Lung cancer - major changes in the American Joint Committee on Cancer eighth edition cancer staging manual

Clinical difference between solitary and multiple pulmonary adenocarcinoma nodules

OBJECTIVE

we compared and analyzed the imaging features, tumor markers, pathological immunohistochemistry, and lymph node metastasis rates of solitary and multiple lung adenocarcinoma to provide a valuable reference for clinical diagnosis and treatment.

METHODS

A retrospective analysis of 212 patients who underwent thoracic surgery in our hospital from 2022 to 2023, including 149 patients with a solitary lung adenocarcinoma nodule and 63 patients with multiple primary nodules. Via propensity score matching, the imaging features, tumor serological markers, pathological immunohistochemistry, and lymph node metastasis rates of the two groups were compared, and the differences in lymph node metastasis rates between solitary and multiple nodules were explored by binary logistic regression.

RESULTS

After propensity score matching, there were significant differences in the mean CT value (P = 0.001), Ki-67 expression (P < 0.001), PD-L1 expression (P = 0.002), and the lymph node metastasis rate (P = 0.030) between the two groups, but there were no significant differences in nodule type, imaging features, tumor serological marker levels, and the ALK-positive and SYN-positive rates. With lymph node metastasis as the dependent variable, solitary or multiple nodules as the categorical covariate, and the three variables were included as independent variables for binary logistic regression analysis. The probability of lymph node metastasis was 80.8% lower in patients with multiple primary lung adenocarcinoma nodules than in those with a solitary one (P = 0.042).

CONCLUSION

Multiple primary adenocarcinoma nodules exhibit milder biological behavior than solitary adenocarcinoma nodules and carry a lower risk of lymph node metastasis.

Peripheral blood markers predict prognosis and irAEs of stage IV driver gene-negative lung adenocarcinoma treated with ICIs

Objective

This study aims to evaluate the prognostic significance of peripheral blood biomarkers in relation to outcomes and immune-related adverse events (irAEs) among patients with stage IV driver gene-negative lung adenocarcinoma receiving treatment with immune checkpoint inhibitors (ICIs).

Methods

We conducted a retrospective analysis of clinicopathological data from 102 patients diagnosed with stage IV driver gene-negative lung adenocarcinoma who were treated with ICIs at the Fourth Hospital of Hebei Medical University between January 1, 2019, and December 31, 2023. We employed the Kaplan-Meier method to perform a univariate analysis of progression-free survival (PFS) and overall survival (OS), generated survival curves, and assessed differences in survival between groups using the log-rank test. The Cox regression model was utilized for multivariate analysis of PFS and OS. Additionally, we assessed the predictive value of peripheral blood markers for irAEs using logistic regression models.

Results

The 1-, 3-, and 5-year PFS rates for the cohort of 102 patients were recorded at 35.3%, 3.9%, and 0%, respectively; similarly, the OS rates at these time points were observed to be 66.7%, 8.8%, and 2.9%. Multivariate analysis identified that the prognostic nutritional index (PNI) and metastatic status served as independent prognostic factors influencing PFS outcomes in this patient population; furthermore, D-dimer levels, PNI, metastatic status, and the occurrence of irAEs emerged as independent prognostic indicators impacting OS rates among patients. Subsequent logistic regression analysis revealed that both platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) functioned as independent predictors of irAEs with statistical significance (P=0.032; P=0.02).

Conclusion

For patients with stage IV driver gene-negative lung adenocarcinoma undergoing ICI therapy, PNI and metastatic status can serve as initial predictors of PFS. Additionally, D-dimer levels, PNI, metastatic status, and the presence of irAEs can initially predict OS, aiding in the identification of populations that may benefit from ICI therapy in clinical practice. Furthermore, our findings indicate a need for heightened attention to PLR and LMR concerning the occurrence of irAEs.

Development of a PET-CT Based Radiomics Model for Preoperative Prediction of the Novel IASLC Grading and Prognosis in Patients with Clinical Stage I Pure Solid Invasive Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

To develop and validate a fluorine-18-fludeoxyglucose (18F-FDG) PET/CT-based radiomics nomogram for preoperative prediction of the International Association for the Study of Lung Cancer (IASLC) grading and recurrence-free survival (RFS) in patients with clinical stage I pure-solid invasive lung adenocarcinoma (LADC). MATERIALS AND METHODS: 418 patients with clinical stage I pure-solid invasive LADC who underwent preoperative 18F-FDG PET/CT examination were retrospectively enrolled. All patients were separated into the low-grade group (grade I and II; n=315) and the high-grade group (grade III; n=103) according to the IASLC grading system, and the cohort was randomly divided into a training set (n=292) and a testing set (n=126) at a ratio of 7:3. Radiomics features were extracted from CT and PET images in regions of the entire tumor. Multivariate analysis identified the independent predictors for IASLC grading and RFS. The Radscore, along with clinical and radiological features were combined to establish a predictive nomogram.

RESULTS

The ultimate Radiomics model, achieving AUCs of 0.838 and 0.768 in the training and testing sets. The multivariate logistic regression showed that higher maximum standard uptake value (SUVmax), cavity presence are the independent risk factors for IASLC grading. The integrated nomogram showed superior prediction performance than CT model (p=0.001) and PET model (p=0.028) in the training set. Furthermore, both pathological grade and preoperatively predictive IASLC grade derived by nomogram significantly stratified patients for RFS, with 5-year survival rates showing marked differences between low-grade and high-grade LADC (p<0.001).

CONCLUSION

The preoperative PET/CT-based radiomics nomogram represents a potential biomarker for predicting IASLC grade and RFS in patients with clinical stage I pure-solid invasive LADC.

Prognostic and clinicopathological significance of the new grading system for invasive pulmonary adenocarcinoma: A systematic review and meta-analysis

In 2020, the International Association for the Study of Lung Cancer (IASLC) introduced a new grading system for invasive pulmonary adenocarcinoma (IPA). This meta-analysis aimed to validate the prognostic utility of this grading system and identify relevant clinicopathological features. The PubMed, Embase, Web of Science, and Cochrane Library databases were searched for relevant studies published between January 1, 2020 and March 5, 2024. Hazard ratios (HRs) with corresponding 95 % confidence intervals (CIs) were pooled to evaluate the effect of IASLC grading on prognosis. Odds ratios with corresponding 95 % CIs were pooled to assess relevant clinicopathological features. Twenty-two studies comprising 12,515 patients with IPA were included. Regarding overall survival, grade 3 adenocarcinomas had a worse prognosis compared with grades 1-2 (HR: 2.26, 95 % CI: 1.79-2.85, P<0.001), grade 1 (HR: 4.75, 95 % CI: 2.61-8.66, P<0.001), or grade 2 (HR: 1.71, 95 % CI: 1.28-2.29, P<0.001). Considering recurrence-free survival, grade 3 tumors had a higher recurrence risk than grades 1-2 (HR: 1.92, 95 % CI: 1.53-2.41, P<0.001), grade 1 (HR: 4.43, 95 % CI: 2.91-6.73, P<0.001), or grade 2 (HR: 1.67, 95 % CI: 1.33-2.10, P<0.001). In the subgroup analysis of stage I patients, grade 3 tumors exhibited a similarly poor prognosis. In addition, grade 3 adenocarcinomas were associated with aggressive clinicopathological features. This study demonstrated that the IASLC grading system is a robust predictor of prognostic stratification in patients with IPA, and warrants further promotion and worldwide implementation.

Prognostic and predictive values of a multimodal nomogram incorporating tumor and peritumor morphology with immune status in resectable lung adenocarcinoma

BACKGROUND

Current prognostic and predictive biomarkers for lung adenocarcinoma (LUAD) predominantly rely on unimodal approaches, limiting their characterization ability. There is an urgent need for a comprehensive and accurate biomarker to guide individualized adjuvant therapy decisions.

METHODS

In this retrospective study, data from patients with resectable LUAD (stage I-III) were collected from two hospitals and a publicly available dataset, forming a training dataset (n=223), a validation dataset (n=95), a testing dataset (n=449), and the non-small cell lung cancer (NSCLC) Radiogenomics dataset (n=59). Tumor and peritumor scores were constructed from preoperative CT radiomics features (shape/intensity/texture). An immune score was derived from the density of tumor-infiltrating lymphocytes (TILs) within the cancer epithelium and stroma on hematoxylin and eosin-stained whole-slide images. A clinical score was constructed based on clinicopathological risk factors. A Cox regression model was employed to integrate these scores, thereby constructing a multimodal nomogram to predict disease-free survival (DFS). The adjuvant chemotherapy benefit rate was subsequently calculated based on this nomogram.

RESULTS

The multimodal nomogram outperformed each of the unimodal scores in predicting DFS, with a C-index of 0.769 (vs 0.634-0.731) in the training dataset, 0.730 (vs 0.548-0.713) in the validation dataset, and 0.751 (vs 0.660-0.692) in the testing dataset. It was independently associated with DFS after adjusting for other clinicopathological risk factors (training dataset: HR=3.02, p<0.001; validation dataset: HR=2.33, p<0.001; testing dataset: HR=2.03, p=0.001). The adjuvant chemotherapy benefit rate effectively distinguished between patients benefiting from adjuvant chemotherapy and those from observation alone (interaction p<0.001). Furthermore, the high-/low-risk groups defined by the multimodal nomogram provided refined stratification of candidates for adjuvant chemotherapy identified by current guidelines (p<0.001). Gene set enrichment analyses using the NSCLC Radiogenomics dataset revealed associations between tumor/peritumor scores and pathways involved in epithelial-mesenchymal transition, angiogenesis, IL6-JAK-STAT3 signaling, and reactive oxidative species.

CONCLUSION

The multimodal nomogram, which incorporates tumor and peritumor morphology with anti-tumor immune response, provides superior prognostic accuracy compared with unimodal scores. Its defined adjuvant chemotherapy benefit rates can inform individualized adjuvant therapy decisions.

Validation of the 9th edition of the TNM staging system for limited-stage small cell lung cancer after Resection: A multicenter study

OBJECTIVES

The 9th edition of the tumor-node-metastasis (TNM) staging system for lung cancer was proposed at the 2023 World Conference on Lung Cancer in Singapore. This study aimed to externally validate and compare the latest staging of small-cell lung cancer (SCLC).

