The clinical value of combined detection of seven lung cancer-related autoantibodies in assisting the diagnosis of non-small-cell lung cancer

Abstract

Aim: Evaluate the clinical value of lung-cancer-related autoantibodies (CAGE, GAGE7, GBU4-5, MAGEA1, P53, PGP9.5, SOX2) in auxiliary diagnosis of non-small-cell lung cancer (NSCLC).

Methods: We detected the concentrations of above 7 antibodies and lung cancer markers (CEA, NSE, CYFRE21-1) and drew area under the receiver characteristic curve of 316 patients.

Results: The concentrations of CAGE, GBU4-5, MAGEA1, P53, PGP9.5 and SOX2 of significantly higher than other groups (p < 0.01). The sensitivity of different stages and pathological types of NSCLC consistent. Among them, the sensitivity of combined-detection in diagnosing adenocarcinoma and squamous cell carcinoma significantly better than CEA, NSE and CYFRA21-1.

Conclusion: The combined detection has better efficacy in assisting the diagnosis of NSCLC and has certain clinical promotion and application value.

Plain language summary

Article highlights.

Introduction

• The diagnostic efficacy of single lung cancer-related autoantibodies is low.

Comparison of concentration levels of seven autoantibodies in different groups

• The concentrations of CAGE, GBU4-5, MAGEA1, P53, PGP9.5 and SOX2 were significantly higher than those of lung benign disease group, other malignant solid tumor group, autoimmune disease group and healthy body group, while the concentration of GAGE7 in lung cancer group was significantly higher than that of healthy body group. However, there was no significant difference between the levels and those of lung benign disease group, other malignant solid tumor group and autoimmune disease group.

Efficacy of seven autoantibodies alone & in combination in the diagnosis of NSCLC

• The combined assay of seven autoantibodies had an AUC of 0.791, with an overall sensitivity of 60.1% and a specificity of 83.0%. It is suggested that seven lung cancer-related autoantibodies have good efficacy in the auxiliary diagnosis of NSCLC.

Comparison of sensitivity between seven autoantibodies & three traditional tumor markers in the diagnosis of NSCLC

• The combined detection of seven autoantibodies showed consistent sensitivity in the diagnosis of different stages and pathological types of NSCLC, and the sensitivity in the diagnosis of adenocarcinoma and squamous cell carcinoma was significantly superior to CEA, NSE and CYFRA21-1.

Conclusion

• The combined detection of seven autoantibodies has certain clinical application value.

1. Introduction

Lung cancer is the malignant tumor with the highest incidence rate and mortality in China and even in the world. In March 2023, according to the latest national cancer statistics released by the National Cancer Center, there were 815,000 new cases of lung cancer and 714,000 deaths in China. It is expected that by 2030, the number of newly diagnosed lung cancer patients in China will exceed 1 million [1–3]. Due to the insidious onset of lung cancer, lack of specific symptoms in the early stages and rapid disease progression in the later stages, more than 70% of patients are initially diagnosed in the late stage, missing the opportunity for surgical treatment, resulting in an overall poor prognosis for patients and bringing a heavy medical and economic burden to the country and society [4]. At present, the standard method of lung cancer screening recommended by China and European and American countries is low-dose spiral computed tomography. However, the application of LDCT in lung cancer screening faces two serious challenges: first, its false positive rate of diagnosis of pulmonary nodules exceeds 90% and second, repeated CT exposure may induce second tumors [5]. More importantly, non-high-risk individuals undergoing LDCT screening can seriously encroach on medical resources and cause unnecessary waste of socio-economic resources. It is worth noting that in recent years, with the in-depth exploration of the occurrence and development process of lung cancer and the rapid advancement of detection technology, tumor biomarkers derived from blood have received widespread attention due to their convenient and relatively non-invasive sampling [6–8]. However, currently commonly used tumor biomarkers in clinical practice, such as carcinoembryonic antigen (CEA), neuron specific enolase (NSE) and cytokeratin 19 fragment (CYFRA21-1), have low sensitivity for lung cancer screening and early adjuvant diagnosis and cannot meet clinical requirements. Therefore, we urgently need to explore new tumor markers that can be used for lung cancer screening and early auxiliary diagnosis.

