With the development and improved availability of low-dose computed tomography (LDCT), an increasing number of patients are clinically diagnosed with lung cancer manifesting as ground-glass nodules. Although radical surgery is currently the mainstay of treatment for patients with early-stage lung cancer, traditional anatomic lobectomy and mediastinal lymph node dissection (MLND) are not ideal for every patient. Clinically, it is critical to adopt an appropriate approach to pulmonary lobectomy, determine whether it is necessary to perform MLND, establish standard criteria to define the scope of lymph node dissection, and optimize the decision-making process. Thereby avoiding over- and under-treatment of lung cancer with surgical intervention and achieving optimal results from clinical diagnosis and treatment are important issues before us.
Risk prediction models for postoperative pulmonary complications (PPCs) can assist healthcare professionals in assessing the likelihood of PPCs occurring after surgery, thereby supporting rapid decision-making. This study evaluated the merits, limitations, and challenges of these models, focusing on model types, construction methods, performance, and clinical applications. The findings indicate that current risk prediction models for PPCs following lung cancer surgery demonstrate a certain level of predictive effectiveness. However, there are notable deficiencies in study design, clinical implementation, and reporting transparency. Future research should prioritize large-scale, prospective, multi-center studies that utilize multiomics approaches to ensure robust data for accurate predictions, ultimately facilitating clinical translation, adoption, and promotion.
Objective Through the analysis of hospital costs of 16 866 cases of patients with lung cancer in Sichuan Province, in oder to find the main influencing factors of hospital costs of patients with lung cancer, and to provide references for reducing the hospital costs of patients with lung cancer. Methods We selected information of in-patients with lung cancer in 6 hospitals in Sichuan province from January 2008 to December 2011 based on full consideration into the local economic levels geographics distribution of different regions in Sichuan province. Then we extracted baseline data, hospitalization data and costs, and then analysis on relevant influencing factors was performed using single factor analysis of variance and multiple stepwise regression analysis. Results A total of 16 918 cases are chosen, of which, 16 866 were effective for further analysis. The results of statistical analysis showed that, the cost of western medicine accounted for the most of the average of the total hospital costs (50.79%) , followed by the cost of diagnosis and treatment (40.79%). The reuslts of multiple stepwise regression analysis showed that, the top three factors influencing hospital costs most included hospital stay, operation, and regions. Conclusion Facing daily increasing costs of hospital costs of lung cancer, effectively reducing drug expenses of patients could be a breakthrough. We could ultimately reduce the hospital costs of patients with lung cancer as well as the the economic burden of patients and society, by strengthening hospital management, shortening hospital stay, and rationally regulating drug use.
Objective
To assess the effects of physiotherapy on pulmonary function in COPD patients with lung cancer after lobectomy or pneumonectomy.
Methods
Fifty-five COPD patients with lung cancer undergoing lobectomy or pneumonectomy from January 2005 to May 2014 were recruited in the study. They were divided into group A received comprehensive physiotherapy before surgery and group B without comprehensive physiotherapy before surgery. The changes of lung function and tolerance were compared before physiotherapy (T1 time point) and after physiotherapy (T2 time point) in the group A, and between two groups before lung resection (T2 time point) and after lung resection (T3 time point).
Results
In group A, the forced expiratory volume in one second (FEV1), vital capacity (VC), peak expiratory flow at 50% of vital capacity (FEF50) and FEF25 increased significantly respectively by 16.96%, 14.75%, 20.69% and 13.79% compared with those before physiotherapy. Meanwhile, six-minutes walking distance (6MWD) achieved a significant improvement. After resection of lung, FEV1 and VC appeared to reduce, and pulmonary small airway function, tolerance, and clinical features deteriorated significantly. The differences between T2 and T1 in FEV1, FEF50 and FEF25 in the patients with FEV1%pred ≥80% and 50%-80% were similar with those in the patients with FEV1%pred<50%. The differences between T2 and T3 in FEF50 and FEF25 in the patients with FEV1%pred≥80% and 50%-80% were higher than those with FEV1%pred<50%. For the patients with lobectomy, FEV1 and VC in the group B were lower than those in the group A (FEV1: 10.24% vs. 22.44%; VC: 10.13% vs. 20.87%). For the patients with pulmonary resection, FEV1 and VC had little differences (FEV1: 36.33% vs. 36.78%; VC: 37.23% vs. 38.98%).