METHODS

Four hundred and eight patients with limited-stage SCLC were collected after lung resection from four centers. Survival curves by TNM stages were drawn using the Kaplan-Meier method and further compared by the Log-rank test. The Cox regression, receiver operating characteristics curves, area under the curve (AUC), Akaike information criterion (AIC), Bayesian information criterion (BIC), and Concordance index (C-index) were used in this study.

RESULTS

In comparing IA vs. IIB, IIA vs. IIB, IIA vs. IIIA, IIA vs. IIIB, and IIIA vs. IIIB, the 9th edition had a better distinguishing ability than the eighth staging system (all p < 0.05). Besides, the 9th edition TNM staging had better predictive power and accuracy for the overall survival (OS) of SCLC patients over the 8th edition (AUC of 3-year OS: 0.680 vs. o.668; AIC: 4425.25 vs. 4444.52; BIC: 4493.44 vs. 4512.71; C-index: 0.637 [0.04] vs. 0.629 [0.039], p < 0.001).

CONCLUSIONS

Our external validation demonstrates that the ninth edition of pathological TNM staging for limited-stage SCLC is reasonable and valid based on a multicenter study. The ninth edition has better prognostic accuracy than the eighth edition.

Comparison of Wedge Resection and Anatomical Lung Resection in Elderly Patients With Early-Stage Nonsmall Cell Lung Cancer With Visceral Pleural Invasion: A Population-Based Study

BACKGROUND

As the global population ages, the prevalence of early-stage nonsmall cell lung cancer (NSCLC) among octogenarians is rising. This demographic frequently presents with comorbid conditions, diminished cardiopulmonary function, and increased frailty, which elevate the risks associated with standard treatments. While lobectomy combined with lymph node dissection is still considered the gold standard for managing NSCLC, octogenarians are at significantly higher risk of perioperative mortality. Although wedge resection has been suggested as a less invasive option, previous research has insufficiently explored the influence of visceral pleural invasion (VPI) on postoperative outcomes. This study seeks to evaluate whether wedge resection can provide survival outcomes equivalent to those of anatomical resection in this high-risk population.

METHODS

We conducted a retrospective analysis using SEER data from 2010 to 2019, focusing on octogenarians diagnosed with stage I NSCLC and VPI. Propensity score matching, Kaplan-Meier survival analysis, log-rank testing, and Cox multivariate regression were employed to evaluate and compare the outcomes associated with two different surgical techniques.

RESULTS

We identified 523 octogenarians with stage I NSCLC and VPI, from a cohort of 1587 patients. In this study cohort, 372 (71.1%) patients received anatomical resection, while 151 (28.9%) patients underwent wedge resection. Following multivariable adjustment and propensity score matching, there were no statistically significant differences in lung cancer-specific survival (CSS; HR 0.99, 95% CI: 0.57-1.73) or overall survival (OS; HR 1.02, 95% CI: 0.68-1.53) observed between the two surgical groups. Additionally, multivariate Cox regression analysis indicated that the choice of surgical approach was not an independent prognostic factor for either CSS (HR 1.29, 95% CI: 0.62-2.69) or OS (HR 1.50, 95% CI: 0.68-1.62).

CONCLUSIONS

This study demonstrates that wedge resection is a viable surgical option for octogenarians with stage I NSCLC and VPI. Notably, the addition of lymph node dissection to wedge resection significantly enhances survival outcomes compared to wedge resection performed without lymph node dissection.

Nicotinamide N-methyltransferase negatively regulates metastasis-promoting property of cancer-associated fibroblasts in lung adenocarcinoma

BACKGROUND

Recurrence and metastasis remain significant challenges in lung adenocarcinoma (LUAD) after radical resection. The mechanisms behind the recurrence and metastasis of LUAD remain elusive, and deregulated cellular metabolism is suspected to play a significant role. This study explores the metabolic and epigenetic regulation mediated by nicotinamide N-methyl transferase (NNMT) in LUAD.

METHODS

Untargeted metabolomic analyses were performed to detect metabolism irregularities. Single-cell RNA sequencing (RNA-seq) databases and multiplex immunofluorescence analysis were used to identify the location of NNMT within the tumor microenvironment. The biological functions of NNMT were investigated both in vitro and in vivo, with RNA-seq and chromatin immunoprecipitation-PCR providing insights into underlying mechanisms. Finally, single-cell RNA-seq data and immunohistochemistry of primary tumors were analyzed to validate the main findings.

RESULTS

Untargeted metabolomic analyses revealed metabolic aberrations in amino acids, organic acids, lipids, and nicotinamide pathways, which are linked to metastasis of non-small cell lung cancer. NNMT is a key enzyme in nicotinamide metabolism, and we found the bulk tissue mRNA level of NNMT gene was inversely associated with LUAD metastasis. NNMT was proved to be predominantly expressed in cancer-associated fibroblasts (CAFs) within the stromal regions of LUAD, and a low stromal NNMT expression was identified as a predictor of poor disease-free survival following radical resection of LUAD. The isolation and primary culture of CAFs from LUAD enabled in vitro and in vivo experiments, which confirmed that NNMT negatively regulated the metastasis-promoting properties of CAFs in LUAD. Mechanistically, the downregulation of NNMT led to an increase in intracellular methyl groups by reducing the activity of the methionine cycle, resulting in heightened methylation at H3K4me3. This alteration triggered the upregulation of genes involved in extracellular matrix remodeling in CAFs, including those encoding collagens, integrins, laminins, and matrix metalloproteinases, thereby facilitating cancer cell invasion and metastasis. Reanalysis of single-cell RNA-seq data and immunohistochemistry assays of primary LUAD tissues substantiated NNMT's negative regulation of these genes in CAFs.

CONCLUSIONS

This study provides novel insights into the metabolic and epigenetic regulatory functions of NNMT in CAFs, expanding the current understanding of LUAD metastasis regulation and suggesting potential avenues for future research and therapeutic development.

Preoperative CT and Radiomics Nomograms for Distinguishing Bronchiolar Adenoma and Early-Stage Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

Evaluating the capability of CT nomograms and CT-based radiomics nomograms to differentiate between Bronchiolar Adenoma (BA) and Early-stage Lung Adenocarcinoma (LUAD).

MATERIALS AND METHODS

In this retrospective study; we analyzed data from 226 patients who were treated at our institution and pathologically confirmed to have either BA or Early-stage LUAD. Patients were randomly divided into a training cohort (n=158) and a testing cohort (n=68). All CT images were independently analyzed and measured by two radiologists using conventional computed tomography. Clinical predictive factors were identified using logistic regression. Multivariable logistic regression analysis was used to construct differential diagnostic models for BA and early-stage LUAD, including traditional CT and radiomics models. The performance of the models was determined based on the area under the receiver operating characteristic curve, discrimination ability, and decision curve analysis (DCA).

RESULTS

Lesion shape, tumor-lung interface, and pleural retraction signs were identified as independent clinical predictors. The areas under the curve for the CT nomogram, radiomic features, and radiomics nomogram were 0.854, 0.769, and 0.901, respectively. Both the CT nomogram and the radiomics nomogram demonstrated good generalizability in distinguishing between the two entities. DCA indicated that the nomograms achieved a higher net benefit compared to the use of radiomic features alone.

CONCLUSION

The two preoperative nomograms hold significant value in differentiating between patients with BA and those with Early-stage LUAD, and they contribute to informed clinical treatment decision-making.

Development and validation of nomogram for predicting the cancer-specific survival among patients aged 80 and above with early-stage non-small cell lung cancer

BACKGROUND

The use of nomograms in predicting the prognosis of early-stage non-small cell lung cancer (NSCLC), particularly in elderly patients, is not widespread. A validated prognostic model specifically for NSCLC patients over 80 years old holds promising potential for clinical application in forecasting patient outcomes.

METHODS

The prognostic value of various factors for NSCLC patients aged 80 and above was evaluated using data from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2017). Kaplan-Meier (KM) curves, Cox proportional hazards regression models, and nomogram were utilized to evaluate the impact of each factor on cancer-specific survival (CSS).

RESULTS

A cohort comprising 7045 individuals was selected for inclusion in the analysis. Through rigorous statistical analysis, 10 independent prognostic factors were identified and incorporated into the nomogram. The nomogram's receiver operating characteristic (ROC) curve area under the curve (AUC) was higher than that of the AJCC 7th edition TNM staging system's predicted CSS (0.744 versus 0.602), establishing the superior prognostic value of the nomogram.

CONCLUSIONS

We have successfully created a highly accurate and discriminative nomogram that enables oncologists to predict the survival outcome of each individual patient with I/II NSCLC who is 80 years or older.

Burden of obstructive sleep apnea in patients with lung cancer and its effect on performance status

The association between lung cancer and obstructive sleep apnea has remained a matter of debate for years. Obstructive sleep apnea is thought to increase the incidence of lung cancer due to intermittent hypoxaemia and sleep fragmentation. The aim of this study is to assess the prevalence of obstructive sleep apnea in patients with lung cancer and its effect on those patients' performance status. This is a prevalence study that was conducted at Chest Diseases Department, Alexandria Main University Hospitals. We enrolled 153 patients with lung cancer. All patients underwent cardiorespiratory monitoring using a home sleep-testing device. Performance status was assessed using Karnofsky performance status scale. The study included 120 (78.4%) males and 33 (21.6%) females newly diagnosed with lung cancer. The mean age was 59.98 ± 11.11 years. Obstructive sleep apnea (apnea-hypopnea index ≥ 5) was present in 134 (87.6%) patients. Eighty-five (63.4%) patients had mild obstructive sleep apnea, 39 (29.1%) patients had moderate obstructive sleep apnea, and 10 (7.46%) patients had severe obstructive sleep apnea. Prolonged nocturnal oxygen desaturation as demonstrated by time of oxygen saturation spent below 90% (T90%) during total sleep time > 30% was present in 25 (16.3%) patients. There was a significant difference in the median value of Karnofsky performance status scale between patients with lung cancer and associated obstructive sleep apnea and those without obstructive sleep apnea. In conclusion, obstructive sleep apnea is highly prevalent among patients with lung cancer. Performance status is worse among patients with lung cancer in the presence of obstructive sleep apnea. Screening patients with lung cancer for obstructive sleep apnea is important regardless of the presence of classical symptoms of obstructive sleep apnea.

Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) with lymph node (LN) metastasis is linked to poor prognosis, yet the underlying mechanisms remain largely undefined. This study aimed to elucidate the immunogenomic landscape associated with LN metastasis in LUAD.

