Analysis on risk factors of lung cancer complicated with pulmonary embolism

Characteristics and risk factors for advanced lung cancer with pulmonary embolism: A cross-sectional, case-control study

OBJECTIVES

Pulmonary embolism (PE) is a life-threatening complication that can occur in patients with lung cancer. In this study, we aimed to identify risk factors and examine the clinical characteristics of advanced lung cancer patients with PE.

METHODS

We conducted a retrospective review of patients admitted to our two hospitals between January 2020 and June 2022. The case group consisted of patients with lung cancer and PE, and a closely matched control group was included to identify risk factors. Statistical analysis was conducted using R language.

RESULTS

A total of 4957 patients were reviewed, and 162 patients (comprising 54 cases and 108 controls) were included in this study. The prevalence of lung cancer with PE in the study population was 1.08%. The majority of patients were male, and the most common histological subtype was adenocarcinoma (67%), followed by squamous cell carcinoma, small cell carcinoma, and poorly differentiated non-small cell lung cancer. The majority of patients had a high performance status (PS) score, with 50% experiencing respiratory failure (mainly hypoxia) and 33% with deep vein thrombosis (DVT). Forty-eight percent of patients were diagnosed with concurrent PE. Further analysis showed that PE was an independent predictor of poor survival, and a PS score of >1 was an independent risk factor for PE in patients with lung cancer.

CONCLUSION

Our study provides valuable insights into the epidemiology and prognosis of PE in lung cancer patients and suggests that a poor ECOG PS, which has not been previously reported, is an independent risk factor for PE.

Stratification of Risk Factors of Lung Cancer-Associated Venous Thromboembolism and Determining the Critical Point for Preemptive Intervention: A Systematic Review With Meta-analysis

Background

Several biomarkers or risk factors have been identified and several prediction models exist. The major limitations inherent in these models include cost-ineffectiveness and lack of systematic stratification of risk factors resulting in the inclusion of clinically insignificant biomarkers in the models. This review aimed to systematically stratify the risk factors of lung cancer-associated venous thromboembolism (VTE) and determine the critical point for preemptive intervention.

Methods

This systematic review was structured as per the Preferred Reporting Item for Systematic Reviews and Meta-analyses. We searched MEDLINE, PubMed, Cochrane Library, CINAHL, Academic Search Complete, and PsycINFO from the onset to June 2022. We included studies that reported the risk factors of lung cancer-associated VTE and corresponding risk estimates, irrespective of treatment status but studies were excluded if patients were on anti-VTE medications. We employed random effects models of meta-analysis and computed risk stability index and risk weight (Rw) to achieve the review objectives. The review protocol is registered with PROSPERO (CRD42022336476).

Results

The clinically significant risk factors of VTE in lung cancer patients were D-dimer (odds ratio [OR] = 5.510, 95% CI = 2.6-11.7; Rw = 5.0), albumin (OR = 2.2, 95% CI = 1.0-4.8; Rw = 1.79), leukocyte (OR = 2.48, 95% CI = 1.9-3.2; Rw = 1.77), histological type (OR = 1.69 , 95% CI = 1.2-2.4; Rw = 1.3), age (OR = 1.56; Rw = 0.99), and hemoglobin (OR = 1.85, 95% CI = 1.3-2.6; Rw = 0.92). Based on the distribution of Rw across risk factors, the critical point (upper third of the upper quartile class) was 4.5 and may mark the point at which preemptive intervention should be commenced.

Conclusions

Targeted screening for VTE in lung cancer patients could be patient-specific and should be based on a combination of the most significant risk factors required to meet the critical point, provided that such a combination is affordable as illustrated in the ALBAH model.

Registration

The review protocol is registered with PROSPERO (ID: CRD42022336476).

Change in cytokine profiles released by mast cells mediated by lung cancer-derived exosome activation may contribute to cancer-associated coagulation disorders

BACKGROUND

Coagulation disorders are a significant cause of lung cancer mortality. Although mast cells are known to play a role in coagulation abnormalities, their specific role in this process has not yet been elucidated.

