Lung nodule in patients with extrathoracic primary cancer-not always what it seems.
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ABSTRACT:
SUBMITTER: Sponholz S
PROVIDER: S-EPMC10586952 | biostudies-literature | 2023 Sep
REPOSITORIES: biostudies-literature
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Lung nodule in patients with extrathoracic primary cancer-not always what it seems.
Journal of thoracic disease 20230906 9
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Project description:Traumatic lung herniation is an uncommon complication of blunt chest trauma due to seatbelt injury. High index of suspicion, adherence to ATLS guidelines, and cooperation between different surgical specialties for the prompt stabilization of flail chest and primary or prosthetic closure of the defect may ensure a favorable outcome.
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Project description:Stage IV non-small cell lung cancer (NSCLC) accounts for 35 to 40% of newly diagnosed cases of NSCLC. The oligometastatic state-≤5 extrathoracic metastatic lesions in ≤3 organs-is present in ~25% of patients with stage IV disease and is associated with markedly improved outcomes. We retrospectively identified patients with extrathoracic oligometastatic NSCLC who underwent primary tumor resection at our institution from 2000 to 2018. Event-free survival (EFS) and overall survival (OS) were estimated using the Kaplan-Meier method. Factors associated with EFS and OS were determined using Cox regression. In total, 111 patients with oligometastatic NSCLC underwent primary tumor resection; 87 (78%) had a single metastatic lesion. Local consolidative therapy for metastases was performed in 93 patients (84%). Seventy-seven patients experienced recurrence or progression. The five-year EFS was 19% (95% confidence interval (CI), 12-29%), and the five-year OS was 36% (95% CI, 27-50%). Factors independently associated with EFS were primary tumor size (hazard ratio (HR), 1.15 (95% CI, 1.03-1.29); p = 0.014) and lymphovascular invasion (HR, 1.73 (95% CI, 1.06-2.84); p = 0.029). Factors independently associated with OS were neoadjuvant therapy (HR, 0.43 (95% CI, 0.24-0.77); p = 0.004), primary tumor size (HR, 1.18 (95% CI, 1.02-1.35); p = 0.023), pathologic nodal disease (HR, 1.83 (95% CI, 1.05-3.20); p = 0.033), and visceral-pleural invasion (HR, 1.93 (95% CI, 1.10-3.40); p = 0.022). Primary tumor resection represents an important treatment option in the multimodal management of extrathoracic oligometastatic NSCLC. Encouraging long-term survival can be achieved in carefully selected patients, including those who received neoadjuvant therapy and those with limited intrathoracic disease.
| S-EPMC8071146 | biostudies-literature
Project description:Metastatic non-small cell lung cancer (NSCLC) continues to have a poor prognosis despite recent advances in both targeted radiotherapy methodologies such as stereotactic body radiotherapy (SBRT) and immunotherapies. The impact of location of metastatic disease in patients with NSCLC has not been investigated; we aimed to investigate this using the Surveillance, Epidemiology, and End Results (SEER) database.We included 39,910 patients from the SEER database treated for M1b NSCLC from 2010-2013. We identified patients with metastatic disease in the brain, lung, liver, and bone. We used Kaplan-Meier analyses and Cox proportional hazards models to assess the impact of varying sites of metastatic disease on overall survival (OS).Patients with disease coded as in the brain without other disease in the lung, liver, or bone had improved OS relative to all other comers with M1b disease (HR =0.84, 95% CI, 0.84-0.90, P<0.001). Likewise, patients with disease coded as in the bone without other disease in the lung, liver, or brain had improved OS relative to all other comers with M1b disease (HR =0.89, 95% CI, 0.86-0.92, P<0.001).This hypothesis-generating analysis suggests that patients with limited metastatic NSCLC to the bone or brain may particularly benefit from aggressive upfront therapies.