METHODS

We employed broad-panel next-generation sequencing (NGS) on a cohort of 257 surgically treated LUAD patients to delineate the molecular landscape of primary tumors and identify actionable driver-gene alterations. Additionally, we used multiplex immunohistochemistry (mIHC) on a propensity score-matched cohort, which enabled us to profile the immune microenvironment of primary tumors in detail while preserving cellular metaclusters, interactions, and neighborhood functional units. By integrating data from NGS and mIHC, we successfully identified spatial immunogenomic patterns and developed a predictive model for LN metastasis, which was subsequently validated independently.

RESULTS

Our analysis revealed distinct immunogenomic alteration patterns associated with LN metastasis stages. Specifically, we observed increased mutation frequencies in genes such as PIK3CG and ATM in LN metastatic primary tumors. Moreover, LN positive primary tumors exhibited a higher presence of macrophage and regulatory T cell metaclusters, along with their enriched neighborhood units (p < 0.05), compared to LN negative tumors. Furthermore, we developed a novel predictive model for LN metastasis likelihood, designed to inform non-surgical treatment strategies, optimize personalized therapy plans, and potentially improve outcomes for patients who are ineligible for surgery.

CONCLUSIONS

This study offers a comprehensive analysis of the genetic and immune profiles in LUAD primary tumors with LN metastasis, identifying key immunogenomic patterns linked to metastatic progression. The predictive model derived from these insights marks a substantial advancement in personalized treatment, underscoring its potential to improve patient management.

Effect of Exercise and Pulmonary Rehabilitation in Pre- and Post-Surgical Patients with Lung Cancer: Systematic Review and Meta-Analysis

Background and objectives: Lung cancer is a common cancer, and its impact on public health is not only reflected in the 1 million deaths it causes annually but also in the significant implications it has on daily activities and quality of life, resulting in a considerable burden on healthcare systems. This review aims to determine the effects of pulmonary rehabilitation and pre- or post-surgical exercise in patients with lung cancer. Materials and methods: A systematic review with a meta-analysis of randomized controlled trials published between 2010 and 2024 was conducted; the search was carried out in PubMed, Cochrane Clinical Trial, SCOPUS, Science Direct, Web of Science, Scielo, and LILAC. Results: Pulmonary rehabilitation or exercise before surgery was associated with a greater 6 min walking distance (MD: 37.42, 95% CI: 9.68-65.1; p = 0.008); however, it had no implications on hospital stay (MD: -0.91, 95% CI: -1.88-0.055; p = 0.06). When the intervention was performed post-surgery, higher FEV1 (SMD: 0.62, 95% CI: 0.32-0.92; p = 0.0001) and improved 6 min walking distances (60.8, 95% CI: 20.96-100.6; p = 0.0033) were found compared to standard management. Conclusions: This review suggests that, depending on the timing of implementation, pulmonary rehabilitation or exercise could produce positive effects on certain clinical variables in lung cancer patients.

Number of involved nodal stations predicts survival in small cell lung cancer

BACKGROUND

In small cell lung cancer (SCLC), the pathological N category is identical to it in non-small cell lung cancer (NSCLC) and remains unchanged over a decade. Here we verified the discriminability of number of involved nodal stations (nS) in SCLC and compared its efficacy in predicting survival with currently used pathological nodal (pN) staging.

METHODS

We retrospectively analyzed the patients who received operations and were pathologically diagnosed as SCLC at Shanghai Pulmonary Hospital between 2009 and 2019. X-tile software was adopted to determine optimal cut-off values for nS groups. Kaplan-Meier method and Cox regression analysis were used to compare survival between different groups. Decision curve analysis (DCA) was employed to evaluate the standardized net benefit.

RESULTS

A total of 369 patients were included. The median number of sampled stations was 6 (range 3-11), and the median number of positive stations was 1 (range 0-7). The optimal cutoff for nS groups was: nS0 (no station involved), nS1-2 (one or two stations involved), and nS ≥ 3 (three or more stations involved). Overall survival (OS) and relapse-free survival (RFS) were statistically different among all adjacent categories within the nS classification (p < 0.001, for both OS and RFS between each two subgroups), but survival curves for subgroups in pN overlapped (OS, p = 0.067; RFS, p = 0.068, pN2 vs. pN1). After adjusting for other confounders, nS was a prognostic indicator for OS and RFS. The DCA revealed that nS had improved predictive capability than pN.

CONCLUSIONS

Our cohort study demonstrated that the nS might serve as a superior indicator to predict survival than pN in SCLC and was worth considering in the future definition of the N category.

Neoadjuvant and Adjuvant Treatments for Early Stage Resectable NSCLC: Consensus Recommendations From the International Association for the Study of Lung Cancer

Advances in the multidisciplinary care of early stage resectable NSCLC (rNSCLC) are emerging at an unprecedented pace. Numerous phase 3 trials produced results that have transformed patient outcomes for the better, yet these findings also require important modifications to the patient treatment journey trajectory and reorganization of care pathways. Perhaps, most notably, the need for multispecialty collaboration for this patient population has never been greater. These rapid advances have inevitably left us with important gaps in knowledge for which definitive answers will only become available in several years. To this end, the International Association for the Study of Lung Cancer commissioned a diverse multidisciplinary international expert panel to evaluate the current landscape and provide diagnostic, staging, and therapeutic recommendations for patients with rNSCLC, with particular emphasis on patients with American Joint Committee on Cancer-Union for International Cancer Control TNM eighth edition stages II and III disease. Using a team-based approach, we generated 19 recommendations, of which all but one achieved greater than 85% consensus among panel members. A public voting process was initiated, which successfully validated and provided qualitative nuance to our recommendations. Highlights include the following: (1) the critical importance of a multidisciplinary approach to the evaluation of patients with rNSCLC driven by shared clinical decision-making of a multispecialty team of expert providers; (2) biomarker testing for rNSCLC; (3) a preference for neoadjuvant chemoimmunotherapy for stage III rNSCLC; (4) equipoise regarding the optimal management of patients with stage II between upfront surgery followed by adjuvant therapy and neoadjuvant or perioperative strategies; and (5) the robust preference for adjuvant targeted therapy for patients with rNSCLC and sensitizing EGFR and ALK tumor alterations. Our primary goals were to provide practical recommendations sensitive to the global differences in biology and resources for patients with rNSCLC and to provide expert consensus guidance tailored to the individualized patient needs, goals, and preferences in their cancer care journey as these are areas where physicians must make daily clinical decisions in the absence of definitive data. These recommendations will continue to evolve as the treatment landscape for rNSCLC expands and more knowledge is acquired on the best therapeutic approach in specific patient and disease subgroups.

Diagnosis and management of multiple primary lung cancer

Multiple primary lung cancer (MPLC), can be categorized as synchronous multiple primary lung cancer (sMPLC) and metachronous multiple primary lung cancer (mMPLC), which are becoming increasingly common in clinical practice. A precise differential diagnosis between MPLC and intrapulmonary metastases (IPM) is essential for determining the appropriate management strategy. MPLC is primarily diagnosed through histology, imaging, and molecular methods. Imaging serves as an essential foundation for preoperative diagnosis, while histology is a critical tool for establishing a definitive diagnosis. As molecular biology advances, the diagnosis of MPLC has stepped into the era of molecular precision. Surgery is the preferred treatment approach, with stereotactic radiotherapy and ablation being viable options for unresectable lesions. Targeted therapy and immunotherapy can be considered for specific patients. A multidisciplinary team approach to evaluation and the application of combination therapy can benefit more patients. Looking ahead, the development of more authoritative guidelines will be instrumental in streamlining the diagnosis and management of MPLC.

Pembrolizumab therapy in a patient with NSCLC and bullous pemphigoid: A case report

Immune checkpoint inhibitor (ICI) therapy, which targets programmed cell death protein 1, has demonstrated enhanced survival outcomes in numerous patients with cancer. Historically, individuals with autoimmune diseases have been excluded from clinical trials involving cancer immunotherapies due to concerns about the potential worsening of their underlying autoimmune conditions. In the present case report, a patient with non-small cell lung cancer and bullous pemphigoid (BP) who underwent treatment with the ICI pembrolizumab is described. In this specific clinical case, no severe exacerbation of the underlying autoimmune disease was observed. Contrarily, the patient not only tolerated pembrolizumab well but also experienced amelioration of the BP lesions after the treatment. This case challenges the conventional exclusion criteria for ICI therapy in patients with autoimmune diseases, suggesting the potential safety and efficacy of such treatments in this specific population. However, further investigations and larger-scale studies are warranted to validate these findings and provide a more comprehensive understanding of the implications of ICI therapy in patients with autoimmune comorbidities.

Immunogenomic features of radiologically distinctive nodules in multiple primary lung cancer

OBJECTIVES

To provide molecular and immunological attributes mechanistic insights for the management of radiologically distinctive multiple primary lung cancer (MPLC).

METHODS

The Bulk RNA-seq data of MPLC were obtained from our center. The Bulk RNA-seq data and CT images of patients with single primary lung cancer (SPLC) were obtained from GSE103584. Immune infiltration algorithms were performed to investigate the disparities in the immunological microenvironment between the two groups. Single-cell gene analysis was used to explore immune cells composition and communication relationships between cells in MPLC.

RESULTS

In MPLC, 11 pure ground-glass opacity nodules (pGGN) and 10 mixed GGN (mGGN) were identified, while in SPLC, the numbers were 18 pGGN and 22 mGGN, respectively. In MPLC, compared to pGGN, mGGN demonstrated a significantly elevated infiltration of CD8+ T cells. Single-cell gene analysis demonstrated that CD8+ T cells play a central role in the signaling among immune cells in MPLC. The transcription factors including MAFG, RUNX3, and TBX21 may play pivotal roles in regulation of CD8+ T cells. Notably, compared to SPLC nodules for both mGGN and pGGN, MPLC nodules demonstrated a significantly elevated degree of tumor-infiltrating immune cells, with this difference being particularly pronounced in mGGN. There was a positive correlation between the proportion of immune cells and consolidation/tumor ratio (CTR).

CONCLUSIONS

Our findings provided a comprehensive description about the difference in the immune microenvironment between pGGN and mGGN in early-stage MPLC, as well as between MPLC and SPLC for both mGGN and pGGN. The findings may provide evidence for the design of immunotherapeutic strategies for MPLC.

