MétaCan
Menu
← Back to cohort
Record W2982955127 · doi:10.1182/blood-2019-124476

Natural History of Tumor Thrombus: A Single-Centre Retrospective Study

2019· article· en· W2982955127 on OpenAlexaff
C. Marcoux, Shahad Al Ghamdi, Daria Manos, Mary‐Margaret Keating, Sudeep Shivakumar

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineThrombusThrombosisPulmonary embolismRadiologyRetrospective cohort studyMalignancyHazard ratioProportional hazards modelDeep veinLog-rank testSurgeryVenous thrombosisInternal medicine

Abstract

fetched live from OpenAlex

Introduction: Venous thromboembolism (VTE) encompasses a spectrum of disorders involving thrombosis in the venous circulation, namely deep vein thrombosis (DVT) and pulmonary embolism (PE). The incidence of thrombosis is significantly elevated in patients with malignancy due to a hypercoagulable state. In addition to the elevated risk of thrombus formation in patients with malignancy, certain tumours have a predilection for intravascular extension, termed tumour thrombus. The presence of tumour thrombus considerably worsens prognosis, alters staging, and can influence the treatment options for these patients. While tumour thrombus can have have a significant impact on patients, the clinical course and optimal management of tumour thrombus remains unknown. We aim to describe the natural history of tumour thrombus and compare outcomes in those treated with or without anticoagulation at our centre. Methods: We performed a retrospective, observational review of patients over 16 years of age with tumour thrombus at a single-centre between January 2008 and December 2017. Patients with documented tumour thrombus on computed tomography (CT), magnetic resonance imaging (MRI), or ultrasound (US) were included in this study. Patients already on anticoagulation were excluded. Data were collected through medical record review including baseline characteristics, treatment history, complications and clinical outcomes. Overall survival and VTE recurrence rates between those treated with or without anticoagulation were demonstrated using Kaplan-Meier survival curves and Log-rank test. Cox-proportional hazards models were used to estimate the hazard ratio for tumor thrombosis with and without adjustment for patient characteristics including comorbidities, treatment, acuity, and location. Results: A total of 153 patients were identified to meet inclusion criteria over the study period. The majority of patients were male (65.4%) with an mean age of 65.7. The most common malignancies associated with tumour thrombus were renal cell carcinoma (34.6%) and hepatocellular carcinoma (28.8%), with 125 patients (82.5%) having stage III or IV malignancies. The most common locations of tumour thrombus were the portal vein (37.5%), renal vein (32.9%) and inferior vena cava (26.3%). Forty-one patients (26.8%) were treated with anticoagulation. Of the entire study population, 18 patients (11.8%) developed VTE within a 6 month study period after being diagnosed with tumour thrombus. Of those that developed VTE following a diagnosis of tumour thrombus, 11 were on anticoagulation (61%) and 7 were not (39%). Five patients receiving anticoagulation experienced major bleeding. Mortality was 42.5% at 6 months with no significant difference in survival between those treated with or without anticoagulation (Figure 1; p = 0.42). Proportion hazards models were not completed at the abstract submission deadline; full study results will be presented at the ASH meeting. Conclusion: In our study, we show that there is no significant difference in survival between patients with tumour thrombus treated with or without anticoagulation. While there is no clear evidence that anticoagulation improves outcomes across all patients with tumour thrombus, further studies are needed to identify subgroups of patients who may benefit from anticoagulation given their increased risk of VTE. Figure 1 Disclosures Keating: Sanofi: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; Seattle Genetics: Consultancy; Janssen: Membership on an entity's Board of Directors or advisory committees; Shire: Membership on an entity's Board of Directors or advisory committees; Hoffman La Roche: Membership on an entity's Board of Directors or advisory committees.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations20
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueBlood→Same topicVenous Thromboembolism Diagnosis and Management→French-language works237,207→