The latest medical research on Lung Cancer

The research magnet gathers the latest research from around the web, based on your specialty area. Below you will find a sample of some of the most recent articles from reputable medical journals about lung cancer gathered by our medical AI research bot.

The selection below is filtered by medical specialty. Registered users get access to the Plexa Intelligent Filtering System that personalises your dashboard to display only content that is relevant to you.

Want more personalised results?

Request Access

Concomitant osimertinib and antituberculosis therapy in an elderly patient with EGFR-mutated lung cancer and pulmonary tuberculosis: A case report.

Thoracic Cancer

The concurrent incidence of lung cancer and tuberculosis is expected to escalate due to the projected growth in the older population. Combination t...

Comparison of SP263 and 22C3 pharmDx assays to test programmed death ligand-1 (PD-L1) expression in surgically resected non-small cell lung cancer.

Thoracic Cancer

Atezolizumab, one of the immune checkpoint inhibitors, has been approved as an adjuvant treatment following resection and platinum-based chemotherapy in patients with stage II-IIIA non-small cell lung cancer with 1% or more programmed death ligand-1 (PD-L1) expression. The Food and Drug Administration (FDA) has approved SP263 as a companion diagnostic assay for adjuvant treatment with atezolizumab; however, in clinical practice, the 22C3 assay is most commonly used for advanced non-small cell lung cancer. Therefore, our study aimed to compare two PD-L1 assays, SP263 and 22C3, to evaluate whether 22C3 could replace SP263 when deciding whether to administer adjuvant atezolizumab.

We retrospectively and prospectively analyzed 98 patients who underwent surgical resection at Kanagawa Cancer Center (Japan). An immunohistochemistry assay was performed for all the cases with both SP263 and 22C3. We statistically analyzed the concordance of PD-L1 expression between SP263 and 22C3 assays.

The concordance between the two assays using Cohen's kappa was κ = 0.670 (95% CI: 0.522-0.818) at the 1% cutoff and κ = 0.796 (95% CI: 0.639-0.954) at the 50% cutoff. The Spearman correlation coefficient of 0.874 (p < 0.01) indicated high concordance. PD-L1 expression with 22C3 resulted slightly higher than that with SP263.

This study showed a high concordance of PD-L1 expression with the SP263 and 22C3 assays. Further studies examining the therapeutic effects of adjuvant atezolizumab are required.

Pulmonary pleomorphic carcinoma arising in mixed squamous and glandular papilloma: A case report.

Thoracic Cancer

Solitary pulmonary papillomas (SPPs) are rare lung neoplasms. Histologically, SPP is classified into three subtypes, and mixed squamous and glandul...

Efficiency of endoscopic artificial intelligence in the diagnosis of early esophageal cancer.

Thoracic Cancer

The accuracy of artificial intelligence (AI) and experts in diagnosing early esophageal cancer (EC) and its infiltration depth was summarized and analyzed, thus identifying the advantages of AI over traditional manual diagnosis, with a view to more accurately assisting doctors in evaluating the patients' conditions and improving their cure and survival rates.

The PubMed, EMBASE, Cochrane, Google, and CNKI databases were searched for relevant literature related to AI diagnosis of early EC and its invasion depth published before August 2023. Summary analysis of pooled sensitivity, specificity, summary receiver operating characteristics (SROC) and area under the curve (AUC) of AI in diagnosing early EC were performed, and Review Manager and Stata were adopted for data analysis.

A total of 19 studies were enrolled with a low to moderate total risk of bias. The pooled sensitivity of AI for diagnosing early EC was markedly higher than that of novices and comparable to that of endoscopists. Moreover, AI predicted early EC with markedly higher AUCs than novices and experts (0.93 vs. 0.74 vs. 0.89). In addition, pooled sensitivity and specificity in the diagnosis of invasion depth in early EC were higher than that of experts, with AUCs of 0.97 and 0.92, respectively.

AI-assistance can diagnose early EC and its infiltration depth more accurately, which can help in its early intervention and the customization of personalized treatment plans. Therefore, AI systems have great potential in the early diagnosis of EC.

A novel evaluation model of image registration for cone-beam computed tomography guided lung cancer radiotherapy.

Thoracic Cancer

The aim of the study was to establish a weighted comprehensive evaluation model (WCEM) of image registration for cone-beam computed tomography (CBCT) guided lung cancer radiotherapy that considers the geometric accuracy of gross target volume (GTV) and organs at risk (OARs), and assess the registration accuracy of different image registration methods to provide clinical references.

The planning CT and CBCT images of 20 lung cancer patients were registered using diverse algorithms (bony and grayscale) and regions of interest (target, ipsilateral, and body). We compared the coverage ratio (CR) of the planning target volume (PTVCT) to GTVCBCT, as well as the dice similarity coefficient (DSC) of the GTV and OARs, considering the treatment position across various registration methods. Furthermore, we developed a mathematical model to assess registration results comprehensively. This model was evaluated and validated using CRFs across four automatic registration methods.

