Development of a predictive model for 6 month survival in patients with venous thromboembolism and solid malignancy requiring IVC filter placement

Abstract

Purpose Our purpose was to develop a predictive model for short-term survival (i.e. less than 6 months) following inferior vena cava filter placement in patients with venous thromboembolism (VTE) and solid malignancy. Materials and 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 versus stage 4, HR 0.177, P=0.0001; stage 3 versus 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 3 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.

A Prediction Model Based on Blood Biomarker for Mortality Risk in Patients with Acute Venous Thromboembolism

“…For example, Huang et al identified serum albumin, tumor stage and history of surgery within 30 days as independent risk variables for 6-month survival in patients with malignancy combined with VTE who underwent inferior vena cava filter placement. 11 The prediction model had an AUC of 0.815. However, the authors did not provide further parameters or calibration plots for this model, and neither internal nor external validation was conducted.…”

“…Most previous studies in this area have focused on the prediction of VTE risk in specific populations. [7][8][9][10][11]35 For example, McCurdy et al identified the incidence and risk variables for VTE in 2161 patients with inflammatory bowel disease (IBD) after discharge and developed a prediction model to assess VTE risk. 35 The final model included age >45 years, multiple admissions, intensive care unit admissions, length of admissions >7 days and central venous catheters.…”

“…Most studies to date have focused on predicting the risk of VTE in specific populations. [6][7][8][9][10][11][12][13][14] However, studies of risk variables associated with all-cause mortality and PTS in VTE patients are relatively uncommon, 11,[15][16][17][18] and multivariable clinical prediction models in emergency setting are also rarely reported.…”