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Enregistrement W3214319350 · doi:10.1182/blood-2021-149221

Impact of Race/Ethnicity on Cancer Associated Thrombosis Among Underserved Patients with Cancer

2021· article· en· W3214319350 sur OpenAlexaff
Wilson Luiz da Costa, Danielle Guffey, Raka Bandyo, Courtney D. Wallace, Carolina Granada, Romil Patel, Margaret Fitzgerald, Elizabeth Y. Chiao, David García, Marc Carrier, Christopher I. Amos, Ang Li

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueVenous Thromboembolism Diagnosis and Management
Établissements canadiensOttawa HospitalUniversity of Ottawa
Organismes subventionnairesnon disponible
Mots-clésMedicineCancerPulmonary embolismDeep veinThrombosisIncidence (geometry)Internal medicineCumulative incidenceRetrospective cohort studyMalignancyCohort

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Cancer-associated thrombosis (CAT) is common among patients with cancer. Risk factors for CAT include type of malignancy, advanced stage, and chemotherapy treatment, but the association of CAT with race and ethnicity remains controversial. Identifying the incidence of CAT among populations susceptible to inequalities in healthcare delivery may help delineate preventive strategies. Methods: We performed a retrospective cohort study at Harris Health System (HHS), a safety-net healthcare system that provides care for underserved minorities and uninsured patients in Houston, TX. We created an integrated database that linked consecutive patients with newly diagnosed invasive cancer with structured electronic health record (EHR) data from 2011-2020 (Figure 1). We followed patients from time of cancer diagnosis to time of first VTE, death, or loss of follow-up. VTE was defined as radiologically confirmed pulmonary embolism (PE), lower extremity deep vein thrombosis (LE-DVT), catheter-related DVT (CR-DVT), or splanchnic vein thrombosis in either inpatient or outpatient setting. We used VTE ICD9/ICD10 billing codes to assess for potential events and confirmed incident, recurrent, and historical events through medical record review. VTE occurring within 30 days prior to cancer diagnosis were considered as CAT at diagnosis. Incidence rates were assessed per 100 person-year (py) within 1 year of diagnosis and stratified by race/ethnicity, cancer type, and cancer stage. Cumulative incidence of VTE was assessed through competing risk method with death as the competing cause. Multivariable Fine-Gray competing risk models were performed to determine the effect of race/ethnicity on the risk of CAT, adjusted for age, sex, body mass index, insurance, cancer site, stage, systemic therapy, recent hospitalization, and prior history of VTE. Results: A total of 9,353 cancer patients were included in the study, where 49.3% were Hispanics, 27.6% were Non-Hispanic Blacks (NHB), 15.5% were Non-Hispanic Whites (NHW), and 7.6% were Asian/Pacific Islander (PI). Most patients (74.7%) were uninsured, 35.8% were obese, 19% had recent hospitalization, and 31.9% had stage IV disease. Overall, 832 developed CAT within 1 year, including 49.4% PE, 28.1% LE-DVT, and 17.1% CR-DVT. The median onset was 69 days (IQR 20-154), but a significant proportion (n=92) was diagnosed in the month before diagnosis. The incidence of CAT was 7.3% at 6 months and 9.6% at 1 year. The overall incidence rate was 11/100 py with a similar trend from 2011 to 2020. Figure 2 shows the variation in incidence rates for different cancer types across stages. The rate increased 2- to 10-fold from stage I to IV, reaching >40/100 py among patients with pancreatic and upper gastrointestinal cancers. Figure 3 shows the impact of race/ethnicity on the incidence of CAT, with 9.3% and 8.4% for NHW and NHB at 6 months, compared to 6.5% and 3.8% for Hispanics and Asian/PI, respectively. In the adjusted multivariable analysis, the risk of CAT remained lower in Hispanics vs. NHW (SHR 0.80 [0.65-0.97]) and Asian/PI vs. NHW (SHR 0.48 [0.32-0.73]). There was no difference in NHB vs. NHW (SHR 1.04 [0.84-1.27]). Other important covariates included history of VTE (SHR 2.29 [1.32-3.97]) and prolonged hospitalization (SHR 1.53 [CI 1.31-1.80]) in addition to staging and cancer types. Compared to no systemic therapy or adjuvant endocrine only, there was a higher incidence of VTE in patients receiving chemotherapy (SHR 1.72 [1.39-2.15]), targeted therapy (SHR 1.58 [1.12-2.23]), immunotherapy (SHR 2.13 [1.30-3.48], but not non-adjuvant endocrine therapy (SHR 0.91 [0.40-2.08]). Conclusion: In the current cancer registry-linked EHR cohort with a high proportion of Hispanics and Blacks from a large safety-net healthcare system in the US, we have observed a high incidence rate of CAT at 11/100 py. This rate is much higher than 3.9-5.8/100 py reported in contemporary cancer registries in Europe (PMID 27709226, 33171494), and likely reflects advanced disease and comorbidity at the time of diagnosis due to delayed care from the lack of health insurance. Despite adjusting for patient-, cancer-, and treatment-specific confounders, we found that Hispanics and Asian/PI had ~20% and ~50% lower rate of VTE, respectively, compared to NHW or NHB. This racial/ethnicity difference should be considered in future risk assessment models for CAT. Figure 1 Figure 1. Disclosures Carrier: Sanofi Aventis: Honoraria, Membership on an entity's Board of Directors or advisory committees; LEO Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Aspen: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Honoraria; Servier: Honoraria.

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)0,001
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 enseignants0,016
Score d'incertitude au seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
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 savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,026
Tête enseignante GPT0,305
Écart entre enseignants0,279 · 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

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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