Tumor-associated antigens (TAAs) are proteins expressed during the development and progression of tumor cells [9]. At the early stage of tumor development, immune cells in the body can recognize TAAs and produce corresponding antibodies through humoral immunity mediated by B cells, namely tumor associated autoantibodies, which are released into the body's bloodstream [10]. Detection of tumor-related autoantibodies in peripheral blood is helpful to diagnose tumor-related tumors more accurately at an early stage. Based on the above mechanism, some studies attempted to evaluate the value of assisting the diagnosis of solid tumors by detecting different combinations of tumor-related autoantibodies and the results found that combined detection of multiple tumor-related autoantibodies could assist clinicians in early diagnosis of multiple solid tumors, including lung cancer [11–15]. Importantly, the relevant detection kit has been approved by some European and American countries for the auxiliary diagnosis of lung cancer, suggesting that it has certain clinical application prospects.

However, on the one hand, previous studies lacked high-quality, multi-group and large sample cohorts. On the other hand, researchers tend to only include lung cancer and healthy population cohort, unable to make a comprehensive evaluation of the sensitivity and specificity of tumor-related autoantibodies, limiting their large-scale clinical application.

In this study, by establishing a high quality, large sample clinical cohort with different disease spectra, we aim to investigate the combined detection of seven lung cancer-related autoantibodies (CAGE, GAGE7, GBU4-5, MAGEA1, P53, PGP9.5, SOX2) in the diagnosis of NSCLC; evaluate the sensitivity and specificity of seven autoantibodies in the diagnosis of NSCLC at different stages and pathological types, and compare their sensitivity differences with those of three traditional tumor markers in the assisted diagnosis of NSCLC.

2. Data & methods

2.1. Clinical data collection

A total of 316 patients with NSCLC were selected from the First People's Hospital of Fuyang District of Hangzhou from May 2019 to May 2022. Inclusion criteria: 1 Age range from 18 to 85 years old; 2 Diagnosis of NSCLC was confirmed through pathological examination after ultrasound, chest CT guided puncture, and/or surgical resection; 3 The patient has not received systemic anti-tumor therapy such as radiotherapy and chemotherapy; 4 The informed consent of the patient has been obtained and the clinical data are complete. Exclusion criteria: 1 Combined with primary malignant tumors of other sites; 2 Patients also suffer from serious infectious diseases, important organ failure, etc. 3 Unable to obtain informed consent from patients. Besides, 115 patients with benign lung diseases, 41 patients with other malignant solid tumors confirmed by pathology, 47 patients with autoimmune diseases and 112 healthy people were included. This study has been approved and approved by the Ethics Committee of the First People's Hospital of Fuyang District, Hangzhou, with ethics number 2021-010.

2.2. Sample collection & preservation

Collect 10 ml of peripheral venous blood from all enrolled patients in the study and separate serum, plasma and blood cells using gradient centrifugation (3000 rpm, centrifugation for 10 min). The serum sample is used for detecting autoantibody concentration, and the corresponding detection is completed within 6 hours after centrifugation. For serum samples that cannot be tested in a timely manner, they will be frozen in a -80°C freezer.

2.3. Sample testing

The concentration of seven lung cancer-related autoantibodies in the peripheral blood samples was detected using the enzyme-linked immunosorbent assay (ELISA) kit provided by Hangzhou Kaibaoluo Biotechnology Co., Ltd. The Multiskan MK3 enzyme-linked immunosorbent assay (ELISA) kit from Thermo was used to measure the absorbance at 450 nm, and the specimens were tested strictly according to the reagent instructions. According to previous studies and kit instructions, the cut-off values for seven types of autoantibody positive readings were set as follows: CAGE 7.2 U/ml, GAGE7 14.4 U/ml, GBU4-5 7.0 U/ml, MAGEA1 11.9 U/ml, P53 13.1 U/ml, PGP9.5 11.1 U/ml, SOX2 10.3 U/ml. Use an electrochemiluminescence detection system to detect the levels of CEA, NSE and CYFRA21-1 in all peripheral blood samples, strictly following the instructions of the instrument and kit during the operation process.

2.4. Statistic analysis

Statistical analysis was performed using GraphPad PRISM 9.0 software. The statistical data were expressed as frequency or percentage, and χ2 test was used for comparison between groups. Measurement data conforming to normal distribution were represented by ?x ± s, and t-test was used for comparison between groups. The measurement data of skew distribution were expressed as the median. Non-parametric Mann-Whitney U test was used for comparison between two groups, and Kruskal-Wallis H test was used for comparison between multiple groups. By drawing the Receiver Operating Characteristic curve (AUC), we comprehensively evaluated the diagnostic value of seven autoantibodies alone and combined in NSCLC. All statistical tests in this study were bilateral tests. p < 0.05 was considered statistically significant.

