Thoracic Cancer最新文献

Chest wall sarcomas are rare and may exhibit aggressive behavior, posing diagnostic challenges-particularly in young adults. Although multidisciplinary treatments involving chemotherapy, radiotherapy, and surgery are recommended, prognosis remains poor. We report a case of a 43-year-old man referred with left-sided chest pain, dyspnea, and massive pleural effusion. Cytological analysis of the effusion and biopsy revealed small, round, atypical cells, and initial immunohistochemistry suggested Ewing sarcoma. During workup, the patient's symptoms worsened, tumor lysis syndrome developed, and he died on hospital day 28. Autopsy and extended immunohistochemical testing indicated small round cell sarcoma. Molecular analysis identified an echinoderm microtubule-associated protein-like 4 (EML4)-anaplastic lymphoma kinase (ALK) fusion gene. The final diagnosis was small round cell sarcoma with EML4-ALK fusion originating from the thoracic wall. This case highlights the importance of early presentation and timely diagnosis using next generation sequencing to facilitate targeted therapy for ALK-rearranged chest wall sarcomas and improve patient outcomes.

A 47-year-old woman was diagnosed with invasive thymoma 13 years ago. She had undergone repeated surgeries, as well as chemotherapy and radiation therapy. Chemotherapy was discontinued after the patient developed normocytic anemia, which was unresponsive to repeated blood transfusions. Bone marrow biopsy results revealed pure red cell aplasia (PRCA). Cyclosporine treatment led to improvement in PRCA; however, the patient died 3 years later from an invasive pneumococcal infection. The onset of thymoma-associated PRCA remains unpredictable, and a significant delay may occur between the diagnosis of the two conditions.

Background: Immune checkpoint inhibitors (ICIs) improve outcomes in non-small cell lung cancer (NSCLC) with high PD-L1 expression, but biomarkers beyond PD-L1 are limited. Smoking-related immune activation may enhance ICI efficacy, yet evidence in non-squamous NSCLC, especially among non-smokers, is sparse.

Methods: We retrospectively analyzed 74 patients with Stage IIIB-IV non-squamous NSCLC, PD-L1 ≥ 50%, and no EGFR/ALK/ROS1 mutations, treated at a tertiary center in Taiwan (2017-2023). Patients were stratified by smoking status. Treatment responses, progression-free survival (PFS), and overall survival (OS) were evaluated using RECIST v1.1, Kaplan-Meier, and Cox regression.

Results: Among 74 patients, 54 (72.9%) were smokers and 20 (27.1%) were non-smokers. Compared with non-smokers, smokers had a higher partial response rate (66.7% vs. 25.0%, p = 0.001), longer median PFS (12.8 vs. 1.4 months, p = 0.001), and improved OS (47.1 vs. 10.0 months, p = 0.011). In the non-smoker subgroup, chemoimmunotherapy significantly prolonged PFS compared with ICI monotherapy (not reached vs. 1.4 months, p = 0.034). In multivariate analysis, smoking independently predicted better PFS (HR = 0.234, p = 0.001) and OS (HR = 0.229, p = 0.011).

Conclusion: Non-smokers with PD-L1-high non-squamous NSCLC showed significantly poorer outcomes with ICI monotherapy. Chemoimmunotherapy may be preferred in this group. Smoking history may provide a simple and clinically relevant stratification factor when considering ICI-based treatment.

Objective: To analyze the effect of the holistic management model on the management of postoperative chronic cough patients with lung cancer.

Methods: A total of 197 patients were selected to receive routine perioperative health guidance from August 2021 to July 2022 and 180 patients were selected to receive the holistic management rehabilitation model from August 2022 to March 2024 by using convenience sampling method. The incidence and severity of chronic cough assessed using a visual analog scale (VAS) and the quality of life assessed by the Chinese version of the Leicester Cough Scale (LCQ-MC) were compared between the two groups, at baseline and 1, 2, and 6 months postoperatively. The effect of the total management was evaluated (assessed by the rate of loss of visit, referral, and follow-up), and adherence to total management (assessed by the Chronic Disease Self-Efficacy Scale [CDSES]) and satisfaction were investigated at the end of the 6 months of continuous postoperative management.

