Efficacy and Safety of Tinzaparin in CAT Patients with Metastatic Disease
Bibliographic record
Abstract
Introduction Venous thromboembolism (VTE) frequently complicates the course of active cancer with a significant impact on morbidity and mortality. The results of CATCH trial for treatment of cancer-associated thrombosis (CAT) have been reported and included patients with and without metastatic disease. As metastatic disease is known to be associated with a higher risk of recurrent VTE and bleeding, we performed these post hoc analyses to assess the recurrent VTE (rVTE), recurrent deep vein thrombosis (rDVT), and bleeding events (major bleeding (MB), clinically relevant (CRB) and clinically relevant non-major (CRNMB)) in patients with CAT with metastatic disease. Risk factors associated with rVTE, rDVT and CRB were also explored. Method CATCH (ClinicalTrials.govNCT01130025; Lee A et al. JAMA 2015) was a Phase III, multinational, randomized, active-controlled, open-label trial. Patients with solid tumor cancer and haematological malignancies were included. Patients were randomized to receive therapeutic dosing of tinzaparin (175 U/kg OD) vs warfarin (INR target 2.0 - 3.0). Treatment was given for up to 6 months. The primary efficacy outcome was the composite of symptomatic DVT, symptomatic nonfatal pulmonary embolism (PE), fatal PE, incidental proximal DVT and incidental proximal PE. All cumulative incidence VTE and MB outcome were objectively documented and centrally adjudicated in a treatment-blinded fashion. Patients who had known metastatic solid tumor at presentation were included in these analysis. The regression model compared the two treatment groups adjusting for competing risks and geographical region and history of VTE. Results Among the CATCH study population, 55% had metastatic disease. Of these patients, 247 and 245 received tinzaparin and warfarin, respectively, with no significant differences in patient characteristics between treatment groups. Patients with metastatic disease had a higher incidence of rVTE (10.2% vs 7.0%) and symptomatic non-fatal rDVT (5.5% vs 2.9%) compared to patients without metastatic disease. Patients with metastatic disease also had a higher incidence of MB (2.8% vs 1.9%), CRB (17.7%% vs 11.8%) and CRNMB (15.0% vs 10.5%) compared to patients without metastatic disease. rVTE occurred in significantly fewer patients assigned to tinzaparin (6.8%) versus warfarin (14.4%) (HR 0.45; 95%CI 0.25-0.80; p=0.007). rDVT also occurred significantly less frequently in patients assigned to tinzaparin (3.0%) versus warfarin (8.4%) (HR 0.34; 95%CI 0.15-0.81; p=0.015). 96% of rVTE were symptomatic. There was no significant difference in MB between tinzaparin- and warfarin-treated patients (4.0% vs 1.6%; HR 2.17; 95%CI 0.71-6.65; p=0.177), but tinzaparin was associated with significantly lower risk of CRB (15.8% vs 19.6%; HR 0.63; 95%CI 0.41-0.97; p=0.037) and CRNMB (12.1% vs 18.0%; HR 0.53; 95%CI 0.33-0.84; p=0.008). Factors associated with rVTE in patients with metastatic disease included central venous catheterization (HR 0.10; 95%CI 0.01-0.79; p=0.029), venous compression from mass or adenopathy (HR 3.99; 95%CI 2.14-7.43; p<0.001), and hepatobiliary cancer (HR 4.07; 95%CI 1.65-10.0; p=0.002). The latter two were also significant risk factors for rDVT. Age > 75 (HR 2.56; 95%CI 1.43-4.60; p=0.002) and known intracranial pathology (HR 2.24; 95%CI 1.07-4.66; p=0.031) were found to be significant risk factors for CRB. Conclusion CAT patients with metastatic diseases have higher risks of rVTE and bleeding compared with patients without metastases. Amongst CAT patients with metastatic solid tumors, treatment with tinzaparin was associated with significantly lower risk of rVTE and rDVT and significantly lower risk of CRB and CRNMB compared with warfarin. Tinzaparin offers a favourable risk-benefit profile in treatment of CAT in patients with metastatic solid tumors. Disclosures Lee: Pfizer: Consultancy, Honoraria; BMS: Research Funding; LEO Pharma A/S: Consultancy, Honoraria; Bayer: Consultancy, Honoraria, Other: Advisory board, steering committee. Bauersachs:Aspen: Consultancy, Honoraria; Bayer: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria; LEO Pharma A/S: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. Turpin:LEO Pharma Canada: Current Employment. Hansen:LEO Pharma A/S: Current Employment. Khorana:Leo Pharma: Honoraria; Merck: Research Funding; Array: Other: Research funding (to institution); Leap: Research Funding; Seattle Genetics: Honoraria; Pharmacyte: Honoraria; Pharmacyclics: Honoraria; Janssen: Honoraria; Pfizer: Honoraria; Medscape: Honoraria; Bayer: Honoraria; BMS: Honoraria, Research Funding; Sanofi: Honoraria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".