| S-EPMC5543004 | biostudies-other
Project description:We developed a computer-aided diagnosis (CADx) method for classification between benign nodule, primary lung cancer, and metastatic lung cancer and evaluated the following: (i) the usefulness of the deep convolutional neural network (DCNN) for CADx of the ternary classification, compared with a conventional method (hand-crafted imaging feature plus machine learning), (ii) the effectiveness of transfer learning, and (iii) the effect of image size as the DCNN input. Among 1240 patients of previously-built database, computed tomography images and clinical information of 1236 patients were included. For the conventional method, CADx was performed by using rotation-invariant uniform-pattern local binary pattern on three orthogonal planes with a support vector machine. For the DCNN method, CADx was evaluated using the VGG-16 convolutional neural network with and without transfer learning, and hyperparameter optimization of the DCNN method was performed by random search. The best averaged validation accuracies of CADx were 55.9%, 68.0%, and 62.4% for the conventional method, the DCNN method with transfer learning, and the DCNN method without transfer learning, respectively. For image size of 56, 112, and 224, the best averaged validation accuracy for the DCNN with transfer learning were 60.7%, 64.7%, and 68.0%, respectively. DCNN was better than the conventional method for CADx, and the accuracy of DCNN improved when using transfer learning. Also, we found that larger image sizes as inputs to DCNN improved the accuracy of lung nodule classification.
| S-EPMC6063408 | biostudies-literature
Project description:Lung cancer is the leading cause of cancer-related deaths mainly attributable to metastasis, especially extrathoracic metastasis. This large-cohort research is aimed to explore metastatic profiles in different histological types of lung cancer, as well as to assess clinicopathological and survival significance of diverse metastatic lesions. Lung cancer cases were extracted and enrolled from the Surveillance, Epidemiology, and End Results (SEER) database. χ2-tests were conducted to make comparisons of metastatic distribution among different histological types and odds ratios were calculated to analyze co-occurrence relationships between different metastatic lesions. Kaplan-Meier methods were performed to analyze survival outcomes according to different metastatic sites and Cox regression models were conducted to identify independent prognostic factors. In total, we included 159,241 lung cancer cases with detailed metastatic status and complete follow-up information. In order to understand their metastatic patterns, we elucidated the following points in this research: (1) Comparing the frequencies of different metastatic lesions in different histological types. The frequency of bone metastasis was highest in adenocarcinoma, squamous cell carcinoma, LCLC and NSCLC/NOS, while liver was the most common metastatic site in SCLC. (2) Elaborating the tendency of combined metastases. Bi-site metastases occurred more common than tri-site and tetra-site metastases. And several metastatic sites, such as bone and liver, intended to co-metastasize preferentially. (3) Clarifying the prognostic significance of single-site and bi-site metastases. All single-site metastases were independent prognostic factors and co-metastases ended up with even worse survival outcomes. Thus, our findings would be beneficial for research design and clinical practice.
| S-EPMC7248315 | biostudies-literature
Project description:BackgroundDifferential diagnosis of single-nodule pulmonary metastasis (SNPM) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC) prior to lung surgery is relatively complex. Radiomics is an emerging technique for image information analysis, while it has not yet been applied to construct a differential diagnostic model between SNPM and SPLC in patients with CRC. In the present study, we aimed to extract radiomics signatures from thin-section computed tomography (CT) images of the chest. These radiomics signatures were combined with clinical features to construct a composite differential diagnostic model.MethodA total of 91 patients with CRC, including 66 patients with SNPM and 25 patients with SPLC, were enrolled in this study. Patients were randomly assigned to the training cohort (n = 63) and validation cohort (n = 28) at a ratio of 7 to 3. Moreover, 107 radiomics features were extracted from the chest thin-section CT images. The least absolute shrinkage and selection operator (LASSO) regression was used to filter these features, and clinical features were screened by univariate analysis. The screened radiomics and clinical features were combined to construct a multifactorial logistic regression composite model. The receiver operating characteristic (ROC) curves were adopted to evaluate the models, and the corresponding nomograms were created.ResultsA series of 6 radiomics characteristics was screened by LASSO. After univariate logistic regression analysis, the composite model finally included 4 radiomics features and 4 clinical features. In the training cohort, the area under the curve scores of ROC curves were 0.912 (95% confidence interval [CI]: 0.813-0.969), 0.884 (95% CI: 0.778-0.951), and 0.939 (95% CI: 0.848-0.984) for models derived from radiomics, clinical, and combined features, respectively. Similarly, these values were 0.756 (95% CI: 0.558-0.897), 0.888 (95% CI: 0.711-0.975), and 0.950 (95% CI: 0.795-0.997) in the validation cohort, respectively.ConclusionsWe constructed a model for differential diagnosis of SNPM and SPLC in patients with CRC using radiomics and clinical features. Moreover, our findings provided a new assessment tool for patients with CRC in the future.
