	<0.001	0.36	0.95	0.952	0.50
LMR	0.398	0.532~0.672	0.005	0.50	0.69	0.193	3.40
IL-5	0.516	0.445~0.588	0.037	0.49	0.63	0.119	3.16
IL-2	0.380	0.311~0.450	0.007	0.33	0.95	0.286	14.44
SAA	0.773	0.715~0.830	<0.001	0.69	0.75	0.439	102.46
PCT	0.821	0.767~0.874	<0.001	0.67	0.98	0.653	0.30
联合检测	0.983	0.971~0.995	<0.001	0.92	0.97	0.890	0.53