Anticoagulation for the initial treatment of venous thromboembolism in patients with cancer
Bibliographic record
Abstract
BACKGROUND: Compared to patients without cancer, patients with cancer receiving anticoagulant treatment for venous thromboembolism are more likely to develop recurrent venous thromboembolism (VTE). OBJECTIVES: To compare the efficacy and safety of three types of anticoagulants (i.e. low molecular weight heparin (LMWH), unfractionated heparin (UFH), and fondaparinux) for the initial treatment of VTE in patients with cancer. SEARCH STRATEGY: A comprehensive search for studies of anticoagulation in cancer patients including a January 2007 electronic search of : Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE and ISI the Web of Science. SELECTION CRITERIA: Randomized clinical trials (RCTs) comparing LMWH, UFH, and fondaparinux in patients with cancer and objectively confirmed VTE. DATA COLLECTION AND ANALYSIS: Using a standardized data form data was extracted in duplicate on methodological quality, participants, interventions and outcomes of interest that included all cause mortality, recurrent VTE, major bleeding, minor bleeding, thrombocytopenia and postphlebitic syndrome. MAIN RESULTS: Of 3986 identified citations, 26 RCTs including cancer patients as subgroups fulfilled the inclusion criteria. Cancer subgroup data was obtained for 15 of the 26 RCTs. Thirteen studies compared a LMWH to UFH while one study compared fondaparinux to UFH and one study compared dalteparin to tinzaparin. Meta-analysis of 11 studies showed a statistically significant mortality reduction in patients treated with LMWH compared with those treated with UFH (Relative risk (RR) = 0.71; 95% confidence interval (CI) 0.52 to 0.98). There was little change in the results after excluding studies of lower methodological quality (RR = 0.72; 95% CI 0.52 to 1.00). A meta-analysis of three studies comparing LMWH with UFH in reducing recurrent VTE was inconclusive (RR = 0.78; 95% CI 0.29 to 2.08). No data was available for bleeding outcomes, thrombocytopenia or postphlebitic syndrome. Compared to UFH, fondaparinux showed a non-statistically significant benefit for the outcome of death (RR = 0.52; 95% CI 0.26 to 1.05). The one study comparing dalteparin to tinzaparin showed a non-statistically significant mortality reduction with dalteparin (RR = 0.86; 95% CI 0.43 to 1.73). AUTHORS' CONCLUSIONS: Based on the included trials, LMWH is likely to be superior to UFH in the initial treatment of VTE in patients with cancer. However, there is a need for more trials to better address this research question in cancer patients. Moreover, researchers should consider making the raw data of RCTs available for individual patient data meta-analyses.
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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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".