Risk Factors Predictive of Occult Cancer Detection in Patients with Unprovoked Venous Thromboembolism
Bibliographic record
Abstract
Abstract Background: Venous thromboembolism (VTE) may be the earliest sign of cancer. Risk factors associated with the presence of an occult cancer in patients with a first acute unprovoked VTE are unknown. We sought to assess the risk factors predictive of occult cancer detection in patients with a first unprovoked symptomatic VTE. Methods: Post-hoc, pre-defined analyses of the multicenter open-label randomized controlled trial - Screening for Occult Malignancy in Patients with Idiopathic Venous Thromboembolism (SOME) trial (Carrier M et al. N Engl J Med 2015). The trial compared comprehensive computed tomography (cCT) of the abdomen and pelvis in addition to limited occult-cancer screening (complete history and examination, basic laboratory testing, chest radiography, and breast, cervical and prostate cancer screening) with limited occult-cancer screening alone in patients with a first unprovoked episode of VTE. Cox proportional hazard models were used to analyze the effect of specific risk factors on the outcome of occult cancer within 12 months of a diagnosis of unprovoked VTE. Multivariable analysis was performed using Cox proportional hazard models that included all variables that achieved a p value of < 0.20 in univariate analyses. Results: A total of 854 patients were randomized to limited occult cancer screening only, or limited occult cancer screening in combination with a cCT. The mean age was 54 years and 67.4% were males. A total of 33 (3.9%; 95% C.I. 2.8-5.4) patients received a new diagnosis of cancer at 12 months follow-up. Age ≥ 60 years, compared to age < 60 years, was a predictor of cancer with a corresponding hazard ratio (HR) of 2.90 (95% C.I. 1.44-5.83, p=0.003). A previous provoked VTE in patients was also associated with a higher risk of developing cancer (HR=3.57, 95% C.I. 1.38-9.25, p=0.009). Patients with an unprovoked deep vein thrombosis (DVT), compared to either those with a pulmonary embolism (PE) only or both DVT and PE, seemed more likely to have a diagnosis of cancer. However, this trend was not statistically significant. (Table 1) These results were confirmed on multivariable analysis. Patients exhibiting one of these characteristics had a three-fold higher risk of occult cancer compared with patients without these characteristics. (Table 1) Conclusion: Age at unprovoked VTE diagnosis (≥ 60 years) and prior provoked VTE are predictors of occult cancer, and could potentially be used to identify a group of patients with unprovoked VTE at high risk of underlying cancer. Table 1.Risk factors of occult malignancy among patients with a first unprovoked symptomatic VTE.Patients without cancer (%) (n = 821)Patients with cancer (%) (n = 33)Univariate analysis Hazard Ratio (95% C.I.)P valueMultivariable analysis Hazard Ratio (95% C.I.)P valueAge at diagnosis ≥ 60 years288 (35.1)20 (60.6)2.90 (1.44-5.83)0.0033.0 (1.47-5.99)0.002Male sex555 (67.6)21 (63.6)0.72 (0.35-1.46)0.358--Prior provoked VTE42 (5.1)5 (15.2)3.57 (1.38-9.25)0.0093.8 (1.46-10.03)0.006Type of current VTEDVT only444 (54.3)24 (72.7)1.91 (0.89-4.12)0.0972.1 (0.97-4.51)0.061PE only271 (33.1)7 (21.2)0.60 (0.26-1.38)0.229--DVT + PE103 (12.6)2 (6.1)0.54 (0.13-2.24)0.392--Baseline medicationsOral contraceptive pill48 (5.8)0 (0.0)----Exogenous estrogen18 (2.2)1 (3.0)1.51 (0.21-11.07)0.685--Antiplatelet agent39 (4.8)1 (3.0)0.62 (0.09-4.56)0.641--Oral anticoagulant688 (83.8)26 (78.8)0.66 (0.29-1.53)0.337--LMWH391 (47.7)15 (45.5)0.68 (0.34-1.36)0.275--VTE, venous thromboembolism; DVT, deep vein thrombosis; PE, pulmonary embolism; LMWH, low molecular weight heparin Disclosures Lazo-Langner: Pfizer: Honoraria, Other: Participated in studies funded by this organization, Speakers Bureau; LEO Pharma: Honoraria, Other: Participated in studies funded by this organization; Boehringer Ingelheim: Honoraria, Other: Participated in studies funded by this organization; Bayer: Honoraria, Other: Participated in studies funded by this organization; Daiichi-Sankyo: Other: Participated in studies funded by this organization; Novartis: Other: Participated in studies funded by this organization; Celgene: Other: Participated in studies funded by this organization; Alexion: Research Funding. Shivakumar:Bayer: Honoraria. Routhier:Sanofi-Aventis: Research Funding. Douketis:Janssen: Consultancy; Bristol-Myers Squibb: Consultancy, Honoraria; Pfizer: Honoraria; Sanofi-Aventis: Honoraria; Daiichi-Sankyo: Consultancy; Actelion: Consultancy; Biotie: Other: Advisory board; The Medicines Company: Other: Advisory board; Bayer: Consultancy; Boehringer Ingelheim: Consultancy, Honoraria. Carrier:LEO Pharma: Consultancy, Research Funding; BMS: Research Funding; Bayer: Consultancy; Pfizer: Consultancy.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".