The grayscale registration method, coupled with the registration of the ipsilateral structure, exhibited the highest level of automatic registration accuracy, the DSC were 0.87 ± 0.09 (GTV), 0.71 ± 0.09 (esophagus), 0.74 ± 0.09 (spinal cord), and 0.91 ± 0.05 (heart), respectively. Our proposed WCEM proved to be both practical and effective. The results clearly indicated that the grayscale registration method, when applied to the ipsilateral structure, achieved the highest CRF score. The average CRF scores, excellent rates, good rate and qualification rates were 58 ± 26, 40%, 75%, and 85%, respectively.

This study successfully developed a clinically relevant weighted evaluation model for CBCT-guided lung cancer radiotherapy. Validation confirmed the grayscale method's optimal performance in ipsilateral structure registration.

Automated CT quantification of interstitial lung abnormality in patients with resectable stage I non-small cell lung cancer: Prognostic significance.

Thoracic Cancer

In patients with non-small cell lung cancer (NSCLC), interstitial lung abnormalities (ILA) have been linked to mortality and can be identified on computed tomography (CT) scans. In the present study we aimed to evaluate the predictive value of automatically quantified ILA based on the Fleischner Society definition in patients with stage I NSCLC.

We retrospectively reviewed 948 patients with pathological stage I NSCLC who underwent pulmonary resection between April 2009 and October 2022. A commercially available deep learning-based automated quantification program for ILA was used to evaluate the preoperative CT data. The Fleischner Society definition, quantitative results, and interdisciplinary discussion led to the division of patients into normal and ILA groups. The sum of the fibrotic and nonfibrotic ILA components constituted the total ILA component and more than 5%.

Of the 948 patients with stage I NSCLC, 99 (10.4%) patients had ILA. Shorter overall survival and recurrence-free survival was associated with the presence of ILA. After controlling for confounding variables, the presence of ILA remained significant for increased risk of death (hazard ratio [HR] = 3.09; 95% confidence interval [CI]: 1.91-5.00; p < 0.001) and the presence of ILA remained significant for increased recurrence (HR = 1.96; 95% CI: 1.16-3.30; p = 0.012).

The automated CT quantification of ILA, based on the Fleischner Society definition, was significantly linked to poorer survival and recurrence in patients with stage I NSCLC.

A liquid biopsy assay for the noninvasive detection of lymph node metastases in T1 lung adenocarcinoma.

Thoracic Cancer

Lung adenocarcinoma (LUAD) is a common pathological type of lung cancer. The presence of lymph node metastasis plays a crucial role in determining the overall treatment approach and long-term prognosis for early LUAD, therefore accurate prediction of lymph node metastasis is essential to guide treatment decisions and ultimately improve patient outcomes.

We performed transcriptome sequencing on T1 LUAD patients with positive or negative lymph node metastases and combined this data with The Cancer Genome Atlas Program cohort to identify potential risk molecules at the tissue level. Subsequently, by detecting the expression of these risk molecules by real-time quantitative PCR in serum samples, we developed a model to predict the risk of lymph node metastasis from a training cohort of 96 patients and a validation cohort of 158 patients.

Through transcriptome sequencing analysis of tissue samples, we identified 11 RNA (miR-412, miR-219, miR-371, FOXC1, ID1, MMP13, COL11A1, PODXL2, CXCL13, SPOCK1 and MECOM) associated with positive lymph node metastases in T1 LUAD. As the expression of FOXC1 and COL11A1 was not detected in serum, we constructed a predictive model that accurately identifies patients with positive lymph node metastases using the remaining nine RNA molecules in the serum of T1 LUAD patients. In the training set, the model achieved an area under the curve (AUC) of 0.89, and in the validation set, the AUC was 0.91.

We have established a new risk prediction model using serum samples from T1 LUAD patients, enabling noninvasive identification of those with positive lymph node metastases.

Historical trends of breast cancer burden attributable to metabolic factors among Chinese women, 1990-2019: A population-based epidemiological study.

Thoracic Cancer

 This study aims to analyze breast cancer burden attributable to high body mass index (BMI) and high fasting plasma glucose (FPG) in China from 1990 to 2019.

Data were obtained from the Global Burden of Disease (GBD) study 2019. Deaths and disability-adjusted life years (DALYs) were used for attributable burden, and age-period-cohort (APC) model was used to evaluate the independent effects of age, period and birth cohort.