Results: The incidence of postoperative chronic cough in the total management group is lower than in the conventional care group (p < 0.05), and the degree of chronic cough and its impact on quality of life were better than those in the conventional care group at 2 and 6 months postoperatively, with statistically significant differences (p < 0.05).

Conclusion: The total management model is remarkably effective in managing postoperative chronic cough in patients with lung cancer, reducing the incidence of chronic cough.

Background: Esophageal cancer is a prevalent malignancy worldwide, often accompanied by dysphagia and malnutrition that necessitate long-term intravenous nutritional support. Peripherally Inserted Central Catheters (PICCs) have become a standard nursing practice to facilitate chemotherapy and parenteral nutrition in these patients. However, maintaining PICCs poses significant challenges that can affect patient adherence and outcomes.

Objective: This study aims to explore the experiences and needs of esophageal cancer patients regarding PICC maintenance after hospital discharge, with the goal of providing evidence to optimize nursing care services.

Methods: A qualitative study was conducted involving semi-structured interviews with 15 esophageal cancer patients receiving PICC care at a specialized oncology hospital in Beijing from October 2024 to January 2025. Descriptive phenomenological methods were used to analyze the data following Colaizzi's seven-step approach.

Results: Patient experiences clustered into four main themes: (1) Survival under the combined pressures of nutritional needs and chemotherapy; (2) Maintenance challenges influenced by anatomical and treatment-related factors; (3) Adherence difficulties due to symptoms and frequent hospital visits; (4) Emotional responses to dramatic physical changes and distressing symptoms.

Conclusion: Esophageal cancer patients face complex, multifaceted needs during PICC maintenance, encompassing practical care, informational support, and psychological assistance. To improve patient adaptation and quality of life, future nursing practices should focus on enhancing care techniques, developing accessible support tools, and strengthening health education strategies.

Background: With the widespread adoption of low-dose CT screening, the detection of pulmonary ground-glass nodules (GGNs) has risen markedly, presenting diagnostic challenges in distinguishing preinvasive lesions from invasive adenocarcinomas (IAC). This study aimed to develop a machine learning (ML)-based model using artificial intelligence (AI)-extracted CT radiomic features to predict the invasiveness of GGNs.

Methods: A retrospective cohort of 285 patients (148 with preinvasive lesions, 137 with IAC) from the Lingnan Campus was divided into training and internal validation sets (8:2). An independent cohort of 210 patients (118 with preinvasive lesions, 92 with IAC) from the Tianhe Campus served as external validation. Nineteen radiomic features were extracted and filtered using Boruta and LASSO algorithms. Seven ML classifiers were evaluated using AUC-ROC, decision curve analysis (DCA), and SHAP interpretability.

Results: Median CT value, skewness, 3D long-axis diameter, and transverse diameter were ultimately selected for model construction. Among all classifiers, the Gradient Boosting Machine (GBM) model achieved the best performance (AUC = 0.965 training, 0.908 internal validation, and 0.965 external validation). It demonstrated strong accuracy (88.1%), specificity (80.7%), and F1 score (0.87) in the external validation cohort. The GBM model demonstrated superior net clinical benefit. SHAP analysis identified median CT value and skewness as the most influential predictors.

Conclusion: This study presents a simplified ML model using AI-extracted radiomic features, which has strong predictive performance and biological interpretability for preoperative risk stratification of GGNs. By leveraging median CT value, skewness, 3D long-axis diameter, and transverse diameter, the model enables accurate and noninvasive differentiation between IAC and indolent lesions, supporting precise surgical planning.

