Models for predicting venous thromboembolism in ambulatory patients with lung cancer: a systematic review protocol
Introduction: Venous thromboembolism (VTE) is a common complication in patients with cancer and has a determining role in the disease prognosis. The risk is significantly increased with certain types of cancer, such as lung cancer. Partly due to difficulties in managing haemorrhage in outpatient settings, anticoagulant prophylaxis is only recommended for ambulatory patients at high risk of VTE. This requires a precise VTE risk assessment in individual patients. Although VTE risk assessment models have been developed and updated in recent years, there are conflicting reports on the effectiveness of such risk prediction models in patient management. The aim of this systematic review is to gain a better understanding of the available VTE risk assessment tools for ambulatory patients with lung cancer and compare their predictive performance.
Methods and analysis: A systematic review will be conducted using MEDLINE, Cochrane Library, CINAHL, Scopus and Web of Science databases from inception to 30 September 2021, to identify all reports published in English describing VTE risk prediction models which have included adult ambulatory patients with primary lung cancer for model development and/or validation. Two independent reviewers will conduct article screening, study selection, data extraction and quality assessment of the primary studies. Any disagreements will be referred to a third researcher to resolve. The included studies will be assessed for risk of bias and applicability. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies will be used for data extraction and appraisal. Data from similar studies will be used for meta-analysis to determine the incidence of VTE and the performance of the risk models.
Publication titleBMJ Open
Department/SchoolSchool of Pharmacy and Pharmacology
PublisherBMJ Publishing Group Ltd.
Place of publicationUnited Kingdom
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