Clinical Characteristics of Pulmonary Embolism with Underlying Malignancy

Lee, Ji Eun; Kim, Hye Ryun; Lee, Sang‐Min; Yim, Jae Joon; Yoo, Chul Gyu; Kim, Youngwhan; Han, Sang Beom; Shim, Young Soo; Yang, Seung Ho

doi:10.3904/kjim.2010.25.1.66

Cited by 13 publications

(6 citation statements)

References 23 publications

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“…This is inconsistent with trends that have been seen in previous studies, but again, the sample size was too small to draw any meaningful conclusions . The trend towards higher rates of PE in patients receiving platinum containing chemotherapy regiments is concordant with observations made in other studies …”

Section: Discussionsupporting

confidence: 90%

An analysis of incidental and symptomatic pulmonary embolism (PE) in medical oncology patients

Thaker

Douglas

Blazak

et al. 2016

Asia-Pac J Clin Oncol

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Forty percent of the diagnosed PEs were incidental, more common in the metastatic group. This may be due to the increased frequency of staging scans performed in patients with metastatic disease, as well as the inherent disease biology of metastatic compared with localized disease. Further prospective analysis of survival by PE subtype and optimal length of anticoagulation in incidental PE is warranted.

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Section: Discussionsupporting

confidence: 90%

An analysis of incidental and symptomatic pulmonary embolism (PE) in medical oncology patients

Thaker

Douglas

Blazak

et al. 2016

Asia-Pac J Clin Oncol

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“…The most prominent pathway associated with LUAD, compared to LUSC, is platelet degranulation and exocytosis (Tables 5 , 6 ). Interestingly, lung cancer is the most common malignancy to coexist with venous thromboembolism, especially pulmonary embolism 68 . LUAD, in particular, has been shown to be an independent risk factor for pulmonary embolism even among lung cancers 69 , 70 .…”

Section: Discussionmentioning

confidence: 99%

Lung adenocarcinoma and lung squamous cell carcinoma cancer classification, biomarker identification, and gene expression analysis using overlapping feature selection methods

Chen¹,

Dhahbi²

2021

Sci Rep

103

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Lung cancer is one of the deadliest cancers in the world. Two of the most common subtypes, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), have drastically different biological signatures, yet they are often treated similarly and classified together as non-small cell lung cancer (NSCLC). LUAD and LUSC biomarkers are scarce, and their distinct biological mechanisms have yet to be elucidated. To detect biologically relevant markers, many studies have attempted to improve traditional machine learning algorithms or develop novel algorithms for biomarker discovery. However, few have used overlapping machine learning or feature selection methods for cancer classification, biomarker identification, or gene expression analysis. This study proposes to use overlapping traditional feature selection or feature reduction techniques for cancer classification and biomarker discovery. The genes selected by the overlapping method were then verified using random forest. The classification statistics of the overlapping method were compared to those of the traditional feature selection methods. The identified biomarkers were validated in an external dataset using AUC and ROC analysis. Gene expression analysis was then performed to further investigate biological differences between LUAD and LUSC. Overall, our method achieved classification results comparable to, if not better than, the traditional algorithms. It also identified multiple known biomarkers, and five potentially novel biomarkers with high discriminating values between LUAD and LUSC. Many of the biomarkers also exhibit significant prognostic potential, particularly in LUAD. Our study also unraveled distinct biological pathways between LUAD and LUSC.

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“…Deep vein thrombosis (DVT) and pulmonary embolism (PE) are collectively referred to as venous thromboembolism. Notably, lung cancer, the most frequently diagnosed cancer and the leading cause of cancer death among males all over the world, and among females in more developed countries 1 , is the most common malignancy coexisting in patients with pulmonary embolism 2 , 3 , namely lung cancer is more prone to PE than other malignant tumors 4 , 5 . Undoubtedly lung cancer is a great risk factor for development of PE .…”

Section: Introductionmentioning

confidence: 99%

Lung Cancer and Pulmonary Embolism: What Is the Relationship? A Review

Shang²,

Wang

et al. 2018

J. Cancer

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Pulmonary embolism (PE) is gradually considered to be the third most common disease in the vascular disease category. Lung cancer is the most frequently diagnosed cancer and the leading cause of cancer death among males worldwide. Although initially appearing as distinct entities, lung cancer is a great risk factor for the development of PE. Pulmonary embolism is common in lung cancer patients, with a pooled incidence of 3.7%, and unsuspected pulmonary embolism (UPE) is also non-negligible with a rough rate ranging from 29.4% to 63%. Many risk factors of PE have been detected and could be classified into three categories: lung cancer-related, patient-related, and treatment-related factors. Decreased mean survival time could be significantly observed in lung cancer patients with PE or UPE compared to those only, but suspected PE has higher mortality than UPE. Prophylactic anticoagulant therapy benefit might be highest in patients with stage IV non-small cell lung cancer (NSCLC) or limited small cell lung cancer (SCLC), and heparin seems superior to warfarin for thrombotic prophylaxis. Periodically reassessing the risk-benefit ratio of anticoagulant treatment will be an efficient treatment strategy in lung cancer patients with PE.

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Clinical Characteristics of Pulmonary Embolism with Underlying Malignancy

Cited by 13 publications

References 23 publications

An analysis of incidental and symptomatic pulmonary embolism (PE) in medical oncology patients

An analysis of incidental and symptomatic pulmonary embolism (PE) in medical oncology patients

Lung adenocarcinoma and lung squamous cell carcinoma cancer classification, biomarker identification, and gene expression analysis using overlapping feature selection methods

Lung Cancer and Pulmonary Embolism: What Is the Relationship? A Review

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