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Practice patterns and real-life outcomes for patients with acute promyelocytic leukemia in the United States.
Bewersdorf, Jan Philipp; Prozora, Stephanie; Podoltsev, Nikolai A; Shallis, Rory M; Huntington, Scott F; Neparidze, Natalia; Wang, Rong; Zeidan, Amer M; Davidoff, Amy J.
Afiliação
  • Bewersdorf JP; Department of Internal Medicine, Yale School of Medicine and Yale Cancer Center, New Haven, CT.
  • Prozora S; Yale Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, New Haven, CT.
  • Podoltsev NA; Yale School of Medicine, Department of Pediatrics, Section of Hematology and Oncology, Yale University, New Haven, CT.
  • Shallis RM; Department of Internal Medicine, Yale School of Medicine and Yale Cancer Center, New Haven, CT.
  • Huntington SF; Yale Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, New Haven, CT.
  • Neparidze N; Department of Internal Medicine, Yale School of Medicine and Yale Cancer Center, New Haven, CT.
  • Wang R; Department of Internal Medicine, Yale School of Medicine and Yale Cancer Center, New Haven, CT.
  • Zeidan AM; Yale Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, New Haven, CT.
  • Davidoff AJ; Department of Internal Medicine, Yale School of Medicine and Yale Cancer Center, New Haven, CT.
Blood Adv ; 6(2): 376-385, 2022 01 25.
Article em En | MEDLINE | ID: mdl-34724703
ABSTRACT
Acute promyelocytic leukemia (APL) is associated with a favorable long-term prognosis if appropriate treatment is initiated promptly. Outcomes in clinical trials and population-based registries vary; potential explanations include a delay in treatment and lower adherence to guideline-recommended therapy in real-world practice. We used the Vizient Clinical Data Base to describe demographic characteristics, baseline clinical characteristics, and treatment patterns in patients newly diagnosed with APL during the study period of April 2017 to March 2020. Baseline white blood cell count was used to assign risk status and assess treatment concordance with National Comprehensive Cancer Network guidelines. Logistic regression models examined adjusted associations between patient, hospital, disease characteristics, and adverse outcomes (in-hospital death or discharge to hospice). Among 1464 patients with APL, 205 (14.0%) experienced an adverse outcome. A substantial subset (20.6%) of patients did not receive guideline-concordant regimens. Odds of adverse outcomes increased with failure to receive guideline-concordant treatment (odds ratio [OR], 2.31; 95% confidence interval [CI], 1.43-3.75; P = .001), high-risk disease (OR, 2.48; 95% CI, 1.53-4.00; P < .001), and increasing age (≥60 years OR, 11.13; 95% CI, 4.55-27.22; P < .001). Higher hospital acute myeloid leukemia (AML) patient volume was associated with lower odds of adverse outcome (OR, 0.44; 95% CI, 0.20-0.99 [for ≤50 vs >200 AML patients per year]; P = .046). In conclusion, in this large database analysis, 14.0% of patients newly diagnosed with APL died or were discharged to hospice. A substantial proportion of patients did not receive guideline-concordant therapy, potentially contributing to adverse outcomes.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Leucemia Mieloide Aguda / Leucemia Promielocítica Aguda Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Leucemia Mieloide Aguda / Leucemia Promielocítica Aguda Idioma: En Ano de publicação: 2022 Tipo de documento: Article