3. Results

3.1. Baseline data & clinical characteristics of included patients

A total of 316 NSCLC patients were included in this study: including 205 males and 111 females, average age 61 years old (range: 30 to 85 years old). Among them, 85 never smokers and 231 current or former smokers. The pathology department of the hospital confirmed 206 cases of adenocarcinoma, 100 cases of squamous cell carcinoma, 8 cases of large cell carcinoma and 4 cases of NSCLC not otherwise specified (NOS). According to the International Association for the Study of Lung Cancer's eighth edition of TNM staging, there were 88 stage I patients, 66 stage II patients, 64 stage III patients and 98 stage IV patients. 115 patients with benign pulmonary diseases: including 75 males and 40 females, average age 60 years (range: 18 to 78 years), included 39 never-smokers and 76 current or former smokers. 41 patients with other malignant solid tumors: including 18 males and 23 females; Mean age 52 years (range: 26 to 73 years); included 10 never-smokers and 31 current or former smokers. 47 patients with autoimmune diseases, including 30 males and 17 females, average age 50 years (range: 18 to 63 years), 11 never-smokers and 36 current or former smokers. 112 healthy people were examined: among them, 41 were males and 71 were females, average age 46 years (range: 30 to 78 years), included 35 never smokers and 77 current or former smokers (Table 1).

Table 1.

Baseline characteristics of all included patients.

Median age, years (range)	Lung cancer group (n = 316)		Benign lung disease group (n = 115)		Other cancers group (n = 41)		Autoimmune disease group (n = 47)		Healthy control group (n = 112)
	61 (30–85)		60 (18–78)		52 (26–73)		50 (18–63)		46 (30–78)
	n	%	n	%	n	%	n	%	n	%
Gender
Male	205	64.9%	75	65.2%	18	43.9%	30	63.8%	41	36.6%
Female	111	35.1%	40	34.8%	23	56.1%	17	36.2%	71	63.4%
Smoking History
Never	85	26.9%	39	33.9%	10	24.4%	11	23.4%	35	31.3%
Ever/current	231	73.1%	76	66.1%	31	75.6%	36	76.6%	77	68.8%
NSCLC
Ad	206	65.2%	0	0.00	0	0.00	0	0.00	0	0.00
SCC	100	31.6%	0	0.00	0	0.00	0	0.00	0	0.00
LCC	8	2.5%	0	0.00	0	0.00	0	0.00	0	0.00
NOS	4	1.3%	0	0.00	0	0.00	0	0.00	0	0.00
Stage
I	88	27.8%	0	0.00	0	0.00	0	0.00	0	0.00
II	66	20.9%	0	0.00	0	0.00	0	0.00	0	0.00
III	64	20.3%	0	0.00	0	0.00	0	0.00	0	0.00
IV	98	31.0%	0	0.00	0	0.00	0	0.00	0	0.00

Ad: Adenocarcinoma; LCC: Large cell lung cancer; NOS: Not otherwise specified; NSCLC: Non-small-cell lung cancer; SCC: Squamous cell lung cancer.

3.2. Comparison of concentration levels of seven autoantibodies in different groups

Overall, the concentration levels of CAGE, GBU4-5, MAGEA1, P53, PGP9.5 and SOX2 in peripheral blood samples of NSCLC patients were significantly higher than those of other control groups, and the differences were statistically significant (p < 0.05, Figure 1). Although the GAGE7 concentration level in the lung cancer group was higher than that in the other control groups, the difference was not statistically significant (p > 0.05, Figure 1). Specifically, the concentration levels of CAGE, GBU4-5, MAGEA1, P53, PGP9.5 and SOX2 in peripheral blood samples of NSCLC patients were significantly higher than those in the benign lung disease group, other malignant solid tumors group, autoimmune disease group and healthy examination group, with statistical significance (p < 0.05, Figure 2). The concentration level of GAGE7 in the lung cancer group was significantly higher than that in the healthy physical examination group (p < 0.05), but there was no significant difference in concentration levels compared with the benign lung disease group, other malignant solid tumors group and autoimmune disease group (p > 0.05, Figure 2).

Figure 1.

