Related Experiment Video
Updated: Mar 6, 2026

Author Spotlight: Advancing Cancer Associated Thrombosis Research in Rodent Models
Published on: January 5, 2024
Development of a predictive model for 6 month survival in patients with venous thromboembolism and solid malignancy
Steven Y Huang1, Bruno C Odisio2, Sharjeel H Sabir2
1Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX, 77030, USA. syhuang@mdanderson.org.
Purpose:
Our purpose was to develop a predictive model for short-term survival (i.e. <6 months) following inferior vena cava filter placement in patients with venous thromboembolism (VTE) and solid malignancy.
Methods:
Clinical and laboratory parameters were retrospectively reviewed for patients with solid malignancy who received a filter between January 2009 and December 2011 at a tertiary care cancer center. Multivariate Cox proportional hazards modeling was used to assess variables associated with 6 month survival following filter placement in patients with VTE and solid malignancy. Significant variables were used to generate a predictive model.
Results:
397 patients with solid malignancy received a filter during the study period. Three variables were associated with 6 month survival: (1) serum albumin [hazard ratio (HR) 0.496, P < 0.0001], (2) recent or planned surgery (<30 days) (HR 0.409, P < 0.0001), (3) TNM staging (stage 1 or 2 vs. stage 4, HR 0.177, P = 0.0001; stage 3 vs. stage 4, HR 0.367, P = 0.0002). These variables were used to develop a predictive model to estimate 6 month survival with an area under the receiver operating characteristic curve of 0.815, sensitivity of 0.782, and specificity of 0.715.
Conclusions:
Six month survival in patients with VTE and solid malignancy requiring filter placement can be predicted from three patient variables. Our predictive model could be used to help physicians decide whether a permanent or retrievable filter may be more appropriate as well as to assess the risks and benefits for filter retrieval within the context of survival longevity in patients with cancer.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
Related Concept Videos
Venous Thrombosis III: Interprofessional Care
Cancer Survival Analysis
Venous Thrombosis II: Clinical Manifestations and Diagnostic Studies
Assumptions of Survival Analysis
Pulmonary Embolism II: Diagnostic Studies and Interprofessional Care
Venous Thrombosis IV: Nursing Management