IN THE LITERATURE
Tumor Site , D-Dimer Markers Predict VTE Risk in Patients With Cancer
Venous thromboembolism ( VTE ) is a common complication of cancer , with the risk of developing VTE varying greatly depending on several patient and disease factors . In a study published in Lancet Haematology , researchers analyzed incidence of VTE in two large European cohorts to identify factors associated with an increased risk for VTE .
Ingrid Pabinger , MD , of the Medical University of Vienna in Austria , and co-authors determined that two variables , tumor site and D-dimer concentrations , predicted the risk of VTE . They then validated a risk-prediction model incorporating these variables , finding that “ the [ prediction ] nomogram was able to discriminate between patients who did and did not develop VTE during six months of follow-up and was appropriately calibrated ,” the authors reported .
Using this model could help clinicians select patients who would benefit from thromboprophylaxis ( rather than a treatall or treat-none approach ) “ by reducing the risks of VTE and bleeding events caused by unnecessary thromboprophylaxis ,” they continued .
To identify variables prognostic of VTE , the researchers first analyzed data from the prospective Vienna Cancer and Thrombosis Study ( CATS ), which included 1,423 patients with solid tumors or lymphoma . Then , the researchers validated the prognostic importance of these variables with data from 832 patients enrolled in the prospective Multinational Cohort Study to Identify Cancer Patients at High Risk of VTE ( MICA ).
The analysis excluded patients with multiple myeloma or high-grade glioma , but all patients had been treated as outpatients , “ because about 75 percent of all cases of cancer-associated VTE occur within this population ,” the authors added . The primary outcomes for each cohort were as follows :
• CATS : symptomatic , independently assessed VTE ( a composite of distal or proximal deep vein thrombosis [ DVT ] of the leg , upper-limb DVT , symptomatic splanchnic DVT , or pulmonary embolism [ PE ])
• MICA : a composite of symptomatic or incidental PE , distal or proximal DVT , non – catheter-related upper-limb DVT , or symptomatic catheter-related upper-limb DVT
The authors also categorized tumor sites as either low or intermediate risk for VTE , high risk for VTE , or very high risk for VTE .
In the CATS and MICA cohorts , 80 patients ( 6 %) and 48 patients ( 6 %) developed VTE , respectively , during a median follow-up of 180 days ( range = 109-180 days ). This translated to a cumulative risk of VTE at six months ( primary endpoint ) of 5.7 percent in CATS and 6.3 percent in MICA .
Eleven clinical prognostic factors and biomarkers emerged in the univariable model of cause-specific VTE hazards , but , on multivariable analysis , only two variables were significantly associated with an increased VTE risk :
• tumor site : Compared with patients with tumors located in a very – high-risk location , patients with tumors in a highrisk site were nearly twice as likely to develop VTE ( hazard ratio [ HR ] = 1.96 ; 95 % CI 1.41-2.72 ; p = 0.0001 ). The same association was seen for patients with tumors located in a high-risk versus low- or intermediate-risk site .
• D-dimer concentrations : The risk for VTE increased by 32 % as D-dimer concentration levels doubled ( HR = 1.32 ; 95 % CI 1.12-1.56 ; p = 0.001 ).
When the investigators created a two-variable risk model incorporating tumor site and D-dimer concentration levels , they found that the model predicted a six-month VTE risk of 5.7 percent in the CATS cohort .
Next , the researchers performed cross-validation analysis to calculate how the predicted incidence of objectively confirmed VTE at six months compared with the cumulative 6-month incidences observed in both cohorts ( referred to as c-indices ).
The cross-validated c-index of the risk-prediction model was 0.66 in CATS and 0.68 in MICA . The model also performed better than existing models ; it correctly reclassified up to 31 percent of patients in CATS who were initially classified with the five-variable Khorana score , which accounts for tumor site , body mass index , and platelet , hemoglobin , and leukocyte counts .
The researchers noted that patients from the two cohorts were recruited from only academic centers , reducing the generalizability of the findings across the broader cancer population . In addition , considering that the primary outcome in the MICA cohort was a composite of DVT and PE , the authors questioned the validity of the model for predicting the two individual outcomes independently .
“ Our clinical prediction model could outperform previous clinical prediction scores in predicting those patients at high risk of developing VTE ,” the authors concluded . “ Our simple clinical prediction model considerably improved prediction of cancer-associated VTE and could aid physicians in selection of those ambulatory patients with solid tumors who will most benefit from pharmacological thromboprophylaxis .”
The new prediction model is available as a paper-based nomogram , as well as an online risk calculator , the authors reported . ●
The authors reported no conflicts of interest .
REFERENCE
Pabinger I , van Es N , Heinze G , et al . A clinical prediction model for cancer-associated venous thromboembolism : a development and validation study in two independent prospective cohorts . Lancet Haematol . 2018 ; 5 : e289-98 .
20 Focus on Classical Hematology