Increased risk of subsequent primary lung cancer among female hormone-related cancer patients: A meta-analysis based on over four million cases.

BACKGROUND: The incidence rate of lung cancer in women has significantly increased over the past decade, and previous evidence has indicated a significant relationship between the elevated levels of sex hormones and the risk of lung cancer. Therefore, we hypothesized that female hormone-related cancer (FHRC) patients, including breast, endometrial, cervical, and ovarian cancer patients, may experience a higher risk of developing subsequent lung cancer. This meta-analysis aimed to identify the risk of lung cancer among FHRC patients compared to the general population. METHODS: The PubMed, Web of Science, EMBASE, Cochrane Library, and CNKI databases were searched up to May 11, 2022. Standardized incidence ratios (SIRs) with 95% confidence intervals (CIs) were used to identify the risk of subsequent lung cancer after FHRC. Subgroup analyses based on the follow-up time and tumor type were also conducted. RESULTS: A total of 58 retrospective cohort studies involving 4,360,723 FHRC participants were included. The pooled results demonstrated that FHRC patients had a significantly increased risk of developing subsequent primary lung cancer (SIR = 1.61, 95% CI: 1.48-1.76, P <0.001). Subgroup analysis revealed an obvious trend of increasing lung cancer risk over time (SIRs for <5 years, ≥5 years, ≥10 years, ≥20 years, and ≥30 years after FHRC: 1.32, 1.59, 1.57, 1.68, and 1.95, respectively). In addition, subgroup analysis stratified by tumor type indicated an increased risk of developing subsequent lung cancer after breast (SIR = 1.25, P <0.001), endometrial (SIR = 1.40, P = 0.019), cervical (SIR = 2.56, P <0.001), and ovarian cancer (SIR = 1.50, P = 0.010). CONCLUSION: FHRC patients are more likely to develop lung cancer than the general population. Furthermore, the increased risk of subsequent primary lung cancer is more obvious with a longer survival time and is observed in all types of hormone-related cancer. REGISTRATION: International Platform of Registered Systematic Review and Meta-analysis Protocols: No. INPLASY202270044; https://inplasy.com/.

Impact of Pulmonary microbiota on lung cancer treatment-related pneumonia.

Background: The use of immunotherapy is progressively expanding for the treatment of lung cancer, either alone or in combination with radiotherapy. However, treatment-related adverse events, especially pneumonia, significantly limit the drug's effectiveness in treating lung cancer. The occurrence of lung cancer, immunotherapy, and pulmonary radiotherapy can all contribute to the imbalance in the pulmonary microbiota, rendering the lungs more susceptible to inflammatory reactions. Methods: Mouse models of lung transplantation tumor were treated with either PD-1 monoclonal antibody or radiotherapy alone, or in combination. The differences in lung inflammation among the different treatment groups were regularly observed by micro-CT. Further, bronchoalveolar lavage fluid was extracted for macrogenomic and cytokine detection. The transcriptional genome of tumor-filled lung tissue was also sequenced. Results: When treated with a combination of PD-1 and radiotherapy, the CT scans showed more severe pulmonary inflammation. However, with the addition of continuously administered antibiotics, no exacerbation of pneumonia signs was observed. Moreover, the differential gene expression and cytokine profiles in the combination treatment group differed from those in the PD-1 monotherapy group and the radiotherapy monotherapy group. This discrepancy does not seem to be a straightforward superimposition of radiation-induced pneumonia and immune-related pneumonia. Further exploration of changes in pulmonary microbiota revealed specific bacterial interactions with DEGs and cytokines. Conclusions: The underlying causes of this susceptibility are intricate and may be associated with the complexity of pulmonary microbiota imbalance, along with fluctuations in the abundance of specific microbiota species.

Medical Resource Management in Emergency Hierarchical Diagnosis and Treatment Systems: A Research Framework.

The occurrence of major public health crises, like the COVID-19 epidemic, present significant challenges to healthcare systems and the management of emergency medical resources worldwide. This study, by examining the practices of emergency medical resource management in select countries during the COVID-19 epidemic, and reviewing the relevant literature, finds that emergency hierarchical diagnosis and treatment systems (EHDTSs) play a crucial role in managing emergency resources effectively. To address key issues of emergency resource management in EHDTSs, we examine the features of EHDTSs and develop a research framework for emergency resource management in EHDTSs, especially focusing on the management of emergency medical personnel and medical supplies during evolving epidemics. The research framework identifies key issues of emergency medical resource management in EHDTSs, including the sharing and scheduling of emergency medical supplies, the establishment and sharing of emergency medical supply warehouses, and the integrated dispatch of emergency medical personnel. The proposed framework not only offers insights for future research but also can facilitate better emergency medical resource management in EHDTSs during major public health emergencies.