Real-World Analysis of Survival and Treatment Efficacy in Stage IIIA-N2 Non-Small Cell Lung Cancer

BACKGROUND

Stage IIIA-N2 non-small cell lung cancer (NSCLC) poses a significant clinical challenge, with low survival rates despite advances in therapy. The lack of a standardised treatment approach complicates patient management. This study utilises real-world data from Guy's Thoracic Cancer Database to analyse patient outcomes, identify key predictors of overall survival (OS) and disease-free survival (DFS), and address the limitations of randomised controlled trials.

METHODS

This observational, single-centre, non-randomised study analysed 142 patients diagnosed with clinical and pathological T1/2 N2 NSCLC who received curative treatment from 2015 to 2021. Patients were categorised into three groups: Group A (30 patients) underwent surgery for clinical N2 disease, Group B (54 patients) had unsuspected N2 disease discovered during surgery, and Group C (58 patients) received radical chemoradiation or radiotherapy alone (CRT/RT) for clinical N2 disease. Data on demographics, treatment types, recurrence, and survival rates were analysed.

RESULTS

The median OS for the cohort was 31 months, with 2-year and 5-year OS rates of 60% and 30%, respectively. Group A had a median OS of 32 months, Group B 36 months, and Group C 25 months. The median DFS was 18 months overall, with Group A at 16 months, Group B at 22 months, and Group C at 17 months. Significant predictors of OS included ECOG performance status, lymphovascular invasion, and histology. No significant differences in OS were found between treatment groups (p = 0.99).

CONCLUSIONS

This study highlights the complexity and diversity of Stage IIIA-N2 NSCLC, with no single superior treatment strategy identified. The findings underscore the necessity for personalised treatment approaches and multidisciplinary decision-making. Future research should focus on integrating newer therapeutic modalities and conducting multi-centre trials to refine treatment strategies. Collaboration and ongoing data collection are crucial for improving personalised treatment plans and survival outcomes for Stage IIIA-N2 NSCLC patients.

Analysis of high‑risk factors for brain metastasis and prognosis after prophylactic cranial irradiation in limited‑stage small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive malignancy with a high propensity for brain metastases (BM). Limited-stage SCLC (LS-SCLC) can be effectively treated with chemoradiotherapy and prophylactic cranial irradiation (PCI) to enhance patient outcomes. The aim of the present study was to assess the risk factors and prognostic significance of brain metastases (BM) in patients with limited-stage small cell lung cancer (LS-SCLC) who attained complete remission (CR) or partial remission (PR) following combined chemoradiotherapy and subsequent prophylactic cranial irradiation (PCI). Data for 290 patients diagnosed with LS-SCLC and treated at Chengde Central Hospital and Hebei Cangzhou Hospital of Integrated Traditional Chinese and Western Medicine (Chengde, China), who achieved CR or PR and underwent PCI between 2015 and 2023, were retrospectively analyzed. BM rates and overall survival (OS) were estimated using the Kaplan-Meier method, whilst differences were assessed using the log-rank test. Risk factors affecting BM and OS were assessed using univariate and multivariate Cox regression analyses. The overall incidence of BM after PCI was 16.6% (48/290), with annual rates of 1.4, 6.6 and 12.8% at 1, 2 and 3 years, respectively. Multivariate Cox regression analysis identified an initial tumor size of >5 cm [hazard ratio (HR)=15.031; 95% confidence interval (CI): 5.610-40.270; P<0.001] as a significant independent risk factor for BM following PCI. The median OS was 28.8 months and the 5-year OS rate was 27.9%. The median OS for patients with and without BM at 27.55 and 32.5 months, respectively, and the corresponding 5-year OS rates were 8.3 and 31.8%, respectively (P=0.001). Median OS rates for stages I, II and III were 61.15, 48.5 and 28.4 months, respectively, with 5-year OS rates of 62.5, 47.1 and 21.6%, respectively (P<0.001). Further multivariate Cox regression analysis indicated that BM (HR=1.934; 95% CI: 1.358-2.764; P<0.001) and clinical stage (HR=1.741; 95% CI: 1.102-2.750; P=0.018; P=0.022) were significant independent risk factors associated with patient OS. In conclusion, a tumor size of >5 cm is a significant risk factor for BM following PCI in patients with LS-SCLS achieving CR or PR through radiotherapy and chemotherapy. Furthermore, BM and clinical staging independently influence OS.

2.5D peritumoural radiomics predicts postoperative recurrence in stage I lung adenocarcinoma

Objective

Radiomics can non-invasively predict the prognosis of a tumour by applying advanced imaging feature algorithms.The aim of this study was to predict the chance of postoperative recurrence by modelling tumour radiomics and peritumour radiomics and clinical features in patients with stage I lung adenocarcinoma (LUAD).

Materials and methods

Retrospective analysis of 190 patients with postoperative pathologically confirmed stage I LUAD from centre 1, who were divided into training cohort and internal validation cohort, with centre 2 added as external validation cohort. To develop a combined radiation-clinical omics model nomogram incorporating clinical features based on images from low-dose lung cancer screening CT plain for predicting postoperative recurrence and to evaluate the performance of the nomogram in the training cohort, internal validation cohort and external validation cohort.

Results

A total of 190 patients were included in the model in centre 1 and randomised into a training cohort of 133 and an internal validation cohort of 57 in a ratio of 7:3, and 39 were included in centre 2 as an external validation cohort. In the training cohort (AUC=0.865, 95% CI 0.824-0.906), internal validation cohort (AUC=0.902, 95% CI 0.851-0.953) and external validation cohort (AUC=0.830,95% CI 0.751-0.908), the combined radiation-clinical omics model had a good predictive ability. The combined model performed significantly better than the conventional single-modality models (clinical model, radiomic model), and the calibration curve and decision curve analysis (DCA) showed high accuracy and clinical utility of the nomogram.

Conclusion

The combined preoperative radiation-clinical omics model provides good predictive value for postoperative recurrence in stage ILUAD and combines the model's superiority in both internal and external validation cohorts, demonstrating its potential to aid in postoperative treatment strategies.

The presentation pattern and surgical strategies in bronchopulmonary carcinoid tumors: a multicenter experience in a low-income country

Background

Bronchopulmonary carcinoid tumors include typical and atypical carcinoids, with typical carcinoids accounting for 80%-90% of these types of tumor. The primary curative treatment for these tumors is surgical resection. To our knowledge, there are limited studies on the presentation patterns and treatment strategies of bronchopulmonary carcinoid tumors in Africa.

Objective

To determine the presentation patterns and surgical strategies in bronchopulmonary carcinoid tumors in patients treated at multicenters in Ethiopia from January 2018 to December 2023.

Materials and methods

A 5-year retrospective cross-sectional study was conducted using medical records and pathology record reviews of patients operated on in Tikur Anbessa Specialized Hospital, Menelik II Hospital, and Saint Peter's Specialized Hospital from 1 January 2018 to 31 December 2023. The completeness of the data was checked before being entered into EpiData version 4.6.1, and analysis was conducted using SPSS version 29. Logistic regression was applied to depict the association of the histological pattern with its predictors. A P-value of <0.05 was considered significant for the association of variables.

Results

A total of 62 patients with bronchopulmonary carcinoid tumors were included in the study with a mean age of 35.29 ± 12.26 years ranging from 14 to 67 years, in which more than half [37 (56.5%)] were females, with a male-to-female ratio of 1:1.3. The majority of the patients were non-smokers (90.3%) and symptomatic (98.4%), with a mean duration of symptoms of 29.7 ± 26 months, ranging from 3 to 156 months. Nearly half of the patients (48.4%) were treated for pulmonary tuberculosis before a diagnosis of carcinoid tumor was made. The majority of the patients underwent surgery by open posterolateral thoracotomy (98.4%), and pneumonectomy was the most common (38.7%) resection performed. Typical carcinoids were observed in 85.5% of patients. Age, smoking history, duration of symptoms, location of tumors, and lymph node status were statistically associated with histological patterns.

Recommendation

Based on our study findings, improving physician awareness on the clinical presentation of carcinoid tumors, training for surgeons in less invasive surgical approaches, and further nationwide studies are recommended.

Spectral CT for preoperative diagnosis of N2 station lymph node metastasis in solid T1 non-small cell lung cancer

PURPOSE

To evaluate the diagnostic value of spectral CT for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 non-small cell lung cancer (NSCLC).

METHOD

For this retrospective study, dual-phase contrast agent-enhanced CT was performed in patients with NSCLC from September 2019 to June 2023. Quantitative spectral CT parameters measurements were performed by 2 radiologists independently. Logistic regression analysis and Delong test were performed.

RESULTS

60 NSCLC patients (mean age, 62.85 years ± 8.49, 44men) were evaluated. A total of 121 lymph nodes (38 with metastasis) were enrolled. There was no significant difference in the slope of the spectral Hounsfield unit curve (λHu) on arterial phase (AP) or venous phase (VP) between primary lesions and metastatic lymph nodes (P > 0.05), but significant difference in VP λHu between primary lesions and non-metastatic lymph nodes (P < 0.001). The CT40KeV, λHu, normalized iodine concentration (nIC), normalized effective atomic number (nZeff) measured during both AP and VP were lower in metastatic lymph nodes than in non-metastatic lymph nodes (all P < 0.05). Short-axis diameter (S) of metastatic lymph nodes was higher than non-metastatic lymph nodes (P < 0.001). Area under the curve (AUC) for S performed the highest (0.788) in diagnosing metastatic lymph nodes. When combined with VP λHu, VP nZeff, AUC increased to 0.871.

CONCLUSION

Spectral CT is a complementary means for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 NSCLC. The combined parameters have higher diagnostic efficiency.

Can stage-IIB lung cancer be divided into subgroups in terms of prognosis? A modelling study. Acta Chir Belg 2024;124:191-199. [PMID: 37615953 DOI: 10.1080/00015458.2023.2251802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

INTRODUCTION

Whether changes should be made to the TNM classification of non-small cell lung cancer (NSCLC) according to the newly proposed nodal classification is unclear. We aim to compare the survival between stage-IIB subsets using a modelling study performed using the newly proposed nodal classification.

PATIENTS AND METHODS

A total of 682 patients with stage-IIB NSCLC based on the 8th TNM classification were analysed. Hazard ratio (HR) values calculated from survival comparisons between stage-IIB subgroups were used to create a model for patients with stage-IIB NSCLC, and modelling was performed according to the HR values that were close to each other.

