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Record W2980258435 · doi:10.1182/blood.v128.22.415.415

Real-Life Incidence of Cancer Following a First Unprovoked Venous Thrombosis: Results from the Epigetbo Study

2016· article· en· W2980258435 on OpenAlexaff
Aurélien Delluc, Karine Lacut, Jean‐Christophe Ianotto, Cécile Tromeur, Françis Couturaud, Grégoire Le Gal, Dominique Mottier

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineIncidence (geometry)CancerCumulative incidencePulmonary embolismMalignancyHazard ratioDeep veinVenous thrombosisPediatricsInternal medicineThrombosisSurgeryCohortConfidence interval

Abstract

fetched live from OpenAlex

Abstract Background: Venous thromboembolism (VTE) can be the first manifestation of cancer. Whether screening for an occult malignancy should be systematically performed in patients with unprovoked VTE is a daily challenge for clinicians. Recently, two randomized trials demonstrated that limited cancer screening in patients with a first unprovoked VTE could be the standard of care. However, the one-year incidence of occult malignancy found in these trials was unexpectedly low (4.5%) raising the hypothesis of an inclusion bias. We aimed at estimating the real-life one-year incidence of cancer following a first unprovoked VTE to inform physicians and policy makers in establishing recommendations for cancer screening in VTE patients. Methods: The EPIGETBO study is an epidemiologic study that aimed to measure the incidence of VTE in the Brest District, France1. All symptomatic VTE cases (deep vein thrombosis of the lower limb and pulmonary embolism) diagnosed between March 1st, 2013 and February 28th, 2014 among the 367,911 inhabitants of the district were recorded and validated by an adjudication committee. A systematic follow-up was planned in order to study patients' outcome. Unprovoked VTE was defined as the absence of surgical procedure, pregnancy, delivery, immobilization, admission to hospital for an acute medical illness in the 3 months preceding VTE or known active cancer. The 1-year cumulative incidence of cancer was estimated using the Kaplan-Meier method. Then, the hazard for occult cancer diagnosis associated with age>60, male sex, and current smoking was assessed by Cox regression. Results: During the study period, 576 symptomatic validated VTE events were diagnosed in 562 inhabitants of the Brest District. Five patients did not undergo follow-up (4 refusals, 1 aged<18). The VTE event at study entry was unprovoked in 310 patients (55.6%) and this was a first unprovoked VTE event in 257. Patients' mean age was 67.9 ± 2.2 years, 114 (44.3%) were men, 38 (14.8%) had a prior unprovoked VTE event. In the year following VTE, 9 of the 257 patients with a first unprovoked VTE event were diagnosed with cancer, corresponding to an overall 1-year cumulative incidence of occult cancer of 3.68% (95% CI 1.93-6.96). This incidence was 3.78% (95% CI 1.91-7.43) in the 219 patients with a first unprovoked VTE event and no prior history of provoked VTE (8 cancers). In non-smokers, the 1-year incidence rate of occult cancer was 0.81% (95% CI 0.11-5.59) as compared with 8.05% (95% CI 3.92-16.14) in smokers (p=0.004 by log-rank test). In multivariate analysis, age>60 and male sex were associated with a non significant increased risk for occult cancer diagnosis (HR 4.92; 95% CI 0.60-40.30 and 1.42; 95% CI 0.25-8.13 respectively). Conversely, current smoking was independently associated with a significant 11.8-fold increased risk for occult cancer diagnosis (HR 11.80; 95% CI 1.19-116.52). No cancer was diagnosed in patients aged≤50 years. Conclusion: In this comprehensive real-life epidemiological study, we confirmed that the one-year incidence of occult malignancy following a first episode of unprovoked VTE is low, especially in non-smokers. Current smoking was associated with a higher risk for occult cancer diagnosis; however, even in this patient subgroup, the absolute frequency was no higher than 8%. 1 Thromb Haemost 2016; Epub ahead of print DOI: 10.1160/TH16-03-0205 Disclosures No relevant conflicts of interest to declare.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.299
Teacher spread0.273 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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