Outcomes of clinical decision support systems in real-world perioperative care: A systematic review and meta-analysis.

BACKGROUND: Although clinical decision support systems (CDSS) have been developed to enhance the quality and efficiency of surgeries, little is known regarding the practical effects in real-world perioperative care. OBJECTIVE: To systematically review and meta-analyze the current impact of CDSS on various aspects of perioperative care, providing evidence support for future research on CDSS development and clinical implementation. METHODS: This systematic review and meta-analysis followed the Cochrane Handbook and PRISMA statement guidelines, searching databases up to February 2, 2024, including MEDLINE, PubMed, Embase, Cochrane, and Web of Science. It included studies on the effectiveness of CDSS in assisting perioperative decision-making, involving anaesthesiologists, doctors, or surgical patients, and reporting at least one outcome such as complications, mortality, length of stay, compliance, or cost. RESULTS: Forty studies met inclusion criteria, analyzing outcomes from 408,357 participants, predominantly in developed countries. Most perioperative CDSS use was associated with improved guideline adherence, decreased medication errors, and some improvements in patient safety measures such as reduced postoperative nausea and vomiting and myocardial injury. However, reported results varied widely, and no significant improvement in postoperative mortality was observed. CONCLUSION: The preliminary findings of this review offer an overview of the potential use of CDSS in real-world perioperative situations to enhance patient and anaesthesiologist outcomes, but further researches with broader outcome dimensions, involving more stakeholders, and with longer follow-up periods are warranted for the critical evaluation of CDSS and then in better facilitate clinical adoption.

Selenite improves growth by modulating phytohormone pathways and reprogramming primary and secondary metabolism in tomato plants.

Selenium (Se) is an essential micronutrient in organisms that has a significant impact on physiological activity and gene expression in plants, thereby affecting growth and development. Humans and animals acquire Se from plants. Tomato (Solanum lycopersicum L.) is an important vegetable crop worldwide. Improving the Se nutrient level not only is beneficial for growth, development and stress resistance in tomato plants but also contributes to improving human health. However, the molecular basis of Se-mediated tomato plant growth has not been fully elucidated. In this study, using physiological and transcriptomic analyses, we investigated the effects of a low dosage of selenite [Se(Ⅳ)] on tomato seedling growth. Se(IV) enhanced the photosynthetic efficiency and increased the accumulation of soluble sugars, dry matter and organic matter, thereby promoting tomato plant growth. Transcriptome analysis revealed that Se(IV) reprogrammed primary and secondary metabolic pathways, thus modulating plant growth. Se(IV) also increased the concentrations of auxin, jasmonic acid and salicylic acid in leaves and the concentration of cytokinin in roots, thus altering phytohormone signaling pathways and affecting plant growth and stress resistance in tomato plants. Furthermore, exogenous Se(IV) alters the expression of genes involved in flavonoid biosynthesis, thereby modulating plant growth and development in tomato plants. Taken together, these findings provide important insights into the regulatory mechanisms of low-dose Se(IV) on tomato growth and contribute to the breeding of Se-accumulating tomato cultivars.

Integrating muti-omics data to identify tissue-specific DNA methylation biomarkers for cancer risk.

The relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging resources from the Genotype-Tissue Expression consortium, here we develop genetic models to predict DNA methylation at CpG sites across the genome for seven tissues and apply these models to genome-wide association study data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-corrected P < 0.05, we identify 4248 CpGs that are significantly associated with cancer risk, of which 95.4% (4052) are specific to a particular cancer type. Notably, 92 CpGs within 55 putative novel loci retain significant associations with cancer risk after conditioning on proximal signals identified by genome-wide association studies. Integrative multi-omics analyses reveal 854 CpG-gene-cancer trios, suggesting that DNA methylation at 309 distinct CpGs might influence cancer risk through regulating the expression of 205 unique cis-genes. These findings substantially advance our understanding of the interplay between genetics, epigenetics, and gene expression in cancer etiology.