RESULTS

Patients with T1N1a cancer had the best survival rate (58.2%), whereas the worst prognosis was observed in those with T2bN1b cancer (39.2%). The models were created using the following HR results: Model A (T1N1a, n = 85; 12.4%), Model B (T2a/T2bN1a and T3N0, n = 438; 64.2%), and Model C (T1/T2a/T2bN1b, n = 159; 23.4%). There was a significant difference between the models in terms of overall survival (p = 0.03). The median survival time was 69 months in Model A, 56 months in Model B, and 47 months in Model C (Model A vs. Model B, p = 0.224; Model A vs. Model C, p = 0.01; and Model B vs. Model C, p = 0.04). Multivariate analysis showed that age (p < 0.001), pleural invasion (p < 0.001), and the developed modelling system (p = 0.02) were independently negative prognostic factors.

CONCLUSION

There was a prognostic difference between stage-IIB subsets in NSCLC patients. The model created for stage-IIB lung cancer showed a high discriminatory power for prognosis.

The Prognostic Impact of Epidermal Growth Factor Receptor Mutation in Clinical Stage I Lung Adenocarcinoma

BACKGROUND

This study investigated the prognostic impact of epidermal growth factor receptor (EGFR) mutation in clinical stage I lung adenocarcinoma patients.

METHODS

Data for 952 patients who received surgical resection and underwent detection of oncogenic driver mutations were retrospectively collected. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method and compared using the log-rank test. The adjusted hazard ratio (aHR) with 95% CI of the prognosticator was calculated by Cox proportional hazards model, and cumulative incidence function was measured by competing risk regression model.

RESULTS

EGFR mutation was detected in 581 patients (61.0%) and was more frequent in women (63.9%), nonsmokers (85.5%), and those with ground-glass nodules (GGNs; 56.6%). EGFR mutation was not associated with recurrence and death in the entire cohort or GGN cohort. However, for patients with radiologic pure-solid appearance, EGFR mutation was an independent risk factor for RFS (aHR, 1.623; 95% CI, 1.192-2.210) and distant recurrence (aHR, 1.863; 95% CI, 1.311-2.650), but not OS. Subsequently, subgroup analysis based on EGFR mutation subtypes, including exon 19 deletions (19-Del), exon 21 L858R substitution (L858R), and rare mutations in patients with radiologic pure-solid appearance, revealed that all 3 subtypes have poorer RFS (19-Del: aHR, 1.424; 95% CI, 0.991-2.047; L858R: aHR, 1.708; 95% CI, 1.172-2.490; rare mutations: aHR, 2.500; 95% CI, 1.400-4.465) and higher prevalent distant recurrence (19-Del: aHR, 1.595; 95% CI, 1.061-2.400; L858R: aHR, 2.073; 95% CI, 1.371-3.140; rare mutations: aHR, 2.657; 95% CI, 1.397-5.050) compared with wild-type.

CONCLUSIONS

In clinical stage I lung adenocarcinoma, EGFR mutation was associated with worse RFS and higher prevalent distant recurrence in patients with radiologic pure-solid appearance but not in patients with GGN.

Incidence rate of occult lymph node metastasis in clinical T1-2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study : Original research

BACKGROUND

This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients and develop machine learning prediction models using preoperative intratumoral and peritumoral contrast-enhanced CT-based radiomic data.

METHODS

By conducting a retrospective analysis involving 242 eligible patients from 4 centeres, we determined the incidence of OLM in cT1 - 2N0M0 SCLC patients. For each lesion, two ROIs were defined using the gross tumour volume (GTV) and peritumoral volume 15 mm around the tumour (PTV). By extracting a comprehensive set of 1595 enhanced CT-based radiomic features individually from the GTV and PTV, five models were constucted and we rigorously evaluated the model performance using various metrics, including the area under the curve (AUC), accuracy, sensitivity, specificity, calibration curve, and decision curve analysis (DCA). For enhanced clinical applicability, we formulated a nomogram that integrates clinical parameters and the rad_score (GTV and PTV).

RESULTS

The initial investigation revealed a 33.9% OLM positivity rate in cT1 - 2N0M0 SCLC patients. Our combined model, which incorporates three radiomic features from the GTV and PTV, along with two clinical parameters (smoking status and shape), exhibited robust predictive capabilities. With a peak AUC value of 0.772 in the external validation cohort, the model outperformed the alternative models. The nomogram significantly enhanced diagnostic precision for radiologists and added substantial value to the clinical decision-making process for cT1 - 2N0M0 SCLC patients.

CONCLUSIONS

The incidence of OLM in SCLC patients surpassed that in non-small cell lung cancer patients. The combined model demonstrated a notable generalization effect, effectively distinguishing between positive and negative OLMs in a noninvasive manner, thereby guiding individualized clinical decisions for patients with cT1 - 2N0M0 SCLC.

Prognostic nomogram based on pre-treatment HALP score for patients with advanced non-small cell lung cancer

BACKGROUND

To explore the correlation of pre-treatment Hemoglobin-Albumin-Lymphocyte-Platelet (HALP) score with the prognosis of patients with advanced Non-Small Cell Lung Cancer (NSCLC) undergoing first-line conventional platinum-based chemotherapy.

METHODS

In this retrospective cohort study, 203 patients with advanced NSCLC were recruited from January 2017 to December 2021. The cut-off value for the HALP score was determined by Receiver Operating Characteristic (ROC) curve analysis. The baseline characteristics and blood parameters were recorded, and the Log-rank test and Kaplan-Meier curves were applied for the survival analysis. In the univariate and multivariate analyses, the Cox regression analysis was carried out. The predictive accuracy and discriminative ability of the nomogram were determined by the Concordance index (C-index) and calibration curve and compared with a single HALP score by ROC curve analysis.

RESULTS

The optimal cut-off value for the HALP score was 28.02. The lower HALP score was closely associated with poorer Progression-Free Survival (PFS) and Overall Survival (OS). The male gender and other pathological types were associated with shorter OS. Disease progression and low HALP were correlated with shorter OS and PFS. In addition, nomograms were established based on HALP scores, gender, pathology type and efficacy rating, and used to predict OS. The C-index for OS prediction was 0.7036 (95% CI 0.643 to 0.7643), which was significantly higher than the C-index of HALP at 6-, 12-, and 24-months.

CONCLUSION

The HALP score is associated with the prognosis of advanced NSCLC patients receiving conventional platinum-based chemotherapy, and the nomogram established based on the HALP score has a better predictive capability for OS.

Predictors of moderate to severe obstructive sleep apnea in patients with lung cancer

BACKGROUND AND OBJECTIVES

OSA is a known medical condition that is associated with several comorbidities and affect patients' quality of life. The association between OSA and lung cancer remains debated. Some studies reported increased prevalence of OSA in patients with lung cancer. We aimed to assess predictors of moderate-to-severe OSA in patients with lung cancer.

METHODS

We enrolled 153 adult patients who were newly diagnosed with lung cancer. Cardiorespiratory monitoring was performed using home sleep apnea device. We carried out Univariate and multivariate logistic regression analysis on multiple parameters including age, gender, smoking status, neck circumference, waist circumference, BMI, stage and histopathology of lung cancer, presence of superior vena cava obstruction, and performance status to find out the factors that are independently associated with a diagnosis of moderate-to-severe OSA.

RESULTS

Our results suggest that poor performance status is the most significant predictor of moderate to severe OSA in patients with lung cancer after controlling for important confounders.

CONCLUSION

Performance status is a predictor of moderate to severe OSA in patients with lung cancer in our population of middle eastern ethnicity.

Association of log odds of positive lymph nodes with survival in patients with small cell lung cancer: Results from the SEER database

OBJECTIVES

The prognosis of patients with Small Cell Lung Cancer (SCLC) can be predicted by their Lymph Node (LN) status. The authors aimed to assess the correlations between SCLC survival and number of LN Ratio (LNR), positive LN (pLNs), and Logarithmic Odds of positive LN (LODDS).

METHODS

This cohort study retrospectively included 1,762 patients with SCLC from the SEER database 2004‒2015. The X-tile software was used to determine the cutoff values for pLNs, LNR, and LODDS. The correlations between pLNs, LNR, and LODDS with Overall Survival (OS) and Cancer-Specific Survival (CSS) were explored using Cox regression analysis. The study used the C-index to assess the predictive value of LNR, pLNs, and LODDS on survival.

RESULTS

Among these 1,762 patients, 121 (6.87%) were alive, 1,641 (93.13%) died, and 1,532 (86.95%) died of SCLC. In univariable COX analysis, LNR, pLNs, and LODDS all showed a correlation with CSS and OS (p < 0.05). In multivariable COX analysis, only patients with LODDS (> 0.3 vs. ≤ 0.3) were related to both worse OS (HR = 1.28, 95% CI 1.10‒1.50) and CSS (HR = 1.29, 95% CI 1.10‒1.51), but no correction was observed between LNR and pLNs and survival (p > 0.05). The C-indices for predicting OS for LODDS were 0.552 (95% CI 0.541‒0.563), for LNR 0.504 (95% CI 0.501‒0.507), and for pLNs 0.527 (95% CI 0.514‒0.540). Moreover, the association between LODDS and prognosis in SCLC patients was significant only in patients with LN stage N1 and N2, but not in stage N3.

CONCLUSION

LODDS may be better than other LN assessment tools at predicting survival in SCLC patients.

Osimertinib in combination with anti-angiogenesis therapy presents a promising option for osimertinib-resistant non-small cell lung cancer

BACKGROUND

Osimertinib has become standard care for epidermal growth factor receptor (EGFR)-positive non-small cell lung cancer (NSCLC) patients whereas drug resistance remains inevitable. Now we recognize that the interactions between the tumor and the tumor microenvironment (TME) also account for drug resistance. Therefore, we provide a new sight into post-osimertinib management, focusing on the alteration of TME.

METHODS

We conducted a retrospective study on the prognosis of different treatments after osimertinib resistance. Next, we carried out in vivo experiment to validate our findings using a humanized mouse model. Furthermore, we performed single-cell transcriptome sequencing (scRNA-seq) of tumor tissue from the above treatment groups to explore the mechanisms of TME changes.