Comparison of seven autoantibody concentrations in the blood of lung cancer patients and other groups. (A) Comparison of P53 concentration in the blood of lung cancer patients and other groups. (B) Comparison of PGP9.5 concentration in the blood of lung cancer patients and other groups. (C) Comparison of SOX2 concentration in the blood of lung cancer patients and other groups. (D) Comparison of GAGE7 concentration in the blood of lung cancer patients and other groups. (E) Comparison of GBU4-5 concentration in the blood of lung cancer patients and other groups. (F) Comparison of MAGEA1 concentration in the blood of lung cancer patients and other groups. (G) Comparison of CAGE concentration in the blood of lung cancer patients and other groups.

*p < 0.05; **p < 0.01.

Figure 2.

Comparison of seven autoantibody concentrations in peripheral blood of lung cancer patients, patients with benign lung diseases, patients with other malignant solid tumors, patients with autoimmune diseases and healthy individuals undergoing physical examinations. (A) Comparison of P53 concentration in peripheral blood of lung cancer patients, patients with benign lung diseases, patients with other malignant solid tumors, patients with autoimmune diseases and healthy individuals undergoing physical examinations. (B) Comparison of PGP9.5 concentration in peripheral blood of lung cancer patients, patients with benign lung diseases, patients with other malignant solid tumors, patients with autoimmune diseases and healthy individuals undergoing physical examinations. (C) Comparison of SOX2 concentration in peripheral blood of lung cancer patients, patients with benign lung diseases, patients with other malignant solid tumors, patients with autoimmune diseases and healthy individuals undergoing physical examinations. (D) Comparison of GAGE7 concentration in peripheral blood of lung cancer patients, patients with benign lung diseases, patients with other malignant solid tumors, patients with autoimmune diseases and healthy individuals undergoing physical examinations. (E) Comparison of GBU4-5 concentration in peripheral blood of lung cancer patients, patients with benign lung diseases, patients with other malignant solid tumors, patients with autoimmune diseases and healthy individuals undergoing physical examinations. (F) Comparison of MAGEA1 concentration in peripheral blood of lung cancer patients, patients with benign lung diseases, patients with other malignant solid tumors, patients with autoimmune diseases and healthy individuals undergoing physical examinations. (G) Comparison of CAGE concentration in peripheral blood of lung cancer patients, patients with benign lung diseases, patients with other malignant solid tumors, patients with autoimmune diseases and healthy individuals undergoing physical examinations.

*p < 0.05; **p < 0.01.

3.3. Efficacy of seven autoantibodies alone & in combination in the diagnosis of NSCLC

ROC curve was drawn with benign lung disease group and healthy physical examination group as control group and NSCLC group as disease group. The results showed the AUC of CAGE, GAGE7, GBU4-5, MAGEA1, P53, PGP9.5 and SOX2 in the diagnosis of NSCLC was 0.651 (p < 0.01), 0.507 (p > 0.05), 0.644 (p < 0.01), 0.588 (p < 0.01), 0.609 (p < 0.01), 0.561 (p < 0.01) and 0.590 (p < 0.01), respectively. Besides, the AUC of seven autoantibodies combined for the diagnosis of NSCLC was 0.791 (p < 0.01, Figure 3).

Figure 3.

The efficacy of detecting seven types of autoantibodies separately and in combination for diagnosing lung cancer. (A) The efficacy of P53 detection in diagnosing lung cancer. (B) The efficacy of PGP9.5 detection in diagnosing lung cancer. (C) The efficacy of SOX2 detection in diagnosing lung cancer. (D) The efficacy of GAGE7 detection in diagnosing lung cancer. (E) The efficacy of GBU4-5 detection in diagnosing lung cancer. (F) The efficacy of MAGEA1 detection in diagnosing lung cancer. (G) The efficacy of CAGE detection in diagnosing lung cancer. (H) The efficacy of combined detection of seven autoantibodies in diagnosing lung cancer.

Comparison of efficacy of seven autoantibodies alone and in combination in the diagnosis of NSCLC.

3.4. Sensitivity & specificity of seven autoantibodies in diagnosing different stages of NSCLC in different disease groups

The overall sensitivity and specificity of the combined detection of seven autoantibodies for diagnosing NSCLC were 60.1% and 83.0%, respectively. Among them, the sensitivity for diagnosing stage I patients was 62.5%, stage II patients was 60.6%, stage III patients was 50.0% and stage IV patients was 64.3% (Figure 4). The specificity of the seven autoantibodies tested in combination was 87.0% in the group of lung benign diseases, 72.5% in the group of other malignant solid tumors and 72.5% in the group of autoimmune diseases (Figure 4).