Introduction: Previous studies have reported inconsistent findings regarding the associationbetween ALK and ROS1 rearrangements in lung cancer and thromboembolic risk. This retrospective study aimed to investigate this association in advanced lung adenocarcinoma patients with ALK, ROS1, RET rearrangements, and EGFR mutations.

Materials and methods: We retrospectively collected information on patients with advanced lung adenocarcinoma in the First Affiliated Hospital of Zhejiang University School of Medicine from January 2013 to March 2021. All patients with confirmed ALK, ROS1, or RET rearrangements, as well as a comparison cohort of those with EGFR mutation, were included. Clinical characteristics were analyzed, and the association between driver genes and TE risks was analyzed using competing risk and logistic regression.

Results: A total of 546 patients were included in the study. Among them, those with ROS1 rearrangements exhibited the highest cumulative incidence of thromboembolic events (TEs), reaching 17.5% ± 0.2% during the peri-diagnostic period (within 6 months following diagnosis). Regardless of the entire follow-up or the peri-diagnostic period, ROS1 rearrangements were significantly associated with an increased risk of TEs. Multivariate analysis revealed ROS1 rearrangements, the number of comorbidities, the size of mediastinal lymph nodes, and elevated C-reactive protein (CRP) levels as TE risk factors during the peri-diagnostic period. Throughout the follow-up period, ROS1 rearrangements and hypertension were independent TE risk factors. In addition, the development of TE significantly affected the overall survival of patients with EGFR mutations.

Conclusion: ROS1 rearrangements were significantly associated with an increased risk of TE.

Retraction: L. Zhao, X. Zhang, Y. Shi, and T. Teng, "LncRNA SNHG14 Contributes to the Progression of NSCLC Through miR-206/G6PD Pathway," Thoracic Cancer 11, no. 5 (2020): 1202-1210, https://doi.org/10.1111/1759-7714.13374. The above article, published online on 09 March 2020 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, Tateaki Naito; and John Wiley & Sons Australia, Ltd. The retraction has been agreed upon following concerns raised by a third party regarding the use of an incorrect primer for the SNHG14 gene. The authors were invited to provide comments and supporting data but did not respond. Given the nature of the concern, the editors consider the results and conclusions of this article invalid. The authors did not respond to our notice of retraction.

Objective: To investigate the current status of decisional conflict in lung cancer patients receiving systemic therapy and to analyze its influencing factors, with the aim of providing a basis for developing decision support strategies.

Methods: From August to September 2024, a convenience sample of 500 patients receiving systemic therapy for lung cancer at the Department of Medical Oncology, Cancer Hospital, Chinese Academy of Medical Sciences, was surveyed. Data were collected using a general information questionnaire, the Decisional Conflict Scale (DCS), Cancer Patient's Involvement in Treatment Decision-Making Scale (CPITDM), Preparation for Decision-Making Scale (PreDM), and Decisional Regret Scale (DRS).

Result: The mean DCS score was 47.28 ± 15.83, with subscale scores ranking from highest to lowest as decision support/effectiveness, decision uncertainty, and information/values. The mean CPITDM, PreDM, and DRS scores were 28.56 ± 3.91, 63.02 ± 11.65, and 9.46 ± 2.62, respectively. DCS was negatively correlated with CPITDM (r = -0.188, p < 0.001) and PreDM (r = -0.303, p < 0.001) but positively correlated with DRS (r = 0.342, p < 0.001). Multiple regression identified occupation, medical payment, treatment line, pathology, medication type, patient involvement, and preparedness as significant influencing factors (p < 0.05), explaining 59.9% of variance.

Conclusion: Lung cancer patients receiving systemic therapy experience a relatively high level of decisional conflict, with many exhibiting delayed decision-making. Healthcare providers should identify high-risk patients early based on key influencing factors and explore practical clinical decision support interventions. Enhancing decision readiness and reducing decision regret may help to improve quality of life and reduce decisional conflict.