RESULTS

Totally 111 advanced NSCLC patients have been enrolled in the retrospective study. The median PFS was 9.84 months (95% CI 7.0-12.6 months) in the osimertinib plus anti-angiogenesis group, significantly longer than chemotherapy (P = 0.012) and osimertinib (P = 0.003). The median OS was 16.79 months (95% CI 14.97-18.61 months) in the osimertinib plus anti-angiogenesis group, significantly better than chemotherapy (P = 0.026), the chemotherapy plus osimertinib (P = 0.021), and the chemotherapy plus immunotherapy (P = 0.006). The efficacy of osimertinib plus anlotinib in the osimertinib-resistant engraft tumors (R-O+A) group was significantly more potent than the osimertinib (R-O) group (P<0.05) in vitro. The combinational therapy could significantly increase the infiltration of CD4+ T cells (P<0.05), CD25+CD4+ T cells (P<0.001), and PD-1+CD8+ T cells (P<0.05) compared to osimertinib. ScRNA-seq demonstrated that the number of CD8+ T and proliferation T cells increased, and TAM.mo was downregulated in the R-O+A group compared to the R-O group. Subtype study of T cells explained that the changes caused by combination treatment were mainly related to cytotoxic T cells. Subtype study of macrophages showed that proportion and functional changes in IL-1β.mo and CCL18.mo might be responsible for rescue osimertinib resistance by combination therapy.

CONCLUSIONS

In conclusion, osimertinib plus anlotinib could improve the prognosis of patients with a progressed disease on second-line osimertinib treatment, which may ascribe to increased T cell infiltration and TAM remodeling via VEGF-VEGFR blockage.

Anlotinib in Chinese patients aged ≥70 years with advanced non-squamous non-small cell lung cancer without prior chemotherapy: a multicenter, single-arm pilot trial

Background

Based on pharmacoeconomics, drug availability and actual treatment, optimal treatment regimens for Chinese non-small-cell lung carcinoma (NSCLC) patients over 70 years old are needed.

Methods

This multicenter, single-arm pilot trial enrolled patients with advanced non-squamous NSCLC who refused systemic chemotherapy. Eligible patients received anlotinib (12 mg/day, d1-14, Q3W) until disease progression, intolerant toxicities, or withdrawal from the study. The primary endpoint was progression-free survival (PFS).

Results

Forty-nine patients were screened between January 2019 and September 2021, of whom 40 patients were eligible. The median age was 76 years. With a median follow-up period of 16.20 (95% CI: 8.77, 25.10) months, the median PFS was 5.45 months (95% CI: 3.52-9.23) and the median overall survival was 10.32 months (95% CI: 6.44-12.78). Three patients achieved a partial response and 34 had stable disease, with an objective response rate of 7.5% and a disease control rate of 92.5%. Thirty-three (82.5%; 33/40) patients reported treatment-related adverse events (TRAEs) of any grade, and the incidence rate of grade ≥3 TRAEs was 35% (14/40). The most common grade ≥3 TRAEs were hypertension (4/40; 10.0%), hand-foot syndrome (3/40; 7.5%), and proteinuria (2/40; 5.0%).

Conclusion

Anlotinib treatment was feasible and safe in Chinese elderly patients with advanced non-squamous NSCLC who did not receive any systemic chemotherapy.

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma

BACKGROUND

Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD).

METHODS

Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS).

RESULTS

This study identified TIME-related lncRNAs from integrated analysis of single‑cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy.

CONCLUSIONS

This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.

Enhanced Survival with Lymphadenectomy in Early-Stage Metachronous Second Primary Lung Cancer: A Retrospective Analysis

INTRODUCTION

Lymphadenectomy is a cornerstone in the surgical management of resectable primary lung cancer. However, its prognostic significance in early-stage metachronous second primary lung cancer (MSPLC) remains poorly understood. This retrospective study aimed to evaluate the prognostic impact of lymphadenectomy in these patients using data from the Surveillance, Epidemiology, and End Results (SEER) Database.

METHODS

A retrospective cohort study was conducted using data from the SEER Database for patients surgically treated for stage I MSPLC between 2004 and 2015. Propensity score-matching was employed to create comparable cohorts, and the Cox proportional hazards model was utilized to estimate the hazard ratio (HR) for overall survival after lymphadenectomy compared to non-lymphadenectomy. Survival analysis was performed using Kaplan-Meier curves and the log-rank test.

RESULTS

Among 920 identified patients with MSPLC, 574 (62.4%) underwent lymphadenectomy. Propensity score-matching yielded 255 patients in both the lymphadenectomy and non-lymphadenectomy groups. Over a median follow-up of 38 months, the 5-year overall survival probability after a diagnosis of MSPLC was 58.7% in the lymphadenectomy group and 43.9% in the non-lymphadenectomy group (HR: 0.76; 95% confidence interval 0.64-0.90; p = 0.002).

CONCLUSION

In this population-based study, lymphadenectomy is associated with prolonged overall survival in patients with stage I MSPLC. These findings suggest the potential benefit of incorporating lymphadenectomy into the surgical management of MSPLC, providing valuable guidance for thoracic surgeons in clinical decision-making.

The association of visceral pleural invasion with skip N2 metastasis on clinical stage IA NSCLC

BACKGROUND

Lung lymphatic drainage occurs mainly through a peribronchial path, but it is hypothesized that visceral pleural invasion could alter this path. This study aims to investigate the association between visceral pleural invasion, node upstaging, and N2 skip metastasis and the impact on survival in a population of patients with non-small cell lung cancer of 3 cm or smaller.

METHODS

We retrospectively queried our institutional database of lung cancer resection for all patients with clinical stage IA NSCLC between June 2009 and June 2022. We collected baseline characteristics and clinical and pathological staging data. Patients were classified into two groups: The non-VPI group with negative visceral pleural invasion and the VPI group with positive. The primary results analyzed were the occurrence of nodal upstaging, skip N2 metastasis and recurrence.

RESULTS

There were 320 patients analyzed. 61.3 % were women; the median age was 65.4 years. The pleural invasion occurred in 44 patients (13.7 %). VPI group had larger nodules (2.3 vs. 1.7 cm; p < 0.0001), higher 18F-FDG uptake (7.4 vs. 3.4; p < 0.0001), and lymph-vascular invasion (35.7 % vs. 13.5 %, p = 0.001). Also, the VPI group had more nodal disease (25.6 % vs. 8.7 %; p = 0.001) and skip N2 metastasis (9.3 % vs. 1.8 %; p = 0.006). VPI was a statistically independent factor for skip N2 metastasis. Recurrence occurred in 17.2 % of the population. 5-year disease-free and overall survival were worse in the VPI group.

CONCLUSIONS

The visceral pleural invasion was an independent factor associated with N2 skip metastasis and had worse disease-free and overall survival.

Exploration and machine learning model development for T2 NSCLC with bronchus infiltration and obstructive pneumonia/atelectasis

In the 8th edition of the American Joint Committee on Cancer (AJCC) staging system for Non-Small Cell Lung Cancer (NSCLC), tumors exhibiting main bronchial infiltration (MBI) near the carina and those presenting with complete lung obstructive pneumonia/atelectasis (P/ATL) have been reclassified from T3 to T2. Our investigation into the Surveillance, Epidemiology, and End Results (SEER) database, spanning from 2007 to 2015 and adjusted via Propensity Score Matching (PSM) for additional variables, disclosed a notably inferior overall survival (OS) for patients afflicted with these conditions. Specifically, individuals with P/ATL experienced a median OS of 12 months compared to 15 months (p < 0.001). In contrast, MBI patients demonstrated a slightly worse prognosis with a median OS of 22 months versus 23 months (p = 0.037), with both conditions significantly correlated with lymph node metastasis (All p < 0.001). Upon evaluating different treatment approaches for these particular T2 NSCLC variants, while adjusting for other factors, surgery emerged as the optimal therapeutic strategy. We counted those who underwent surgery and found that compared to surgery alone, the MBI/(P/ATL) group experienced a much higher proportion of preoperative induction therapy or postoperative adjuvant therapy than the non-MBI/(P/ATL) group (41.3%/54.7% vs. 36.6%). However, for MBI patients, initial surgery followed by adjuvant treatment or induction therapy succeeded in significantly enhancing prognosis, a benefit that was not replicated for P/ATL patients. Leveraging the XGBoost model for a 5-year survival forecast and treatment determination for P/ATL and MBI patients yielded Area Under the Curve (AUC) scores of 0.853 for P/ATL and 0.814 for MBI, affirming the model's efficacy in prognostication and treatment allocation for these distinct T2 NSCLC categories.

LNAS: a clinically applicable deep-learning system for mediastinal enlarged lymph nodes segmentation and station mapping without regard to the pathogenesis using unenhanced CT images

BACKGROUND

The accurate identification and evaluation of lymph nodes by CT images is of great significance for disease diagnosis, treatment, and prognosis.

PURPOSE

To assess the lymph nodes' segmentation, size, and station by artificial intelligence (AI) for unenhanced chest CT images and evaluate its value in clinical scenarios.

MATERIAL AND METHODS

This retrospective study proposed an end-to-end Lymph Nodes Analysis System (LNAS) consisting of three models: the Lymph Node Segmentation model (LNS), the Mediastinal Organ Segmentation model (MOS), and the Lymph Node Station Registration model (LNR). We selected a healthy chest CT image as the template image and annotated 14 lymph node station masks according to the IASLC to build the lymph node station mapping template. The exact contours and stations of the lymph nodes were annotated by two junior radiologists and reviewed by a senior radiologist. Patients aged 18 and above, who had undergone unenhanced chest CT and had at least one suspicious enlarged mediastinal lymph node in imaging reports, were included. Exclusions were patients who had thoracic surgeries in the past 2 weeks or artifacts on CT images affecting lymph node observation by radiologists. The system was trained on 6725 consecutive chest CTs that from Tianjin Medical University General Hospital, among which 6249 patients had suspicious enlarged mediastinal lymph nodes. A total of 519 consecutive chest CTs from Qilu Hospital of Shandong University (Qingdao) were used for external validation. The gold standard for each CT was determined by two radiologists and reviewed by one senior radiologist.

RESULTS

The patient-level sensitivity of the LNAS system reached of 93.94% and 92.89% in internal and external test dataset, respectively. And the lesion-level sensitivity (recall) reached 89.48% and 85.97% in internal and external test dataset. For man-machine comparison, AI significantly apparently shortened the average reading time (p < 0.001) and had better lesion-level and patient-level sensitivities.

CONCLUSION

AI improved the sensitivity lymph node segmentation by radiologists with an advantage in reading time.