METHOD

We detected mast cells in the tumor microenvironment using single-cell sequencing data and examined their correlation with thrombosis-related genes, neutrophil-related genes, neutrophil extracellular trap-related signature genes, and immune infiltration levels in lung cancer patients through bioinformatics analysis. Bone marrow mast cell uptake of exosomes isolated from the lung adenocarcinoma cell line A549, which were labeled using PKH67, was observed using confocal microscopy. Mast cell degranulation was detected by measuring the β-hexosaminidase release rate. Additionally, cytokine array analysis was performed to identify altered mediators released by bone marrow mast cells after uptake of the exosomes.

RESULTS

In our study, we found a close correlation between the proportion of mast cells in lung cancer patients and the expression levels of thrombosis-related genes and neutrophil extracellular trap signature genes, both of which play a key role in thrombophilic disorder. Moreover, we discovered that lung cancer cell-derived exosomes can be taken up by mast cells, which in turn become activated to release procoagulant mediators.

CONCLUSION

Our study shows that exosomes derived from lung cancer cells can activate mast cells to release procoagulants that may contribute to abnormal blood clotting in lung cancer patients. Video Abstract.

Derivation and External Validation of a Risk Prediction Model for Pulmonary Embolism in Patients With Lung Cancer: A Large Retrospective Cohort Study

OBJECTIVE

To investigate the risk factors of pulmonary embolism in patients with lung cancer and develop and validate a novel nomogram scoring system-based prediction model.

METHOD

We retrospectively analyzed the clinical data and laboratory characteristics of 900 patients with lung cancer who were treated, including patients with lung cancer without pulmonary embolism (LC) and patients with lung cancer with pulmonary embolism (LC  +  PE). The patients were randomly divided into derivation and internal validation groups in a 7:3 ratio. Using logistic regression analysis, a diagnostic model of the nomogram scoring system was developed by incorporating selected variables in the derivation group and validated in the internal and external validation groups (n  =  108).

RESULT

Seven variables (adenocarcinoma, stage III-IV LC, indwelling central venous catheter, chemotherapy, and the levels of serum albumin, hemoglobin, and D-dimer) were identified as valuable parameters for developing the novel nomogram diagnostic model for differentiating patients with LC and LC  +  PE. The scoring system demonstrated good diagnostic performance in the derivation (area under the curve [AUC]; 95% confidence interval [CI], 0.918; 0.893, 0.943; sensitivity, 88.5%; specificity, 80.5%), internal validation (AUC; 95% CI, 0.921; 0.884, 0.958; sensitivity, 90.5%; specificity, 80.4%), and external validation (AUC; 95% CI, 0.929; 0.875, 0.983; sensitivity; 85.0%; specificity; 87.5%) groups.

CONCLUSION

In this study, we constructed and validated a nomogram scoring system based on 7 clinical parameters. The scoring system exhibits good accuracy and discrimination between patients with LC and LC  +  PE and can effectively predict the risk of PE in patients with LC.

A new machine learning model for predicting severity prognosis in patients with pulmonary embolism: Study protocol from Wenzhou, China

Introduction

Pulmonary embolism (PE) is a common thrombotic disease and potentially deadly cardiovascular disorder. The ratio of clinical misdiagnosis and missed diagnosis of PE is very large because patients with PE are asymptomatic or non-specific.

Methods

Using the clinical data from the First Affiliated Hospital of Wenzhou Medical University (Wenzhou, China), we proposed a swarm intelligence algorithm-based kernel extreme learning machine model (SSACS-KELM) to recognize and discriminate the severity of the PE by patient's basic information and serum biomarkers. First, an enhanced method (SSACS) is presented by combining the salp swarm algorithm (SSA) with the cuckoo search (CS). Then, the SSACS algorithm is introduced into the KELM classifier to propose the SSACS-KELM model to improve the accuracy and stability of the traditional classifier.

