ABO Group As a Thrombotic Risk Factor In Children With Acute Lymphoblastic Leukemia: A Retrospective Study Of 523 Pediatric Patients
Notice bibliographique
Résumé
Abstract Introduction Children with acute lymphoblastic leukemia (ALL) are at high risk of thrombotic complications, resulting from multiple risk factors (including malignancy, medications, central venous access devices (CVADs) and inherent host characteristics). Several studies have investigated the role of ABO blood groups in the occurrence of thromboembolic events in adults. Non-O blood group has been associated with an increased risk of venous thromboembolism (VTE), with a compounding effect in the presence of thrombophilia or cancer. We hypothesized that among children with ALL receiving a standardized protocol, there would be an increased risk of thrombotic events in non-O blood group compared to O group patients. Methods We retrospectively reviewed medical charts of all children with ALL treated in our tertiary care center between 1995 and 2013 and identified those with an objectively confirmed VTE. Children were included in 3 different, but similar multiagent protocols (DFCI 95-01, 00-01 and 05-01). Patients were classified into O and non-O blood groups. Leukemia phenotype, risk category, age, gender, timing of thrombosis, localisation and thrombotic workup were also collected. Statistical analysis Risk factor for VTE was defined as a prevalence. Univariate and multivariate logistic regression models were applied to assess the association between potential risk factors and the occurrence of VTE. Results are presented as adjusted OR and 95% confidence intervals. All statistical tests were two-sided. Results Of 523 children with ALL, 50 (9.6%) had thrombosis. Blood group distribution showed 38 (76%) patients in the non-O and 12 (24%) in the O group, compared to 302 (58%) non-O and 221 (42%) O in the total cohort. Except for gender, univariate predictors of VTE were all significant (age ≥ 10 years, P = 0.023, high risk category, P = 0.001, T phenotype, P = <0.001, non-O blood group, P = 0.006, male, P = 0.79). In multivariate analysis, non-O blood group, phenotype and risk category remained significant, but not age nor gender: age ≥ 10 years, OR 1.12 [95% CI 0.53,2.34]; high risk, OR 2.45 [95% CI 1.13,5.34]; T phenotype, OR 2.48 [95% CI 1.11,5.55]; non-O blood group, OR 2.93 [95% CI 1.46, 5.87]; male, OR 0.83[ 95% CI 0.45, 1.54] (table I). The vast majority of VTE occurred at an upper limb CVAD site (64%). Other sites were lower limb (14%), cerebral venous sinus thrombosis (14%), pulmonary embolism (6%), intracardiac (6%) and multiple sites (10%). VTE mainly occurred during the induction (18%) and consolidation (72%) phases of therapy. Thrombotic workup was done in 33/50 patients, with 11 abnormal results (mostly non-diagnostic low Protein C or S levels and positive lupus anticoagulants). Positive family history was found in 2 cases, but not consistently explored. No patients had Factor V Leiden or II G20210A mutation. Discussion The estimated prevalence of VTE in children with cancer is 8% (compared with 0.7-1.4/100 000 in the general pediatric population (Athale and Chan, 2003). A large number of studies have evaluated the epidemiology and risk factors of thrombotic events in children with ALL (Caruso et al 2006, Farinasso et al, 2007, Grace et al, 2011), confirming the multifactorial etiology of VTE in these children. Significant associations between ABO blood group and VTE have been reported in several studies (Dentali et al, 2012, T.Ohira et al, 2006 and 2007, Wu O et al, 2008, Wiggins KL et al, 2009). A few studies have investigated ABO blood group as a risk factor for VTE in adult malignancies (Streiff et al, 2004,). To date, none have explored it in childhood cancer. Our results clearly identify non-O blood group as a significant independent risk factor for VTE in children with ALL. Prospective studies are needed to confirm these data. The mechanisms underlying the increased risk of VTE in non-O blood group patients remain to be elucidated. Disclosures: No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».