Current status and progress of PD-L1 detection: guiding immunotherapy for non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths and represents a substantial disease burden worldwide. Immune checkpoint inhibitors combined with chemotherapy are the standard first-line therapy for advanced NSCLC without driver mutations. Programmed death-ligand 1 (PD-L1) is currently the only approved immunotherapy marker. PD-L1 detection methods are diverse and have developed rapidly in recent years, such as improved immunohistochemical detection methods, the application of liquid biopsy in PD-L1 detection, genetic testing, radionuclide imaging, and the use of machine learning methods to construct PD-L1 prediction models. This review focuses on the detection methods and challenges of PD-L1 from different sources, and discusses the influencing factors of PD-L1 detection and the value of combined biomarkers. Provide support for clinical screening of immunotherapy-advantage groups and formulation of personalized treatment decisions.

PPCRKB: a risk factor knowledge base of postoperative pulmonary complications.

Postoperative pulmonary complications (PPCs) are highly heterogeneous disorders with diverse risk factors frequently occurring after surgical interventions, resulting in significant financial burdens, prolonged hospitalization and elevated mortality rates. Despite the existence of multiple studies on PPCs, a comprehensive knowledge base that can effectively integrate and visualize the diverse risk factors associated with PPCs is currently lacking. This study aims to develop an online knowledge platform on risk factors for PPCs (Postoperative Pulmonary Complications Risk Factor Knowledge Base, PPCRKB) that categorizes and presents the risk and protective factors associated with PPCs, as well as to facilitate the development of individualized prevention and management strategies for PPCs based on the needs of each investigator. The PPCRKB is a novel knowledge base that encompasses all investigated potential risk factors linked to PPCs, offering users a web-based platform to access these risk factors. The PPCRKB contains 2673 entries, 915 risk factors that have been categorized into 11 distinct groups. These categories include habit and behavior, surgical factors, anesthetic factors, auxiliary examination, environmental factors, clinical status, medicines and treatment, demographic characteristics, psychosocial factors, genetic factors and miscellaneous factors. The PPCRKB holds significant value for PPC research. The inclusion of both quantitative and qualitative data in the PPCRKB enhances the ability to uncover new insights and solutions related to PPCs. It could provide clinicians with a more comprehensive perspective on research related to PPCs in future. Database URL: http://sysbio.org.cn/PPCs.

A multimodal integration pipeline for accurate diagnosis, pathogen identification, and prognosis prediction of pulmonary infections.

Pulmonary infections pose formidable challenges in clinical settings with high mortality rates across all age groups worldwide. Accurate diagnosis and early intervention are crucial to improve patient outcomes. Artificial intelligence (AI) has the capability to mine imaging features specific to different pathogens and fuse multimodal features to reach a synergistic diagnosis, enabling more precise investigation and individualized clinical management. In this study, we successfully developed a multimodal integration (MMI) pipeline to differentiate among bacterial, fungal, and viral pneumonia and pulmonary tuberculosis based on a real-world dataset of 24,107 patients. The area under the curve (AUC) of the MMI system comprising clinical text and computed tomography (CT) image scans yielded 0.910 (95% confidence interval [CI]: 0.904-0.916) and 0.887 (95% CI: 0.867-0.909) in the internal and external testing datasets respectively, which were comparable to those of experienced physicians. Furthermore, the MMI system was utilized to rapidly differentiate between viral subtypes with a mean AUC of 0.822 (95% CI: 0.805-0.837) and bacterial subtypes with a mean AUC of 0.803 (95% CI: 0.775-0.830). Here, the MMI system harbors the potential to guide tailored medication recommendations, thus mitigating the risk of antibiotic misuse. Additionally, the integration of multimodal factors in the AI-driven system also provided an evident advantage in predicting risks of developing critical illness, contributing to more informed clinical decision-making. To revolutionize medical care, embracing multimodal AI tools in pulmonary infections will pave the way to further facilitate early intervention and precise management in the foreseeable future.

Genomic investigation of bone tuberculosis highlighted the role of subclinical pulmonary tuberculosis in transmission.

