Efficacy and Safety Outcomes in Patients with Cancer-Associated Thromboembolism Treated with Tinzaparin According to the Tumor Site: Meta-Analysis of Prospective Studies Involving 1413 Individual Patients' Data
Bibliographic record
Abstract
Introduction DOAC (direct oral anticoagulant) and LMWH (Low Molecular Weight Heparin) are recommended by international guidelines as first line therapy in patients with CAT (Cancer Associated Thrombosis), but the risk of venous thromboembolic recurrence (rVTE) and the risk of major bleeding (MB) remains high. Several scores have attempted to predict these risks with disappointing results, probably because of heterogeneous treatments and small sample sizes representing various tumor sites. We conduct a meta-analysis on individual patient level data to report the rate of rVTE and MB by 6 months according to site of cancer from prospective studies involving CAT patients on tinzaparin. Methods The meta-analysis is based on individual patient data from prospective studies that included patients with CAT treated with tinzaparin who were followed for 6 months (PROSPERO registration CRD42019119907). Eligible studies must include controlled data and a central decision for study outcomes. Main outcomes were cumulative incidence of rVTE and MB at 6 months. Time-to-event outcomes were estimated using competing risk regression (Fine and Gray's method with death as competing risk). Cumulative incidences were presented with corresponding 95% confidence interval (95% CI). Time-to-event outcomes were estimated using competing risk regression (Fine and Gray's method with death as competing risk). Cumulative incidences were presented with corresponding 95% confidence interval (95% CI). Results Three prospective cohort studies (AXA - NCT02898051, 308 patients; PREDICARE - NCT03099031, 409 patients (1); TICAT - NCT01164046, 247 patients (2) and the Tinzaparin arm of the CATCH study (NCT01130025, 449 patients (3)) were included. A total of 1413 patients (median age 65.0 [IQR 56.0-73.5], 51.9% female) were included in the meta-analysis. Cancers were mostly solid tumors (91.7%); primary sites were gastrointestinal (27.0%), lung (18.0%), breast (11.8%), genitourinary (14.4%); ECOG performance status was ≥ 2 for 30.2%. At 6 months, 74 patients experienced a rVTE, for a cumulative incidence of 5.4% [95% CI: 4.3%; 6.7%], while 47 patients had a MB, for a cumulative incidence of 3.4% [95% CI: 2.6%; 4.6%]. Clinical outcomes according to the type of cancer are summarized in the Table. rVTE cumulative incidence varied from 0.6 to 8.5% and rVTE occurred more frequently in patients with genitourinary, lung and gynecological cancers, while MB cumulative incidence ranged from 2.1% to 4.2% across different cancer sites (Table). Overall mortality ranged from less than 18% (breast and hematological cancers) to 45.2% (lung cancer) within 6 months of the index VTE. Conclusion In CAT patients receiving tinzaparin for up to 6 months, rVTE and MB vary according to tumor site. The CAT entity is not sufficient to describe a situation at risk of recurrence or bleeding for patient management. References 1.Jara-Palomares L et al. Tinzaparin in cancer associated thrombosis beyond 6months: TiCAT study. Thromb Res. 2017; 157:90-96. 2. Girard P, et al. Failure of the Ottawa Score to Predict the Risk of Recurrent Venous Thromboembolism in Cancer Patients: The Prospective PREDICARE Cohort Study. Thromb Haemost. 2022; 122:151-157. 3. Lee AYY et al. CATCH Investigators. Tinzaparin vs Warfarin for Treatment of Acute Venous Thromboembolism in Patients With Active Cancer: A Randomized Clinical Trial. JAMA. 2015; 314(7):677-686.
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.059 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".