A CT-based deep learning model: visceral pleural invasion and survival prediction in clinical stage IA lung adenocarcinoma

Pathologic visceral pleural invasion (VPI) in patients with early-stage lung cancer can result in the upstaging of T1 to T2, in addition to having implications for surgical resection and prognostic outcomes. This study was designed with the goal of establishing and validating a CT-based deep learning (DL) model capable of predicting VPI status and stratifying patients based on their prognostic outcomes. In total, 2077 patients from three centers with pathologically confirmed clinical stage IA lung adenocarcinoma were enrolled. DL signatures were extracted with a 3D residual neural network. DL model was able to effectively predict VPI status. VPI predicted by the DL models, as well as pathologic VPI, was associated with shorter disease-free survival. The established deep learning signature provides a tool capable of aiding the accurate prediction of VPI in patients with clinical stage IA lung adenocarcinoma, thus enabling prognostic stratification.

The prognostic impact of tumor length on pathological stage IA-IC esophageal adenocarcinoma

This study was completed to evaluate the relationship between tumor length and the prognosis of patients with pathological stage IA-IC esophageal adenocarcinoma (EAC). Patients were identified from the Surveillance, Epidemiology, and End Results Program database (United States, 2006-2015). X-tile software and ROC analysis were mainly used to explore the best threshold of tumor length for dividing patients into different groups, and then propensity score matching (PSM) was used to balance other variables between groups. The primary outcome assessed was overall survival (OS). A total of 762 patients were identified, and 500 patients were left after PSM. Twenty millimeters were used as the threshold of tumor length. Patients with longer tumor lengths showed worse OS (median: 93 vs. 128 months; P = 0.006). Multivariable Cox regression analysis showed that longer tumor length was an independent risk factor (hazard ratio 1.512, 95% confidence interval, 1.158-1.974, P = 0.002). Tumor length has an impact on patients with pathological stage IA-IC EAC who undergo surgery alone. The prognostic value of the pathological stage group may be improved after combining it with tumor length and age.

Evaluation of the relationship of the T and M stage with the erector spinae muscle area in male lung cancer patients

OBJECTIVES

Sarcopenia is very common due to cachexia and presents with a decrease in skeletal muscle mass. In this study, we aimed to investigate the relationship between the T, M category and the erector spinae muscle area (ESMa).

MATERIAL AND METHODS

The initial first thorax and high-resolution computed tomography (CT) of patients with lung cancer between 2015 and 2019 were retrospectively screened. After exclusion criterias remaining 226 male patients constituted the study group. ESMa was measured manually in the section taken from the T12 vertebra spinous process level as previously described in the literature and its relationship with the T and M stage were evaluated.

RESULTS

The mean ages of patients were 70 ± 9.57 years. The T stage was T1 in 34 (15%) patients, T2 in 46 (20.4%), T3 in 59 (26.1%), and T4 in 87 (38.5%). Metastasis was detected in 83 (36.7%) patients. The mean ESMa of the patients was 34.15 ± 7.21 mm² and did not differ according to the T stage (p = .39). ESMa was lower in the metastatic group (mean 30.42 ± 6.38 mm²) than the non-metastatic group (mean 36.32 ± 6.78 mm²) (p = .0001).

CONCLUSIONS

ESMa, one of the indicators of sarcopenia, is lower in patients with metastatic lung cancer than in nonmetastatic.

Using CT imaging features to predict visceral pleural invasion of non-small-cell lung cancer

AIM

To examine the diagnostic performance of different models based on computed tomography (CT) imaging features in differentiating the invasiveness of non-small-cell lung cancer (NSCLC) with multiple pleural contact types.

MATERIALS AND METHODS

A total of 1,573 patients with NSCLC (tumour size ≤3 cm) were included retrospectively. The clinical and pathological data and preoperative imaging features of these patients were investigated and their relationships with visceral pleural invasion (VPI) were compared statistically. Multivariate logistic regression was used to eliminate confounding factors and establish different predictive models.

RESULTS

By univariate analysis and multivariable adjustment, surgical history, tumour marker (TM), number of pleural tags, length of solid contact and obstructive inflammation were identified as independent risk predictors of pleural invasiveness (p=0.014, 0.003, <0.001, <0.001, and 0.017, respectively). In the training group, comparison of the diagnostic efficacy between the combined model including these five independent predictors and the image feature model involving the latter three imaging predictors were as follows: sensitivity of 88.9% versus 77% and specificity of 73.5% versus 84.1%, with AUC of 0.868 (95% CI: 0.848-0.886) versus 0.862 (95% CI: 0.842-0.880; p=0.377). In the validation group, the sensitivity and specificity of these two models were as follow: the combined model, 93.5% and 74.3%, the imaging feature model, 77.4% and 81.3%, and their areas under the curve (AUCs) were both 0.884 (95% CI: 0.842-0.919). The best cut-off value of length of solid contact was 7.5 mm (sensitivity 68.9%, specificity 75.5%).

CONCLUSIONS

The image feature model showed great potential in predicting pleural invasiveness, and had comparable diagnostic efficacy compared with the combined model containing clinical data.

Predictability and Utility of Contrast-Enhanced CT on Occult Lymph Node Metastasis for Patients with Clinical Stage IA-IIA Lung Adenocarcinoma: A Double-Center Study

RATIONALE AND OBJECTIVES

With the advantage of minimizing damage and preserving more functional lung tissue, limited surgery is considered depend on the lymph node (LN) involvement situation. However, occult lymph node metastasis (OLM) may be ignored by limited surgery and become a risk factor for local recurrence after surgical resection. The aim of this study was to assess the risk factors for OLM based on computed tomography enhanced image in patients with clinical lung adenocarcinoma (ADC).

MATERIALS AND METHODS

From January 2016 to July 2022, 707 patients with clinical stage IA-IIA ADC underwent lobectomy with systematic LN dissection and were divided into training and validation group based on different institution. Univariate analysis followed by multivariable logistic regression were performed to estimate different risk factors of OLM. A predictive model was established with visual nomogram and external validation, and evaluated in terms of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).

RESULTS

Fifty-nine patients were diagnosed with OLM (11.9%), and four independent predictors of LN involvement were identified: larger consolidation diameter (odds ratio [OR], 2.35, 95% confidence interval [CI]: 1.06, 5.22, p = 0.013), bronchovascular bundle thickening (OR, 1.99, 95% CI: 1.00, 3.95, p = 0.049), lobulation (OR, 2.92, 95% CI: 1.22, 6.99, p = 0.016) and obstructive change (OR, 1.69, 95% CI: 1.17, 6.16, p = 0.020). The model showed good calibration (Hosmer-Lemeshow goodness-of-fit, p = 0.816) with an AUC of 0.821 (95% CI: 0.775, 0.853). For the validation group, the AUC was 0.788 (95% CI: 0.732, 0.806).

CONCLUSION

Our predictive model can non-invasively assess the risk of OLM in patients with clinical stage IA-IIA ADC, enable surgeons perform an individualized prediction preoperatively, and assist the clinical decision-making procedure.

Artificial intelligence-based recurrence prediction outperforms classical histopathological methods in pulmonary adenocarcinoma biopsies

INTRODUCTION

Between 10 and 50% of early-stage lung adenocarcinoma patients experience local or distant recurrence. Histological parameters such as a solid or micropapillary growth pattern are well-described risk factors for recurrence. However, not every patient presenting with such a pattern will develop recurrence. Designing a model which can more accurately predict recurrence on small biopsy samples can aid the stratification of patients for surgery, (neo-)adjuvant therapy, and follow-up.

MATERIAL AND METHODS

In this study, a statistical model on biopsies fed with histological data from early and advanced-stage lung adenocarcinomas was developed to predict recurrence after surgical resection. Additionally, a convolutional neural network (CNN)-based artificial intelligence (AI) classification model, named AI-based Lung Adenocarcinoma Recurrence Predictor (AILARP), was trained to predict recurrence, with an ImageNet pre-trained EfficientNet that was fine-tuned on lung adenocarcinoma biopsies using transfer learning. Both models were validated using the same biopsy dataset to ensure that an accurate comparison was demonstrated.

RESULTS

The statistical model had an accuracy of 0.49 for all patients when using histology data only. The AI classification model yielded a test accuracy of 0.70 and 0.82 and an area under the curve (AUC) of 0.74 and 0.87 on patch-wise and patient-wise hematoxylin and eosin (H&E) stained whole slide images (WSIs), respectively.

CONCLUSION

AI classification outperformed the traditional clinical approach for recurrence prediction on biopsies by a fair margin. The AI classifier may stratify patients according to their recurrence risk, based only on small biopsies. This model warrants validation in a larger lung biopsy cohort.

A real-world study and network pharmacology analysis of EGFR-TKIs combined with ZLJT to delay drug resistance in advanced lung adenocarcinoma

OBJECTIVE

This study aimed to explore the efficacy and safety of combining epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) with ZiLongJin Tablet (ZLJT) in delaying acquired resistance in advanced EGFR-mutant lung adenocarcinoma (LUAD) patients. Furthermore, we employed network pharmacology and molecular docking techniques to investigate the underlying mechanisms.

METHODS

A retrospective comparative study was conducted on stage IIIc/IV LUAD patients treated with EGFR-TKIs alone or in combination with ZLJT at the Second Affiliated Hospital of the Air Force Medical University between January 1, 2017, and May 1, 2023. The study evaluated the onset of TKI resistance, adverse reaction rates, safety indicators (such as aspartate aminotransferase, alanine aminotransferase, and creatinine), and inflammatory markers (neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio) to investigate the impact of EGFR-TKI combined with ZLJT on acquired resistance and prognostic indicators. Additionally, we utilized the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine, PubChem, UniProt, and Swiss Target Prediction databases to identify the active ingredients and targets of ZLJT. We obtained differentially expressed genes related to EGFR-TKI sensitivity and resistance from the Gene Expression Omnibus database using the GSE34228 dataset, which included sensitive (n = 26) and resistant (n = 26) PC9 cell lines. The "limma" package in R software was employed to detect DEGs. Based on this, we constructed a protein‒protein interaction network, performed gene ontology and KEGG enrichment analyses, and conducted pathway network analysis to elucidate the correlation between the active ingredients in ZLJT and signaling pathways. Finally, molecular docking was performed using AutoDockVina, PYMOL 2.2.0, and Discovery Studio Client v19.1.0 software to simulate spatial and energy matching during the recognition process between predicted targets and their corresponding compounds.

