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Enregistrement W3215728887 · doi:10.1182/blood-2021-153887

Pregnancy Management and Outcomes in Patients with Myeloproliferative Neoplasms

2021· article· en· W3215728887 sur OpenAlexaffabout
Iyad Arusi, Vikas Gupta, Ann Kinga Malinowski, Nadine Shehata, Dawn Maze

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueMyeloproliferative Neoplasms: Diagnosis and Treatment
Établissements canadiensMount Sinai HospitalPrincess Margaret Cancer CentreSinai Health SystemUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicinePregnancyEssential thrombocythemiaObstetricsRetrospective cohort studyPreeclampsiaPediatricsPolycythemia veraInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: While BCR-ABL1 negative myeloproliferative neoplasms (MPN) are typically diagnosed in the sixth decade of life, approximately 20% of patients are diagnosed before the age of 40 years. Patients with MPN of reproductive age are being increasingly encountered in clinical practice. Concurrently, there has been increased awareness of the risks of pregnancy complications in patients with MPN and the importance of MPN-specific management to help mitigate these risks. MPN are associated with thrombotic and hemorrhagic complications, and pregnancy may amplify the thrombotic risk. Additionally, MPN may be associated with an increased risk of placental dysfunction and associated complications of preeclampsia, fetal growth restriction, preterm delivery and fetal loss. The aim of this observational study was to report on pregnancy outcomes in a modern cohort of patients with MPN managed according to consensus recommendations. Methods: We conducted a retrospective review of patients with MPN and pregnancy evaluated at either the Princess Margaret Cancer Centre or Mount Sinai Hospital in Toronto, Canada between January 1, 2010 and December 31, 2020. Diagnoses were defined according to the WHO 2016 criteria using information available from hospital records. Descriptive statistics were used to describe selected baseline characteristics. Categorical variables were summarized with counts and percentages. Results: A total of 32 patients with MPN and pregnancy were included in the study (Table 1). The median age at the time of the index pregnancy was 33 (range 21 - 45) years. The most common MPN diagnosis was essential thrombocythemia (ET, n=15), followed by polycythemia vera (PV, n=9) and primary myelofibrosis (PMF, n=8). Driver mutation data was available for 30 patients: 17 (57%) had mutated JAK2, 5 (17%) CALR, and 9 (30%) had no driver mutation identified. Five patients had a prior history of venous thrombosis, all of which were portal vein thrombosis, and 2 patients had a history of bleeding events. Information on antenatal treatment was available for 22 patients: 18 (82%) patients received aspirin, 3 (14%) received antenatal low molecular weight heparin (LMWH) and 3 (14%) received interferon (IFN; interferon alpha 2b in 2 cases and pegylated interferon alfa 2a in 1); 16 (73%) received post-partum LMWH. Information on maternal complications was available for 22 patients. There were 2 thrombotic events (1 antepartum and 1 postpartum) and 1 postpartum hemorrhage. There were no cases of preeclampsia. Of 22 pregnancies, there were 19 live births (86%), 2 first trimester losses (9%) and 1 second trimester loss (5%). Gestational age was 37 weeks or more in 16/17 (94%) and was 33 weeks for 1 patient. Vaginal deliveries were performed in 11/20 (55%) cases and 9/20 (45%) were Cesarean deliveries. Discussion: This observational study represents a modern cohort of MPN patients treated according to consensus recommendations. Our findings highlight that MPN patients have better pregnancy outcomes than those previously described in the literature. Limitations of this retrospective study include a small sample, missing data, and potential underreporting of early pregnancy loss. Pregnancy in patients with MPN is associated with unique risks that may be reduced with interventions such as antepartum aspirin, IFN in higher risk patients, and postpartum LMWH. That not all standard risk patients were managed with aspirin and postpartum LMWH suggests educational opportunities exist for hematologists and maternal-fetal medicine physicians involved in the care of these patients. Figure 1 Figure 1. Disclosures Gupta: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS-Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Honoraria; Pfizer: Consultancy; Roche: Consultancy; Constellation Pharma: Consultancy, Honoraria; Sierra Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Research Funding. Malinowski: Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy. Maze: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene-BMS: Honoraria; Takeda: Research Funding; PharmaEssentia: Research Funding; Kronos Bio: Research Funding.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,007
Tête enseignante GPT0,224
Écart entre enseignants0,217 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission2
Résumé présentoui

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