Figure 4.

Sensitivity and specificity of seven autoantibodies combined detection for diagnosing lung cancer in different disease groups. (A) Sensitivity of combined detection of seven autoantibodies for diagnosing NSCLC in different stages. (B) The specificity of combined detection of seven autoantibodies in different disease groups. (C) Comparison of sensitivity between combined detection of seven autoantibodies and three traditional tumor markers for the diagnosis of lung adenocarcinoma. (D) Comparison of sensitivity between combined detection of seven autoantibodies and three traditional tumor markers for the diagnosis of lung squamous cell carcinoma.

3.5. Comparison of sensitivity between seven autoantibodies & three traditional tumor markers in the diagnosis of NSCLC

The sensitivity of the combined detection of seven autoantibodies in diagnosing adenocarcinoma was 57.3%, significantly higher than CEA (7.8%), NSE (9.5%) and CYFRA21-1 (17.2%), and the difference was statistically significant (p < 0.01, Figure 4). The sensitivity of combined detection for diagnosing squamous cell carcinoma was 64.3%, significantly higher than CEA (5.5%), NSE (8.0%) and CYFRA21-1 (20.1), with statistical significance (p < 0.01, Figure 4).

4. Discussion

Currently, the commonly used methods for clinically assisted diagnosis of NSCLC mainly include chest imaging (such as chest CT and PET-CT) and blood-derived tumor markers (such as CEA, NSE and CYFRA21-1)[16]. Although chest imaging has high sensitivity, it is prone to false positives due to its inability to effectively distinguish between benign and malignant lesions and even repeated examination increases radiation risk, leading to the risk of secondary primary tumors. Therefore, traditional tumor markers cannot meet the current clinical diagnostic requirements due to their low sensitivity and specificity. Based on the current clinical needs and considering the cost of patient care, it is significant to develop novel and economical tumor biomarkers that can be used for lung cancer screening and early adjuvant diagnosis is currently a research hotspot in this field [17].

Cancer molecular biomarkers are substances or indicators that can objectively measure and evaluate normal biological processes, cancer treatment processes or treatment prognostic processes [18]. According to different application scenarios and usage purposes, cancer biomarkers can be classified into predictive, prognostic and diagnostic types. Nucleic acids, proteins, enzymes, small molecules, or cancer cells can all serve as cancer biomarkers. In clinical practice, we've noticed that, tumor-related autoantibodies are specific immune response products produced by the body's immune system against tumor cells, with high sensitivity and high specificity [19]. Due to the signal amplification function of the immune system, these autoantibodies can reach the lower limit of detection before traditional tumor biomarkers [20]. Previous studies have suggested that lung cancer-related autoantibodies can detect lung cancer-related signals 5 years earlier than imaging studies [21]. Based on existing clinical issues and previous research results, in order to further verify the efficacy of tumor-related autoantibodies in assisting the diagnosis of NSCLC, this study first evaluated the difference in the expression level of each lung cancer-related autoantibody in different groups and its efficacy in diagnosing NSCLC. The results showed that the concentrations of CAGE, GBU4-5, MAGEA1, P53, PGP9.5 and SOX2 in NSCLC group were significantly higher than those in lung benign disease group, other malignant solid tumor group, autoimmune disease group and healthy body group, while the concentration of GAGE7 in lung cancer group was significantly higher than that in healthy examination group. However, there was no significant difference between the concentration level and those of lung benign disease group, other malignant solid tumor group and autoimmune disease group. The AUC of CAGE, GAGE7, GBU4-5, MAGEA1, P53, PGP9.5 and SOX2 in the diagnosis of NSCLC were 0.651, 0.507, 0.644, 0.588, 0.609, 0.561 and 0.590, respectively.