BACKGROUND: Extrapulmonary tuberculosis (EPTB) without symptomatic pulmonary involvement has been thought to be non-transmissible, but EPTB with asymptomatic pulmonary tuberculosis (PTB) could transmit tuberculosis (TB). Genomic investigation of Mycobacterium tuberculosis (Mtb) isolates from EPTB may provide insight into its epidemiological role in TB transmission. METHODS: Between January 2017 and May 2020, 107 Mtb isolates were obtained from surgical drainage of bone TB patients at the Beijing Chest Hospital, and 218 Mtb strains were isolated from PTB cases. These 325 Mtb isolates were whole-genome sequenced to reconstruct a phylogenetic tree, identify transmission clusters, and infer transmission links using a Bayesian approach. Possible subclinical PTB in the bone TB patients was investigated with chest imaging by two independent experts. RESULTS: Among 107 bone TB patients, 10 were in genomic clusters (≤12 SNPs). Phylogenetic analysis suggested that three bone TB patients transmitted the infection to secondary cases, supported by epidemiological investigations. Pulmonary imaging of 44 bone TB patients revealed that 79.5 % (35/44) had radiological abnormalities suggestive of subclinical PTB. CONCLUSIONS: This study provides genomic evidence that bone TB patients without clinically diagnosed PTB can be sources of TB transmission, underscoring the importance of screening for subclinical, transmissible PTB among EPTB cases.

Physiological and molecular responses of strawberry plants to Cd stress.

Cadmium (Cd), a toxic metal element, can be absorbed by plants via divalent metal ion transporters, thereby retarding plant growth and posing a threat to human health. Strawberries are popular and economically valuable berry species that are sensitive to soil pollutants, especially Cd. However, the mechanisms underlying Cd stress responses in strawberry plants remain largely unclear. Here, we investigated the physiological and molecular basis of Cd stress responses in strawberry plants using the diploid strawberry 'Yellow Wonder' as a material. The results indicated that Cd stress induced oxidative damage, repressed photosynthetic efficiency, and interfered with the accumulation and redistribution of trace elements. Furthermore, Cd stress reduced the concentrations of indoleacetic acid, trans-zeatin riboside and gibberellic acid while increasing the concentration of abscisic acid, thus altering the phytohormone signaling pathway in strawberry plants. Cd stress also inhibited the expression of genes involved in nitrogen uptake and assimilation while promoting the energy supply for plant survival under Cd toxicity. Moreover, the flavonoid biosynthesis pathway was induced, and the anthocyanin concentration increased, thereby improving the free radical scavenging capacity of strawberry plants under Cd toxicity. Additionally, we identified several transcription factors and functional genes as hub genes based on a weighted gene coexpression network analysis. These results collectively provide a theoretical foundation for strawberry breeding and ensuring agriculture and food safety.

Investigating causal associations between pneumonia and lung cancer using a bidirectional mendelian randomization framework.

BACKGROUND: Pneumonia and lung cancer are both major respiratory diseases, and observational studies have explored the association between their susceptibility. However, due to the presence of potential confounders and reverse causality, the comprehensive causal relationships between pneumonia and lung cancer require further exploration. METHODS: Genome-wide association study (GWAS) summary-level data were obtained from the hitherto latest FinnGen database, COVID-19 Host Genetics Initiative resource, and International Lung Cancer Consortium. We implemented a bidirectional Mendelian randomization (MR) framework to evaluate the causal relationships between several specific types of pneumonia and lung cancer. The causal estimates were mainly calculated by inverse-variance weighted (IVW) approach. Additionally, sensitivity analyses were also conducted to validate the robustness of the causalty. RESULTS: In the MR analyses, overall pneumonia demonstrated a suggestive but modest association with overall lung cancer risk (Odds ratio [OR]: 1.21, 95% confidence interval [CI]: 1.01 - 1.44, P = 0.037). The correlations between specific pneumonia types and overall lung cancer were not as significant, including bacterial pneumonia (OR: 1.07, 95% CI: 0.91 - 1.26, P = 0.386), viral pneumonia (OR: 1.00, 95% CI: 0.95 - 1.06, P = 0.891), asthma-related pneumonia (OR: 1.18, 95% CI: 0.92 - 1.52, P = 0.181), and COVID-19 (OR: 1.01, 95% CI: 0.78 - 1.30, P = 0.952). Reversely, with lung cancer as the exposure, we observed that overall lung cancer had statistically crucial associations with bacterial pneumonia (OR: 1.08, 95% CI: 1.03 - 1.13, P = 0.001) and viral pneumonia (OR: 1.09, 95% CI: 1.01 - 1.19, P = 0.037). Sensitivity analysis also confirmed the robustness of these findings. CONCLUSION: This study has presented a systematic investigation into the causal relationships between pneumonia and lung cancer subtypes. Further prospective study is warranted to verify these findings.