Results

In the experiments, the benchmark optimization performance of SSACS is confirmed by comparing SSACS with five original classical methods and five high-performance improved algorithms through benchmark function experiments. Then, the overall adaptability and accuracy of the SSACS-KELM model are tested using eight public data sets. Further, to highlight the superiority of SSACS-KELM on PE datasets, this paper conducts comparison experiments with other classical classifiers, swarm intelligence algorithms, and feature selection approaches.

Discussion

The experimental results show that high D-dimer concentration, hypoalbuminemia, and other indicators are important for the diagnosis of PE. The classification results showed that the accuracy of the prediction model was 99.33%. It is expected to be a new and accurate method to distinguish the severity of PE.

Risk Factors and Impact on Outcomes of Lung Cancer Patients Concurrent with Deep Vein Thrombosis

PURPOSE

Many investigations on prognostic factors in lung cancer have been conducted; however, little is known regarding the outcomes of lung cancer cases complicated by deep vein thrombosis (DVT). This study aimed to determine the risk factors and impact on outcomes of lung cancer patients concurrent with DVT.

METHODS

Lung cancer patients who underwent lower-extremity venous ultrasound were enrolled in this study. The patients were divided into a DVT group and a non-DVT group. Demographic information, clinical characteristics, and survival were analyzed by t-test, Wilcoxon test, chi-squared test, and logistic regression analysis.

RESULTS

Of the 160 enrolled lung cancer patients, DVT was detected in 30 patients. Among the DVT group, adenocarcinoma was the most common histological type (27/30, 90.00%). Lung cancer complicated with DVT was associated with advanced stage, more severe myocardial injury, and a hypercoagulable state (P < .05). Differences in driver genes between the two groups were not significant. Radiologically, lung cancer patients with DVT were more likely to present with pericardial effusion and pleural effusion than patients without DVT (P < .05). Following multivariable logistic regression analysis, advanced stage (OR 5.368, [95%CI 1.871-18.165], P = .021), NT-proBNP >300 pg/ml (OR 5.575, [95%CI 1.733-3.722], P = .018), D-dimer >5 mg/L (OR 8.449, [95%CI 4.323-18.536], P = .004), CRP >12 mg/L (OR 6.687, [95%CI 1.967-13.617], P = .010), and serum CEA >25 ng/ml (OR 4.755, [95%CI 1.358-3.123], P = .029) were independent risk factors for adenocarcinoma complicated with DVT. Finally, survival analysis revealed that the occurrence of DVT resulted in a poorer prognosis despite anticoagulant therapy (P < .05).

CONCLUSION

DVT is a potential complication in patients with lung adenocarcinoma and could represent a prognostic marker for unfavorable outcome. It is essential to screen for DVT in high-risk adenocarcinoma patients.

Are cardiovascular comorbidities always associated with a worse prognosis in patients with lung cancer?

Many factors contribute to mortality in lung cancer, including the presence of concomitant cardiovascular disease. In the treatment of early stage of lung cancer, the presence of comorbidities and occurence of cardiotoxicity may be prognostic. The effect of cardiotoxicity of radiotherapy and chemoradiotherapy on overall survival has been documented. Acute arterial and venous thromboembolic events seem to correlate with the degree of the histological malignancy, its clinical advancement, and even with optimal cardiac treatment, they may influence the survival time. In the case of high-grade and advanced lung cancer stage especially in an unresectable stadium, the prognosis depends primarily on the factors related to the histopathological and molecular diagnosis. Electrocardiographic and echocardiographic abnormalities may be prognostic factors, as they seem to correlate with the patient's performance status as well as tumor localization and size.