In 2019, the age-standardized mortality and DALY rates of breast cancer attributable to high BMI were 1.107 (95% UI: 0.311, 2.327) and 29.990 (8.384, 60.713) per 100 000, and mortality and DALY rates attributable to high FPG were 0.519 (0.095, 1.226) and 13.662 (2.482, 32.425) per 100 000. From 1990 to 2019, the age-standardized mortality and DALY rates of breast cancer attributable to high BMI increased by 1.192% and 1.180%, and the trends of high FPG were not statistically significant. The APC results showed that the age effects of high BMI and high FPG-mortality and DALY rates increased, with the highest rates in the age group over 80 years. The birth cohort effects of high BMI showed "inverted V" shapes, while high FPG showed downward trends.

Age was the main reason for the increase of attributable burden, and postmenopausal women were the high-risk groups. Therefore, targeted prevention measures should be developed to improve postmenopausal women's awareness and effectively reduce the prevalence of obesity and diabetes, thereby reducing the breast cancer burden caused by metabolic factors in China.

Long-term survival of a patient with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) and untreated multiple brain metastases treated with zorifertinib: A case report.

Thoracic Cancer

Brain metastases (BM) are common in patients with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) and confer poor...

Exploring previously used thresholds for computed tomography-defined low skeletal muscle mass in predicting functional limitations among lung cancer patients.

Thoracic Cancer

Various cutoffs have been used to diagnose computed tomography (CT)-defined low skeletal muscle mass; however, the impact of this variability on predicting physical functional limitations (PFL) remains unclear. In the present study we aimed to evaluate the diagnostic test metrics for predicting PFLs using a fixed cutoff value from previous reports and sought to create a prediction score that incorporated the skeletal muscle index (SMI) and other clinical factors.

In this cross-sectional study including 237 patients with lung cancer, the SMI was assessed using CT-determined skeletal muscle area at the third lumbar vertebra. Physical function was assessed using the short physical performance battery (SPPB) test, with PFL defined as an SPPB score ≤9. We analyzed the diagnostic metrics of the five previous cutoffs for CT-defined low skeletal muscle mass in predicting PFL.

The mean age of participants was 66.0 ± 10.4 years. Out of 237 patients, 158 (66.7%) had PFLs. A significant difference was observed in SMI between individuals with and without PFLs (35.7 cm2/m2 ± 7.8 vs. 39.5 cm2/m2 ± 8.4, p < 0.001). Diagnostic metrics of previous cutoffs in predicting PFL showed suboptimal sensitivity (63.29%-91.77%), specificity (11.39%-50.63%), and area under the receiver operating characteristic curve (AUC) values (0.516-0.592). Age and the SMI were significant predictors of PFL; therefore, a score for predicting PFL (age - SMI + 21) was constructed, which achieved an AUC value of 0.748.

Fixed cutoffs for CT-defined low skeletal muscle mass may inadequately predict PFLs, potentially overlooking declining physical functions in patients with lung cancer.

Endotracheal enucleation and para-toluenesulfonamide injection for adenoid cystic carcinoma in the upper trachea: A novel therapeutic approach.

Thoracic Cancer

We present a case of an adenoid cystic carcinoma (ACC) located in the upper trachea, which resulted in significant airway blockage, that was unsuit...

Circulating SMRP and CA-125 before and after pleurectomy decortication for pleural mesothelioma.

Thoracic Cancer

Tumor recurrence remains the main barrier to survival after surgery for pleural mesothelioma (PM). Soluble mesothelin-related protein (SMRP) and cancer antigen 125 (CA-125) are established blood-based biomarkers for monitoring PM. We prospectively studied the utility of these biomarkers after pleurectomy decortication (PD).

Patients who underwent PD and achieved complete macroscopic resection with available preoperative SMRP levels were included. Tumor marker levels were determined within 60 days of three timepoints: (1) preoperation, (2) post-operation, and (3) recurrence.

Of 356 evaluable patients, 276 (78%) had recurrence by the end of follow-up interval. Elevated preoperative SMRP levels were associated with epithelioid histology (p < 0.013), advanced TNM (p < 0.001) stage, and clinical stage (p < 0.001). Preoperative CA-125 levels were not significantly associated with clinical covariates. Neither biomarker was associated with survival or disease-free survival. With respect to nonpleural and nonlymphatic recurrences, mean SMRP levels were elevated in patients with pleural (p = 0.021) and lymph node (p = 0.042) recurrences. CA-125 levels were significantly higher in patients with abdominal (p < 0.001) and lymph node (p = 0.004) recurrences. Among patients with all three timepoints available, we observed an average decrease in SMRP levels by 1.93 nmol/L (p < 0.001) postoperatively and again an average increase at recurrence by 0.79 nmol/L (p < 0.001). There were no significant changes in levels of CA-125 across the study timepoints (p = 0.47).

Longitudinal changes in SMRP levels corresponded with a radiographic presence of disease in a subset of patients. SMRP surveillance could aid in detection of local recurrences, whereas CA-125 could be helpful in recognizing abdominal recurrences.