The combination of tumor mutational burden and T-cell receptor repertoire predicts the response to immunotherapy in patients with advanced non-small cell lung cancer.

Tumor mutational burden (TMB) and T-cell receptor (TCR) might predict the response to immunotherapy in patients with non-small cell lung cancer (NSCLC). However, the predictive value of the combination of TMB and TCR was not clear. Targeted DNA and TCR sequencing were performed on tumor biopsy specimens. We combined TMB and TCR diversity into a TMB-and-TCR (TMR) score using logistic regression. In total, 38 patients with advanced NSCLC were divided into a discovery set (n = 17) and validation set (n = 21). A higher TMR score was associated with better response and longer progression-free survival to immunotherapy in both the discovery set and validation set. The performance of TMR score was confirmed in the two external validation cohorts of 225 NSCLC patients and 306 NSCLC patients. Tumors with higher TMR scores were more likely to combine with LRP1B gene mutation (p = 0.027) and top 1% CDR3 sequences (p = 0.001). Furthermore, LRP1B allele frequency was negatively correlated with the top 1% CDR3 sequences (r = -0.55, p = 0.033) and positively correlated with tumor shrinkage (r = 0.68, p = 0.007). The TMR score could serve as a potential predictive biomarker for the response to immunotherapy in advanced NSCLC.

Excess multi-cause mortality linked to influenza virus infection in China, 2012-2021: a population-based study.

Objectives: The aim of this study is to estimate the excess mortality burden of influenza virus infection in China from 2012 to 2021, with a concurrent analysis of its associated disease manifestations. Methods: Laboratory surveillance data on influenza, relevant population demographics, and mortality records, including cause of death data in China, spanning the years 2012 to 2021, were incorporated into a comprehensive analysis. A negative binomial regression model was utilized to calculate the excess mortality rate associated with influenza, taking into consideration factors such as year, subtype, and cause of death. Results: There was no evidence to indicate a correlation between malignant neoplasms and any subtype of influenza, despite the examination of the effect of influenza on the mortality burden of eight diseases. A total of 327,520 samples testing positive for influenza virus were isolated between 2012 and 2021, with a significant decrease in the positivity rate observed during the periods of 2012-2013 and 2019-2020. China experienced an average annual influenza-associated excess deaths of 201721.78 and an average annual excess mortality rate of 14.53 per 100,000 people during the research period. Among the causes of mortality that were examined, respiratory and circulatory diseases (R&C) accounted for the most significant proportion (58.50%). Fatalities attributed to respiratory and circulatory diseases exhibited discernible temporal patterns, whereas deaths attributable to other causes were dispersed over the course of the year. Conclusion: Theoretically, the contribution of these disease types to excess influenza-related fatalities can serve as a foundation for early warning and targeted influenza surveillance. Additionally, it is possible to assess the costs of prevention and control measures and the public health repercussions of epidemics with greater precision.

[Comparative research on the relationship between body mass index and physical fitness index among the Uygur, Kazakh and Han ethnic college students].

OBJECTIVE: To understand the nutritional status and physical fitness of the Uygur, Kazak and Han ethnic college students, and to investigate the nonlinear relationship between BMI and physical fitness indexes in different ethnic groups. METHODS: A total of 3 600 Uygur, Kazakh and Han students majoring in non-sports in a university in Xinjiang Uygur Autonomous Region in 2021 were selected by stratified random cluster sampling method. Height, weight, vital capacity, 50 m running, standing long jump, sit-and-reach, sit-up/pull-up and endurance running were measured. Body mass index (BMI), standardized Z score of each test score and physical fitness index (PFI) were calculated. The data were analyzed by Chi-square test, single factor analysis of variance, and nonlinear quadratic regression. RESULTS: Prevalences of overweight (16.00%) and obesity (8.08%) of the Han college students were significantly higher than those of the Uygur (11.83% and 4.08%) and Kazakh (13.58% and 4.58%). Prevalence of low weight in the Uygur (11.92%) was the highest, and the lowest was the Kazakh (9.75%). There were significant differences in the prevalence of BMI classification among the three ethnic groups boys and girls (all P < 0.05). There were significant differences in PFI among college students of different BMI levels in the Uygur, Kazakh and Han ethnic college students (all P < 0.05), and the PFI of normal weight group was higher than the other weight groups in general, and the overweight group was higher than the obese group, but some ethnics showed the highest PFI in the low weight group. The non-linear quadratic regression results showed that the curves of the Uygur boys and girls and the Kazakh boys were inverted "J" shaped, and the PFI increased and then decreased with the increase of BMI, while the rest of the curves were arc-shaped, and the PFI decreased with the increase of BMI. CONCLUSION: Overweight obesity in the Uygur, Kazakh and Han ethnic college students brings about a decrease in physical fitness, but Kazakh low weight male and female and Han low weight grils have better physical fitness than the normal weight groups. Focusing on improving the physical fitness of Uygur low-weight and high-weight boys and Han high-weight girls could effectively reduce the differences in physical fitness of college students in different weight levels and ethnic groups.