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Project description:BackgroundLocal treatment (LT) such as radiotherapy and metastasectomy on metastatic sites may improve outcomes in oligometastatic NSCLC patients, but more data are necessary to support LT in oligometastatic diseases. Patients with single extrathoracic metastatic lesion are more likely to benefit from local therapy. In this study, we evaluated the impact of LT in NSCLC patients with a single extrathoracic metastatic lesion.MethodsData were obtained from the Korean Association for Lung Cancer Registry (KALC-R), a database created using a retrospective sampling survey by the Korean Central Cancer Registry (KCCR) and the Lung Cancer Registration Committee.ResultsA total of 787 NSCLC patients with a single extrathoracic metastatic lesion were evaluated. In the multivariate analysis for OS, age, female sex, poor performance score, squamous histological subtype, LT, and initial treatment modality showed significant associations. Regarding LT, groups that underwent curative LT were significantly associated with better OS compared to groups that did not undergo LT (p = 0.011, HR 0.448, 95% CI: 0.242-0.829). In the multivariate analysis of patients who underwent LT, poor performance score, initial treatment modality, and T stage were independently associated with poor OS. Compared to the T1 stage, T3 stage showed an HR of 2.470 (95% CI: 1.309-4.663; p = 0.005) and T4 stage showed an HR of 2.063 (95% CI: 1.093-3.904; p = 0.026).ConclusionIn NSCLC with a single extrathoracic metastatic lesion, LT, especially for curative purposes, has an independent association with OS. Moreover, among the patients who received LT, factors such as T stage, poor performance score, and initial treatment modality were significantly associated with OS.
| S-EPMC9058316 | biostudies-literature
Project description:Publications of the final results of the two largest randomized lung cancer screening (LCS) trials in the United States and Europe confirmed the reduction in the mortality rate associated with the use of screening with low-dose computed tomography (LDCT). Results of these trials led to widespread acceptance of LCS in properly defined high-risk populations, and its implementation in the clinical practice. Many countries started preparation for national LCS and refreshed still open debate about lung nodule management. Detection of lung cancer in the early stage with a reduction of lung cancer mortality requires dedicated programs with optimized protocols, including a specified pulmonary nodule diagnostic algorithm. The screening protocol should be clear with a precise nodule diameter or volume threshold, based on which a positive screen result is defined. The application of risk-prediction models and the introduction of the semiautomated assessment of detected nodules improves screening accuracy and should be applied in LCS protocols as verified tools to aid radiological diagnosis. In this review, we have summarized recent data about the radiological protocols from the most important LCS programs and pulmonary diagnostic algorithms. These protocols should be taken into consideration in the ongoing and planned LCS programs.
| S-EPMC7947388 | biostudies-literature
Project description:BackgroundIncreased patient survivorship following initial primary lung cancer (IPLC) diagnosis and treatment has uncovered new clinical challenges as individuals post-IPLC are at growing subsequent risk of developing second primary lung cancer (SPLC). Proper SPLC surveillance guidelines aimed at monitoring IPLC survivors are crucial to enhancing health outcomes. This study aims to categorize risk factors associated with SPLC emergence in IPLC survivors for clinical use following IPLC treatment.Materials and methodsUsing the Karmanos Cancer Institute Tumor Registry, patients diagnosed with IPLC from 2000 to 2017 were identified. Patients diagnosed with SPLC were matched to individuals who did not develop SPLC. Logistic and Cox regression analyses were performed to identify risk factors for SPLC emergence and overall survival (OS).ResultsOne hundred twenty-one patients diagnosed with IPLC who later developed SPLC were identified and compared with 120 patients with IPLC who did not develop SPLC. Several factors such as stage at first diagnosis, histology, age, and smoking history were not associated with SPLC risk. The median time to SPLC was 1.79 years. Patients who were treated with surgical resection had a significantly higher probability of developing SPLC. After correcting for potential immortal time bias, the median OS was 3.63 years (95% confidence interval [CI], 3.05-5.00) and 7.31 years (95% CI, 4.62-10.90) for SPLC and no SPLC groups, respectively.ConclusionThis study uncovered notable associations and lack thereof between several competing SPLC risk factors, as well as mortality. Further characterization of SPLC risk factors is essential for enhancing surveillance recommendations.
| S-EPMC8536802 | biostudies-literature