Evaluation of lung toxicity with bevacizumab using the spontaneous reporting database

This study was undertaken to determine the risk of bevacizumab-induced lung toxicity, time to onset, and post hoc outcomes using the Japanese Adverse Drug Event Report database. We analysed data for the period between April 2004 and March 2021. Data on lung toxicities were extracted, and relative risk of adverse events (AEs) was estimated using the reporting odds ratio. We analysed 5,273,115 reports and identified 20,399 reports of AEs caused by bevacizumab. Of these, 1679 lung toxicities were reportedly associated with bevacizumab. Signals were detected for nine lung toxicities. A histogram of times to onset showed occurrence from 35 to 238 days, but some cases occurred even more than one year after the start of administration. Approximately 20% of AEs were thromboembolic events. Among these, pulmonary embolism was the most frequently reported and fatal cases were also reported. The AEs showing the highest fatality rates were pulmonary haemorrhage, pulmonary infarction, and pulmonary thrombosis. In conclusion, we focused on lung toxicities caused by bevacizumab as post-marketing AEs. Some cases could potentially result in serious outcomes, patients should be monitored for signs of onset of AEs not only at the start of administration, but also over a longer period of time.

Risk Assessment of Death of Tumor-Related PTE by CAR Combined with DD Detection

Objective

To investigate the risk of death in patients with tumor-related PTE (pulmonary thromboembolism) detected by CAR (C-reactive protein/albumin ratio) combined with DD (D-dimer).

Methods

The peripheral hematology and coagulation-related indexes of 109 patients with tumor-related PTE diagnosed by PTCA were retrospectively analyzed, and the differences in relationship indexes between tumor-related PTE patients with good prognosis and poor prognosis were compared and analyzed. The receiver operating characteristic curve (ROC) was used to analyze the risk of death in patients with tumor-related PTE by CAR and DD.

Results

① The values of CAR and DD in the poor prognosis group were 3.90 ± 2.69 and 21.25 ± 21.20, respectively, which were significantly higher than those in the good prognosis group (1.66 ± 1.77, 9.53 ± 3.57) (P all <0.01). ② WBC, NE and SII in tumor-related PTE patients with poor prognosis were significantly higher than those in patients with good prognosis, while Hb in patients with poor prognosis was significantly lower than that in patients with good prognosis. ③ There was a significant positive correlation between CAR and DD (P=0.018). ④ The values of CAR and DD in the death group were 4.07 ± 2.42 and 19.65 ± 20.48, respectively, which were significantly higher than those in the survival group (1.94 ± 2.12, 11.52 ± 15.84) (P all<0.05). ⑤ The results of logistic regression analysis showed that both CAR (P=0.000) and DD (P=0.031) were independent prognostic factors in patients with tumor-related PTE. ⑥ CAR combined with DD had high sensitivity (77.8%) and specificity (83.5%), and the Youden index was 0.613. ⑦ The area under the receiver operating characteristic curve of CAR combined with DD was the largest (up to 0.806).

Conclusion

CAR and DD were highly expressed in patients with poor prognosis of tumor-related PTE. CAR combined with DD detection is helpful to improve the correct assessment of the risk of death in patients with tumor-related PTE.

Intermediate risk pulmonary embolism concomitant with or without lung cancer: a wide spectrum of features

OBJECTIVES

We aimed to investigate the differences in clinical features between pulmonary embolism (PE) patients concomitant with lung cancer and without lung cancer (LC) and gain further understanding of the impact of lung cancer on pulmonary embolism.

METHODS

This retrospective study sampled 114 patients diagnosed with pulmonary embolism from January 2017 to April 2021 in the First Affiliated Hospital of Soochow University. The patients were categorized into the LC group (n = 22) or non-LC group (n = 92). Myocardial injury, coagulation and blood cell parameters, along with imaging findings, were analyzed for the two groups. The primary outcome measure was the 90-day mortality.

RESULTS

Of the 114 patients with pulmonary embolism in the present study, the 90 intermediate-risk patients were enrolled for further investigations. Compared to the non-LC group, patients in the LC group had milder myocardial injury, more severe coagulation function disorder, a higher incidence of central PE and a smaller change in diameter of the main pulmonary artery. We found that the occurrence of pericardial effusion created the risk of lung cancer in patients with pulmonary embolism, but there was no increase in the 90-day mortality for non-LC group versus LC group.

CONCLUSION

Intermediate risk PE patients concomitant with lung cancer seem to be more likely to present specific clinical features, accordingly, clinicians must pay great attention to PE patients concomitant with lung cancer and implement effective treatments to simultaneously manage the two conditions.