Conversion therapy of a giant hepatocellular carcinoma with portal vein thrombus and inferior vena cava thrombus: A case report and review of literature.

BACKGROUND: The prognosis of hepatocellular carcinoma (HCC) combined with portal and hepatic vein cancerous thrombosis is poor, for unresectable patients the combination of targeted therapy and immune therapy was the first-line recommended treatment for advanced HCC, with a median survival time of only about 2.7-6 months. In this case report, we present the case of a patient with portal and hepatic vein cancerous thrombosis who achieved pathologic complete response after conversion therapy. CASE SUMMARY: In our center, a patient with giant HCC combined with portal vein tumor thrombus and hepatic vein tumor thrombus was treated with transcatheter arterial chemoembolization (TACE), radiotherapy, targeted therapy and immunotherapy, and was continuously given icaritin soft capsules for oral regulation. After 7 months of conversion therapy, the patient's tumor shrank and the tumor thrombus subsided significantly. The pathology of surgical resection was in complete remission, and there was no progression in the postoperative follow-up for 7 months, which provided a basis for the future strategy of combined conversion therapy. CONCLUSION: In this case, atezolizumab, bevacizumab, icaritin soft capsules combined with radiotherapy and TACE had a good effect. For patients with hepatocellular carcinoma combined with hepatic vein/inferior vena cava tumor thrombus, adopting a high-intensity, multimodal proactive strategy under the guidance of multidisciplinary team (MDT) is an important attempt to break through the current treatment dilemma.

Alkali Metal Pretreatment for Precise Na Doping and Voc Improvement in CIGS Thin-Film Solar Cells.

The pretreatment of the Cu(In,Ga)Se2 (CIGS) absorption layer using an alkali element can effectively improve the photoelectric conversion efficiency (PCE) of CIGS solar cells. Here, we propose using NaF layer pretreatment below the CIGS absorption layer deposited by a three-stage process. Sodium ions in NaF can effectively suppress the diffusion of Ga elements and form a steep gradient backscatter layer on the back of the CIGS absorption layer, thereby passivating solar cell defects, inhibiting carrier recombination, promoting carrier transmission and collection, improving open circuit voltage (VOC), short circuit current (Jsc), and filling factor (FF), and further improving the PCE.

Screening for lung cancer using thin-slice low-dose computed tomography in southwestern China: a population-based real-world study.

OBJECTIVES: Lung cancer is one of the most common malignant tumors threatening human life and health. At present, low-dose computed tomography (LDCT) screening for the high-risk population to achieve early diagnosis and treatment of lung cancer has become the first choice recommended by many authoritative international medical organizations. To further optimize the lung cancer screening method, we conducted a real-world study of LDCT lung cancer screening in a large sample of a healthy physical examination population, comparing differences in lung nodules and lung cancer detection between thin and thick-slice LDCT scanning. METHODS: A total of 29 296 subjects who underwent low-dose thick-slice CT scanning (5 mm thickness) from January 2015 to December 2015 and 28 058 subjects who underwent low-dose thin-slice CT scanning (1 mm thickness) from January 2018 to December 2018 in West China Hospital were included. The positive detection rate, detection rate of lung cancer, pathological stage of lung cancer, and mortality rate of lung cancer were analyzed and compared between the two groups. RESULTS: The positive rate of LDCT screening in the thin-slice scanning group was significantly higher than that in the thick-slice scanning group (20.1% vs. 14.4%, p < 0.001). In addition, the lung cancer detection rate in the thin-slice LDCT screening positive group was significantly higher than that in the thick-slice scanning group (78.0% vs. 52.9%, p < 0.001). CONCLUSIONS: The screening positive rate of low-dose thin-slice CT scanning is higher and more early-stage lung cancer (IA1 stage) can be detected in the screen-positive group.