Conclusion
Physiotherapy is very important for the preoperative treatment and postoperative nursing of COPD patients with primary lung cancer.
ObjectiveTo systematically review the correlation between HDL-C level and lung cancer.
MethodsSuch databases as PubMed, EBSCO, ISI Web of Science, The Cochrane Library (Issue 8, 2015), VIP, and CNKI Data were electronically searched from inception to September 23th, 2015 to collect studies about the correlation between HDL level and lung cancer. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Then meta-analysis was performed using Stata 12.0 software.
ResultsFifteen studies involving 2 015 lung cancer patients and 15 505 controls were finally included. The results of meta-analysis showed that the total HDL-C level in the lung cancer group was lower than that in the control group (SMD=-0.68, 95%CI-0.97 to -0.40, P=0.000). Further subgroup analysis showed that the incidence of lung cancer of different clinical classification (SMDⅠ~Ⅱ=-0.65, 95%CI -1.07 to -0.23, P=0.002; SMDⅢ~Ⅳ=-0.61, 95%CI -0.73 to -0.50, P=0.000), different pathological types (the small cell lung cancer excluded) (SMDAC=-0.76, 95%CI -1.13 to -0.38, P=0.000; SMDSC=-1.51, 95%CI -2.47 to -0.56, P=0.010; SMDSCLC=-1.19, 95%CI -1.42 to -0.95, P=0.000), different quality scores (SMD≥6 score=-0.60, 95%CI -0.89 to -0.29, P=0.000; SMD< 6 score=-0.77, 95%CI -1.48 to -0.0, P=0.015), the number of different studies (SMD≥100 cases=-0.48, 95%CI -0.80 to -0.15, P=0.004; SMD< 100 cases=-0.80, 95%CI -1.33 to -0.27, P=0.003), smoking (SMD=-1.47, 95%CI -2.51 to -0.43, P=0.006) and Asia (SMD=-0.92, 95%CI -1.21 to -0.63, P=0.000) was correlated with the level of HDL-C.
ConclusionThe level of HDL-C is related to the incidence of lung cancer, and low HDL-C level may increase the risk of lung cancer. In view of the limitations of the studies, the above conclusions need a great many large samples and adjust the smoking status of the prospective cohort study at home and abroad to verify.
Objective To establish a machine learning-based risk prediction model of combined chronic obstructive pulmonary disease (COPD) with lung cancer, so as to explore the high risk factors for COPD patients with lung cancer and to lay the foundation for early detection of lung cancer risk in COPD patients. Methods A total of 154 patients from the Second Hospital of Dalian Medical University from 2010 to 2021 were retrospectively analyzed, including 99 patients in the COPD group and 55 patients in the COPD with lung cancer group. the chest high resolution computed tomography (HRCT) scans and pulmonary function test of each patient were acquired. The main analyses were as follow: (1) to valid the statistically differences of the basic information (such as age, body mass index, smoking index), laboratory test results, pulmonary function parameters and quantitative parameters of chest HRCT between the two groups; (2) to analyze the indicators of high risk factors for lung cancer in COPD patients using univariate and binary logistic regression (LR) methods; and (3) to establish the machine learning model (such as LR and Gaussian process) for COPD with lung cancer patients. Results Based on the statistical analysis and LR methods, decreased BMI, increased whole lung emphysema index, increased whole lung mean density, and increased percentage activity of exertional spirometry and prothrombin time were risk factors for COPD with lung cancer patients. Based on the machine learning prediction model for COPD with lung cancer patients, the area under the receiver operating characteristic curve for LR and Gaussian process were obtained as 0.88 using the soluble fragments of prothrombin time percentage activity, whole lung emphysema index, whole lung mean density, and forced vital capacity combined with neuron-specific enolase and cytokeratin 19 as features. Conclusion The prediction model of COPD with lung cancer patients using a machine learning approach can be used for early detection of lung cancer risk in COPD patients.
