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Record W2560200396 · doi:10.1182/blood.v108.11.717.717

The Effect of Low Molecular Weight Heparin (LMWH) on Cancer Survival. A Systematic Review and Meta-Analysis (MA) of Randomized Trials.

2006· review· en· W2560200396 on OpenAlexaff
Alejandro Lazo‐Langner, Glenwood D. Goss, Johanna N. Spaans, Marc Rodger

Bibliographic record

VenueBlood · 2006
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineInternal medicineMeta-analysisCochrane LibraryHazard ratioRandomized controlled trialPlaceboCancerRelative riskOdds ratioSurgeryLow molecular weight heparinConfidence intervalHeparinPathology

Abstract

fetched live from OpenAlex

Abstract Several studies have supported the existence of an antitumor effect of anticoagulants and several MA of studies comparing unfractionated heparin and LMWH for treatment of venous thromboembolism have suggested that the risk of mortality in the subgroup of cancer patients receiving LMWH might be reduced; however other authors have reported contrary findings. We conducted a systematic review and MA of randomized trials comparing LMWH with placebo/no intervention studying as the main outcome the impact on survival in cancer patients. Data sources were Medline, EMBASE, HEALTHstar, Cochrane Library, and grey literature. Data extraction was done by one reviewer and verified by a second reviewer. Discrepancies were resolved by consensus. Main outcomes were death at 1 year and major bleeding episodes. Secondary outcome was death at 2 years. A MA was done using a DerSimonian and Laird random-effects model with odds ratio (OR) and relative risk (RR) as summary statistics. We conducted a MA of survival rates using censored end-points and a MA of hazard ratios (HR). If not reported, HR were extracted from the survival curves and pooled using the generic inverse variance method (random effects model). 283 potential references were identified and 7 were fully evaluated. Four studies which enrolled 898 patients with solid malignancies (the majority with extensive disease) were included; 3 of the 4 studies included previously treated patients. OR and RR of death are shown in the table. Mortality in cancer patients receiving LMWH versus placebo/no treatment All Patients Patients with advanced disease OR 95% CI P OR 95% CI P OR odds ratio; CI confidence interval; RR relative risk 1-year mortality 0.70 0.49, 1.00 0.05 0.75 0.57, 0.99 0.04 2-year mortality 0.57 0.34, 0.96 0.03 0.59 0.42, 0.84 0.004 RR 95% CI P RR 95% CI P 1-year mortality 0.87 0.77, 0.99 0.04 0.89 0.80, 0.99 0.03 2-year mortality 0.90 0.84, 0.97 0.007 0.92 0.86, 0.98 0.02 The results of the survival meta-analysis showed that the pooled survival proportions at 1 and 2 years were 0.43 and 0.19 for the LMWH and 0.35 and 0.11 for the control group, respectively; differences were statistically significant (1 year p=0.018, 2 year p=0.001). The MA of HR is shown in the figure. Figure Figure There was no increase in major bleeding episodes. Sensitivity analyses including only patients with advanced disease did not modify the findings; an analysis according to tumor type was not conducted due to a lack of information. LMWH improves overall survival in cancer patients independent of the stage. Additional trials are required to define the tumor types, disease stages, and dosing schedules most likely to derive the greatest survival benefit. Since the majority of patients included were previously treated, exploring the benefit of LMWH in newly diagnosed patients is necessary.

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)0.025
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.057
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.032
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.061
GPT teacher head0.375
Teacher spread0.313 · 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.

Study designMeta-analysis
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

Citations1
Published2006
Admission routes1
Has abstractyes

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