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NCT04301362: FIIT_Score
Biomarkers of Thrombosis as Predictors of Venous Thromboembolism Risk in Cancer Patients
trial testing Thrombosis biomarkers in Cancer in 600 participants. Status unknown.
19 July 2021
Quick facts
| Lead sponsor | Centro Hospitalar de Vila Nova de Gaia/Espinho, E.P.E. |
|---|---|
| Status | Status unknown |
| Study type | OBSERVATIONAL |
| Enrollment | 600 |
| Start date | 19 July 2019 |
| Primary completion | 19 July 2021 |
| Estimated completion | 19 December 2021 |
| Sites | 1 location across Portugal |
Drugs / interventions tested
- Thrombosis biomarkers
Conditions studied
- Cancer — all drugs for Cancer →
- Thromboembolism — all drugs for Thromboembolism →
- Thrombosis — all drugs for Thrombosis →
- Biomarkers — all drugs for Biomarkers →
Sponsor
Centro Hospitalar de Vila Nova de Gaia/Espinho, E.P.E.
Who can join
18 and older, any sex, with Cancer or Thromboembolism. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
The main venous thromboembolism (VTE) risk prediction model for ambulatory cancer patients is Khorana. Cancer thrombosis is associated with elevated thrombin generation. Its quantification is a promising method for evaluating patient's thrombotic profile. This study aims to develop a predictive model of VTE risk in ambulatory cancer patients, combining thrombosis biomarkers (D-dimers and thrombin generation potential) with the Khorana score. This is a prospective observational study that includes newly diagnosed cancer patients proposed for anti-tumor treatment (chemotherapy, immunotherapy or targeted therapies). Patients with disease progression are allowed if chemotherapy-free for 3 months. A 6-month mean incidence of VTE 6-10% is expected, requiring a sample size of 600 patients. Blood sample is collected at inclusion to analyze thrombosis biomarkers and blood count. The primary endpoint is the occurrence of symptomatic or incidental VTE within 6 months of inclusion. Models will follow a logistic approach with K-fold cross-validation (k=10). Model quality will be assessed with Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Decision for entering predictors in multivariate models will be based on p \<.10 in the univariate analysis.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT04301362 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Centro Hospitalar de Vila Nova de Gaia/Espinho, E.P.E.
- Last refreshed: 12 March 2020
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT04301362.
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