ObjectiveTo systematically review the incidence of adverse skin reactions in lung cancer patients treated by immunotherapy. MethodsPubMed, Web of Science, The Cochrane Library, CNKI, WanFang Data and VIP databases were electronically searched to collect the studies on the incidence of skin adverse reactions in lung cancer patients treated with immunotherapy from June 2011 to June 2021. Two reviewers independently screened literature, extracted data and assessed the risk bias of the included studies. Meta-analysis was then performed by using Stata 15.0 software. ResultsA total of 63 studies were included, with a total sample size of 13 386 cases. The results of meta-analysis showed that the overall incidence of adverse skin reactions in lung cancer patients was 14.0% (95%CI 11.6% to 16.5%). ConclusionCurrent evidence shows that the incidence of adverse skin reactions in lung cancer patients with immunotherapy is high. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusions.
The TNM staging of lung cancer which is now widely used in clinic was formally proposed in 1997. It has played quite an important role in directing the diagnosis and treatment of lung cancer as well as the clinical research in the past decade. However, at the same time, there are some insufficiencies which are emerging gradually. By collecting the clinical information from 100 869 patients, in 2007, International Association for the Study of Lung Cancer(IASLC) made a deep analysis on the relativity between TNM staging and prognosis, and put forward the suggestions to revise the Seventh Edition of the TNM staging of lung cancer: (1) According to the size of tumor, the primary T staging is divide into T1a (the maximum tumor diameter≤2 cm), T1b (3 cm≥the maximum tumor diameter＞2 cm), T2a (5 cm≥the maximum tumor diameter＞3 cm) and T2b (7 cm≥the maximum tumor diameter＞5 cm); (2) T 2c (the maximum tumor diameter gt;7 cm) and additional nodules in the same lobe are classified as T3, while nodules in the ipsilateral nonprimary lobe are classified as T4;(3) Cancerous hydrothorax, pericardial effusion and the additional nodules in the contralateral lung are classified as M1a, while the extrapulmonary metastases are classified as M1b. It is believed that the new revised edition will has higher international authority and identification degree, and it will play a more meticulous and accurate guiding role in the treatment of lung cancer and its predicting prognosis in the future. At the same time, it will provide a new starting point to the research of lung cancer.
Increasing evidence suggests that there is a close relationship between pulmonary ground-glass opacity (GGO) and early-stage lung cancer, especially bronchial alveolar carcinoma in the early stage. With the use of high-resolution computed tomography (HRCT) and positron emission tomography/computed tomography (PET/CT), more and more GGO patients have been identified. Correct diagnosis and surgical indications should be determined according to the image characteristics including proportion and size of GGO in a pulmonary nodule as well as intraoperative quick pathological examination to avoid unnecessary surgical resection. Therefore, early detection and correct diagnosis of GGO are very important to improve patient prognosis.
Objective To study the risk factors of lung cancer and provide scientific evidence for preventing and managing such disease. Methods?The database of MEDLINE, CNKI, and CBM were searched and literature domestically and internationally from January 1997 to January 2007 was collected. The RevMan 4.2 software was used for meta-analysis. Results A total of 40 studies involving 16 559 cases and 25 119 controls were included. The pooled OR values and population attributable risk percentage (PARP) for smoking, female passive smoking from husband, female passive smoking from colleague, chronic bronchitis, emphysema, pulmonary tuberculosis, family history of cancer, and family history of lung cancer were 5.75 (69.16%), 1.32 (14.52%), 1.21 (5.87%), 1.68 (7.45%), 2.70 (10.18%), 1.58 (1.91%), 1.24 (8.92%), and 1.59 (5.33%), respectively. Conclusion Risk factors related to the incidence of lung cancer are smoking, female passive smoking from husband and colleague, chronic bronchitis, emphysema, pulmonary tuberculosis, family history of cancer, family history of lung cancer and so on. Besides, the results of PARP indicate that smoking is the most important factor, followed by female passive smoking from husband, emphysema, family history of cancer sequentially, which suggest that environmental and genetic factors play important roles in the development of lung cancer.
