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Anticoagulation for the long term treatment of venous thromboembolism in patients with cancer

2008· reference-entry· en· W4248689247 on OpenAlexaff
Elie A. Akl, Maddalena Barba, Sandeep Rohilla, Irene Terrenato, Francesca Sperati, Paola Muti, Holger J. Schünemann

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2008
Typereference-entry
Languageen
Field
Topic
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineXimelagatranCochrane LibraryVitamin K antagonistMeta-analysisMEDLINEVenous thromboembolismHazard ratioRandomized controlled trialInternal medicineCancerWarfarinIntensive care medicineOncologyDabigatranConfidence intervalThrombosisAtrial fibrillation

Abstract

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BACKGROUND: Cancer increases the risk of thromboembolic events and the risk of recurrent thromboembolic events while on anticoagulation. OBJECTIVES: To compare the efficacy and safety of low molecular weight heparin (LMWH) and oral anticoagulants (vitamin K antagonist (VKA) and ximelagatran) for the long term treatment of venous thromboembolism (VTE) in patients with cancer. SEARCH STRATEGY: A comprehensive search was undertaken including a January 2007 search of electronic databases; Cochrane Central Register of Controlled Trials (CENTRAL), (The Cochrane Library 2007, Issue 1). MEDLINE (1966 onwards; accessed via OVID), EMBASE (1980 onwards; accessed via OVID) and ISI the Web of Science. Hand search of the proceedings of the American Society of Clinical Oncology and of the American Society of Hematology. Checking of references of included studies, relevant papers and related systematic reviews. Use of "related article" feature in PubMed; and (5) search of ISI the Web of Science for papers citing landmark studies. SELECTION CRITERIA: Randomized controlled trials (RCTs) comparing long term treatment with LMWH versus oral anticoagulants (VKA or ximelagatran) in patients with cancer and symptomatic objectively confirmed VTE. DATA COLLECTION AND ANALYSIS: Using a standardized data form we extracted data on methodological quality, participants, interventions and outcomes of interest: survival, recurrent VTE, major bleeding, minor bleeding, thrombocytopenia and postphlebitic syndrome. MAIN RESULTS: Of 3986 identified citations, eight RCTs were eligible and reported data for patients with cancer. Their overall methodological quality was moderate. Meta-analysis of six RCTs showed that LMWH, compared to VKA provided no statistically significant survival benefit (Hazard ratio (HR) = 0.96; 95% CI 0.81 to 1.14) but a statistically significant reduction in VTE (HR = 0.47; 95% (Confidence Interval (CI) = 0.32 to 0.71). There was no statistically significant difference between LMWH and VKA in bleeding outcomes (RR = 0.91; 95% CI = 0.64 to 1.31) or thrombocytopenia (RR = 1.02; 95% CI = 0.60 to 1.74). One RCT compared tinzaparin and dalteparin and showed no differences in the outcomes of interest. One RCT compared a six months extension of anticoagulation with 18 months Ximelagatran 24mg twice daily versus placebo. It showed a reduction in VTE (HR = 0.16; 95% CI 0.09 to 0.30) with no apparent effect on survival or bleeding. AUTHORS' CONCLUSIONS: For the long term treatment of VTE in patients with cancer, LMWH compared to VKA reduces venous thromboembolic events but not death. The decision for a patient with cancer and VTE to start long term LMWH versus oral anticoagulation should balance the benefits and downsides and integrate the patient's values and preferences for the important outcomes and alternative management strategies.

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 imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.075
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0080.000

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.

Opus teacher head0.099
GPT teacher head0.355
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations19
Published2008
Admission routes1
Has abstractyes

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