Validation of A Clinical Prediction Rule for Risk Stratification of Recurrent Venous Thromboembolism In Patients with Cancer-Associated Venous Thromboembolism
Notice bibliographique
Résumé
Abstract Abstract 4209 Background: The risk of recurrent venous thromboembolism (VTE) in patients with cancer-associated VTE, remains high even with the use of low molecular weight heparin (LMWH). However, due to the heterogeneity of the disease it is probable that recurrence risk varies widely. We have developed a prediction rule to classify risk of recurrence in the first 6 months of treatment: + 1 is scored for each of female gender, lung cancer and prior VTE and – 1 is scored for breast cancer and – 2 for TNM stage 1 disease. With a score of ≤ 0, 4.5% of patients recur (this represented 48% of the patient populations), and > 0, 19.7% recur. The rule was derived in a retrospective cohort study of patients followed at the Thrombosis unit of the Ottawa hospital and requires validation. Methods: We applied our rule in a new set of 819 consecutive patients with cancer-associated VTE from 2 multicentre randomized controlled trials comparing LMWH with vitamin K antagonists (VKA) (ClotCant group). In these studies the stage of disease was not separated by exact TNM classification, rather patients were classified as stage I, II (no metastasis) versus III, IV (metastasis). As such, we redid our derivation model with stage I and II grouped together, which gave this variable a score of – 1. This resulted in a prediction rule which gave a recurrence risk that no longer clearly dichotomized risk; rather gave a low, intermediate, and high risk groups. As in our derivation study, we evaluated patients' risk of recurrence regardless of type of anticoagulant use (VKA or LMWH). Results: Of 819 patients, 86 (10.5%) presented with a VTE recurrence during the anticoagulation period. When we applied our derivation rule in this population, we were able to demonstrate a significant difference in VTE recurrence risk dependent on gender, primary tumour site, stage and history of prior VTE. Patients with a score < 0 have low risk (5.1%) for VTE recurrence and this represented 19% of the patient population; patients with a score of 0 had a intermediate risk (9.8%) and this represented 42% of patients; a score ≥ 1 was high risk (13.9%), occurring in 38% of the population. Dichotomizing the results gave a recurrence risk of 8% in patients with a score ≤ 0 and a 15.2% recurrence risk with a score > 0. Conclusion: the validation dataset suggests reproducibility of our model. The dichotomized score is less discriminatory than our original model suggesting an advantage to classifying patients tumour stage as TNM stage I versus stage II, III and IV. Unfortunately, we could not test this hypothesis with the ClotCant dataset. Our model appears to differentiate risk for recurrence and should be utilized in treatment trials: attempting novel treatment strategies in high risk patients since LMWH alone does not seem to be enough; and using the less costly typical “LMWH followed by oral anticoagulants” in the low risk population to evaluate whether VKA can be as safe and effective as long term LMWH. Disclosures: Lee: Eisai: Research Funding; Sanofi Aventis: Consultancy, Honoraria; Leo Pharma: Consultancy; Pfizer: Consultancy, Honoraria; Bayer: Honoraria; Boehringer Ingelheim: Consultancy, Honoraria, Speakers Bureau.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,048 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».