RESULTS

(1) A total of 89 patients were included, with 40 patients in the EGFR-TKI combined with ZLJT group (combination group) and 49 patients in the EGFR-TKI alone group (monotherapy group). The baseline characteristics of the two groups were comparable. There was a significant difference in the onset of resistance between the combination group and the monotherapy group (P < 0.01). Compared to the monotherapy group, the combination group showed a prolongation of 3.27 months in delayed acquired resistance. There was also a statistically significant difference in the onset of resistance to first-generation TKIs between the two groups (P < 0.05). (2) In terms of safety analysis, the incidence of adverse reactions related to EGFR-TKIs was 12.5% in the combination group and 14.3% in the monotherapy group, but this difference was not statistically significant (P > 0.05). There were no statistically significant differences in serum AST, ALT, CREA, TBIL, ALB and BUN levels between the two groups after medication (P > 0.05). (3) Regarding inflammatory markers, there were no statistically significant differences in the changes in neutrophil-to-lymphocyte Ratio(NLR) and Platelet-to-lymphocyte Ratio(PLR) values before and after treatment between the two groups (P > 0.05). (4) Network pharmacology analysis identified 112 active ingredients and 290 target genes for ZLJT. From the GEO database, 2035 differentially expressed genes related to resistant LUAD were selected, and 39 target genes were obtained by taking the intersection. A "ZLJT-compound-target-disease" network was successfully constructed using Cytoscape 3.7.0. GO enrichment analysis revealed that ZLJT mainly affected biological processes such as adenylate cyclase-modulating G protein-coupled receptor. In terms of cellular components, ZLJT was associated with the cell projection membrane. The molecular function primarily focused on protein heterodimerization activity. KEGG enrichment analysis indicated that ZLJT exerted its antitumor and anti-drug resistance effects through pathways such as the PI3K-Akt pathway. Molecular docking showed that luteolin had good binding activity with FOS (-9.8 kJ/mol), as did tanshinone IIA with FOS (-9.8 kJ/mol) and quercetin with FOS (-8.7 kJ/mol).

CONCLUSION

ZLJT has potential antitumor progression effects. For patients with EGFR gene-mutated non-small cell LUAD, combining ZLJT with EGFR-TKI treatment can delay the occurrence of acquired resistance. The underlying mechanisms may involve altering signal transduction pathways, blocking the tumor cell cycle, inhibiting tumor activity, enhancing cellular vitality, and improving the bioavailability of combination therapy. The combination of EGFR-TKI and ZLJT represents an effective approach for the treatment of tumors using both Chinese and Western medicine.

Prognostic Factors for Survival of Stage IB Non-small Cell Lung Cancer Patients: A 10-Year Follow-Up Retrospective Study

BACKGROUND

This study aimed to determine the prognostic factors for the long-term outcome of stage IB non-small cell lung cancer (NSCLC).

METHODS

Surgically resected patients with stage IB NSCLC diagnosed (based on TNM 8th edition) between April 2008 and December 2013 were retrospectively reviewed. The prognosis and possible risk factors among the stage IB NSCLC patients were evaluated.

RESULTS

Of the 349 patients identified for the study, 80 (22.9%) received post-surgery adjuvant chemotherapy (ACT). The median follow-up time after surgery was 123.3 months. The 10-year overall survival (OS) rate was 69.6%, and the 10-year recurrence-free survival (RFS) rate was 62.8%. The patients in this cohort were divided into three groups (T1 with visceral pleural invasion [VPI], T2a without VPI, and T2a with VPI), and no significant differences in OS or RFS were found among the groups. Furthermore, survival analysis indicated that the absence of ground-glass opacity (GGO) components portends an adverse long-term OS and RFS. In a subgroup of patients with solid nodules, age older than 65 years (hazard ratio [HR] 1.987; 95% confidence interval [CI] 1.312-3.010; p = 0.001) and ACT (HR 0.392; 95% CI 0.225-0.684; p < 0.001) were independent prognostic factors for OS, whereas lymphovascular invasion (HR 1.792; 95% CI 0.995-3.227; p = 0.052) should be considered as an independent unfavorable prognostic factor for RFS.

CONCLUSIONS

As an upstaging factor, VPI did not further stratify prognosis for the stage IB patients in our cohort. The presence of GGO components had a notable impact on a favorable prognosis in stage IB NSCLCs.

Development and validation of 18F-FDG PET/CT radiomics-based nomogram to predict visceral pleural invasion in solid lung adenocarcinoma

OBJECTIVES

This study aimed to establish a radiomics model based on 18F-FDG PET/CT images to predict visceral pleural invasion (VPI) of solid lung adenocarcinoma preoperatively.

METHODS

We retrospectively enrolled 165 solid lung adenocarcinoma patients confirmed by histopathology with 18F-FDG PET/CT images. Patients were divided into training and validation at a ratio of 0.7. To find significant VPI predictors, we collected clinicopathological information and metabolic parameters measured from PET/CT images. Three-dimensional (3D) radiomics features were extracted from each PET and CT volume of interest (VOI). Receiver operating characteristic (ROC) curve was performed to determine the performance of the model. Accuracy, sensitivity, specificity and area under curve (AUC) were calculated. Finally, their performance was evaluated by concordance index (C-index) and decision curve analysis (DCA) in training and validation cohorts.

RESULTS

165 patients were divided into training cohort (n = 116) and validation cohort (n = 49). Multivariate analysis showed that histology grade, maximum standardized uptake value (SUVmax), distance from the lesion to the pleura (DLP) and the radiomics features had statistically significant differences between patients with and without VPI (P < 0.05). A nomogram was developed based on the logistic regression method. The accuracy of ROC curve analysis of this model was 75.86% in the training cohort (AUC: 0.867; C-index: 0.867; sensitivity: 0.694; specificity: 0.889) and the accuracy rate in validation cohort was 71.55% (AUC: 0.889; C-index: 0.819; sensitivity: 0.654; specificity: 0.739).

CONCLUSIONS

A PET/CT-based radiomics model was developed with SUVmax, histology grade, DLP, and radiomics features. It can be easily used for individualized VPI prediction.

Clinical outcomes of advanced NSCLC patients with different EGFR exon 19 deletion subtypes treated with first-line tyrosine kinase inhibitors: A single-center ambispective cohort study

BACKGROUND

Clinical significance of various subtypes of epidermal growth factor receptor (EGFR) exon 19 deletion (ex19del) mutation in non-small cell lung cancer (NSCLC) remains unclear.

METHODS

We analyzed EGFR ex19del subtypes in NSCLC patients receiving first-line tyrosine kinase inhibitor (TKI) therapy at our center (January 2018-June 2022) and correlated them with median progression-free survival (mPFS) and median overall survival (mOS).

RESULTS

We identified 17 different EGFR ex19del variants in 101 patients. Between the classic (E746_A750del, 64.4%) and nonclassic groups (the rest variants), no significant difference was observed in mPFS (13.5 vs. 19.3 months, p = 0.18) or mOS (44.1 vs. 77.0 months, p = 0.06). mPFS showed no significant difference between ex19del subgroups classified based on the presence of insertion (ex19delins), starting position or length of deletion. However, patients with ex19delins starting at E746 showed longer mPFS than the others (29.7 vs. 12.5 months, p = 0.04), and patients with ex19del of 15 nucleotides had shorter mOS than the others (44.1 vs. 77.0 months, p = 0.03). In multivariate analysis, ex19delins independently predicted a better PFS (HR = 0.311, p = 0.03); however, 15 nucleotide deletion was no longer associated with OS (HR = 0.181, p = 0.11). Secondary T790M mutation incidence was significantly higher in the ex19del subgroup starting at E746 than the others (64.7% vs. 30.8%, p = 0.04).

CONCLUSIONS

Our study revealed potential differences in TKI efficacy, resistance mechanism, and prognosis of various EGFR ex19del subtypes in NSCLC, underscoring the need for precise selection of first-line therapy.

Prognostic Value of Tumor Size in Gastric Cancer: A Retrospective Cohort Study Based on SEER Database

Background. Although tumor size is regarded as the "T" stage of the tumor-node-metastasis (TNM) staging system for many solid tumors, its prognostic impact in gastric cancer remains uncertain and conflicting. Methods. We enrolled 6960 eligible patients from the Surveillance, Epidemiology, and End Results (SEER) database. The X-tile program was used to select the best cut-off value of tumor size. Then, the Kaplan-Meier method and the Cox proportional hazards model were applied to examine the efficacy of tumor size on prognostic prediction for overall survival (OS) and gastric cancer-specific survival (GCSS). The presence of nonlinear association was determined by the restricted cubic spline (RCS) model. Results. Tumor size was divided into 3 groups: small size (≤2.5 cm), medium size (2.6-5.2 cm), and large size (≥5.3 cm). After adjusting by covariates such as depth of tumor infiltration, the large and medium groups showed a worse prognosis than the small group; however, no survival difference in OS was suggested between the medium and large groups. Similarly, although there was a nonlinear relationship between tumor size and survival, increasing tumor size did not show an independent negative effect on prognosis in the RCS analysis. However, the stratified analyses proposed this 3-way cut of tumor size in prognostic prediction for patients with both inadequate lymphadenectomy and negative nodal metastasis. Conclusions. Tumor size as a prognostic predictor may not have good clinical applicability in gastric cancer. Otherwise, it was recommended for patients with both insufficient examinations of lymph nodes and stage N0 disease.

Durvalumab real-world treatment patterns and outcomes in patients with stage III non-small-cell lung cancer treated in a US community setting

Background: For eligible patients with unresectable stage III non-small-cell lung cancer, durvalumab consolidation therapy following chemoradiotherapy is the standard of care. Methods: This was a retrospective study of durvalumab-treated patients diagnosed between 1 August 2017 and 29 February 2020. Electronic health record data were assessed descriptively, with Kaplan-Meier methods used for duration of treatment and overall survival (OS). Results: Among 528 patients (median age 70 years, 51.5% male), the median duration of treatment was 7.1 months (95% CI: 6.0-9.0). Estimated 1- and 2-year OS rates were 83.5 and 64.0%, respectively, with median OS not reached. Conclusion: This study confirmed an OS benefit with durvalumab after chemoradiotherapy in a real-world setting, consistent with the results from the PACIFIC phase III clinical trial.