Among these abnormally expressed proteins, P53 protein is produced by mutations in the p53 gene, which leads to abnormal protein production. It binds to heat shock proteins to form a complex, which acts as an antigen to induce an autoimmune response, resulting in the production of p53 antibodies [22]. The p53 antibody can be detected in approximately 30% -40% of various malignant tumors and has been applied in the diagnosis of lung cancer. The inactivation of p53 protein caused by p53 gene mutation is an important step in the development of cancer. P53 autoantibodies are typically produced against mutated p53 gene products. PGP9.5 is a member of the ubiquitin peptide carboxyterminal hydrolase family, which functions to intensify the ubiquitination of cell cycle proteins [23]. Ubiquitination is associated with the disordered growth of undifferentiated somatic cells, thereby affecting cell division and death. PGP9.5 is highly expressed in non-small cell lung cancer. PGP9.5 is a ubiquitin hydrolase expressed in neural tissue and is highly expressed in primary lung cancer and lung cancer cell lines. The SOX family proteins are considered tumor associated antigens associated with lung cancer. SOX2 is a transcription factor that induces tumor cancer signals EGFR and BCL2L1, promoting the proliferation and survival of lung cancer cells [24]. GAGE 7 belongs to tumor/testicular antigen, expressed only in malignant tumors and testicular tissues, and has anti apoptotic activity [25]. GBU4-5 belongs to ATP binding RNA helicase and plays an important role in the process of carcinogenesis. It also has tumor specificity and immunogenicity. MAGE A1 belongs to the human melanoma antigen family, expressed only in malignant tumors and testicular tissues and may be associated with gene transcriptional regulation and cancer transformation or progression [26]. CAGE belongs to the DEAD box helicase family and its expression level is related to the cell cycle. It activates ERK and p38 proteins in cancer cells and increases tumor cell proliferation. According to our research, these results suggest that the diagnostic efficacy of single lung cancer-related autoantibodies is low and may not meet the needs of clinical auxiliary diagnosis.

Subsequently, this study evaluated the efficacy of the combined detection of seven lung cancer-related autoantibodies in the assisted diagnosis of NSCLC, and analyzed their sensitivity and specificity in the diagnosis of NSCLC in different clinical stages and pathological types, and compared their sensitivity differences with traditional tumor markers in the assisted diagnosis of NSCLC. It was found that the AUC of the combined test was 0.791, the overall sensitivity of diagnosis was 60.1% and the specificity was 83.0%. The diagnostic sensitivity of joint testing for different stages and pathological types of NSCLC was relatively consistent. More importantly, the sensitivity of combined detection in the diagnosis of adenocarcinoma and squamous cell carcinoma was significantly superior to CEA, NSE and CYFRA21-1. These results are consistent with those reported in previous studies. In 2014, a foreign research team found that seven autoantibodies (P53, CAGE, NY–ESO–1, SOX2, GBU4-5, MAGE A4 and HuD) had a sensitivity of 37% and a specificity of 91% in the diagnosis of lung cancer through a study of 1600 high-risk patients with lung cancer [27]. On this basis, the domestic research team developed seven kinds of lung cancer autoantibodies (CAGE, GAGE7, GBU4-5, MAGEA1, P53, PGP9.5 and SOX2) that were more suitable for the Chinese population according to the genomic characteristics of the Chinese lung cancer population. 2308 patients were included and analyzed through cooperation with six hospitals in China. The overall sensitivity and specificity of the seven autoantibodies were 61% and 90% respectively. The sensitivity of different stages and pathological types of lung cancer was consistent [28]. It is worth noting that both studies have shown that the combination of seven autoantibodies and LDCT significantly improved the diagnostic accuracy of pulmonary nodules.

5. Conclusion

In summary, the results of this study indicate that the combined detection of seven lung cancer related autoantibodies has high sensitivity and specificity in assisting the diagnosis of NSCLC, and the sensitivity for diagnosing different stages and pathological types of NSCLC is relatively consistent. More importantly, the combined detection of seven autoantibodies for the diagnosis of NSCLC is more effective than traditional tumor markers, and therefore has certain clinical promotion and application value.

However, there are also some shortcomings in this study: firstly, the number of final cases included in the analysis of other control groups is relatively small, and there may be bias in the evaluation of specific results; Secondly, this study did not evaluate the efficacy of its combined diagnosis with LDCT. Future research can establish a new multimodal and multi parameter auxiliary diagnostic model by increasing the number of study cases and disease spectra, and combining chest imaging, artificial intelligence, big data algorithms and other factors to verify the results of this study. This will provide more accurate auxiliary diagnostic information for clinical doctors and guide subsequent clinical intervention measures for patients.

Funding Statement

This work was supported by Hangzhou health science and technology project (No. B20210500).

Financial disclosure

This work was supported by Hangzhou health science and technology project (No. B20210500). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, stock ownership or options and expert testimony.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

The authors state that they have obtained appropriate institutional review board approval (the Ethics Committee of the First People's Hospital of Fuyang District, Hangzhou, and the ethics number is 2021-010) and/or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.