Sex differences in adults with acute myeloid leukemia and the impact of sex on overall survival.

AML acute myeloid leukemia sex differences survival treatment treatment adverse events

Journal

Cancer medicine
ISSN: 2045-7634
Titre abrégé: Cancer Med
Pays: United States
ID NLM: 101595310

Informations de publication

Date de publication:
03 2023
Historique:
revised: 17 10 2022
received: 08 09 2022
accepted: 11 11 2022
medline: 5 4 2023
pubmed: 25 11 2022
entrez: 24 11 2022
Statut: ppublish

Résumé

There is a male predominance of acute myeloid leukemia (AML) incidence, but survival data are conflicting. The objective of this study is to carry out a comprehensive analysis of sex differences in AML, and to investigate the impact of sex disparities in survival. The cohort included patients ≥18 years diagnosed with AML (2010-2022). Demographics, treatment patterns, treatment adverse events, and survival were analyzed. The population was described and compared by sex, and sex-based risks and associations were obtained via Cox proportional-hazards regression. In total, 1020 AML patients were analyzed (57.4% males), with lower risk of death for females (aHR = 0.41, 95% CI 0.26-0.66). Among females, BMT (aHR = 0.51, 95% CI 0.27-0.97), hospitalization record (aHR = 0.65, 95%CI 0.45-0.93), and higher appointment completion rates (aHR = 0.98, 95% CI 0.98-0.98) were associated with lower risk of death. Overall, and similarly in males, higher age at diagnosis (aHR = 1.03, 95% CI 1.02-1.04) and a TP53 mutation (aHR = 2.24, 95% CI 1.69-2.97) were associated with higher risk of death. Sex differences exist in both AML incidence and overall survival. Treatment and health care factors should be addressed by caregivers and public policies developed to reduce mortality rates and mitigate existing sex differences.

Sections du résumé

BACKGROUND
There is a male predominance of acute myeloid leukemia (AML) incidence, but survival data are conflicting. The objective of this study is to carry out a comprehensive analysis of sex differences in AML, and to investigate the impact of sex disparities in survival.
METHODS
The cohort included patients ≥18 years diagnosed with AML (2010-2022). Demographics, treatment patterns, treatment adverse events, and survival were analyzed. The population was described and compared by sex, and sex-based risks and associations were obtained via Cox proportional-hazards regression.
RESULTS
In total, 1020 AML patients were analyzed (57.4% males), with lower risk of death for females (aHR = 0.41, 95% CI 0.26-0.66). Among females, BMT (aHR = 0.51, 95% CI 0.27-0.97), hospitalization record (aHR = 0.65, 95%CI 0.45-0.93), and higher appointment completion rates (aHR = 0.98, 95% CI 0.98-0.98) were associated with lower risk of death. Overall, and similarly in males, higher age at diagnosis (aHR = 1.03, 95% CI 1.02-1.04) and a TP53 mutation (aHR = 2.24, 95% CI 1.69-2.97) were associated with higher risk of death.
CONCLUSION
Sex differences exist in both AML incidence and overall survival. Treatment and health care factors should be addressed by caregivers and public policies developed to reduce mortality rates and mitigate existing sex differences.

Identifiants

pubmed: 36419242
doi: 10.1002/cam4.5461
pmc: PMC10067038
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

6711-6721

Subventions

Organisme : NCI NIH HHS
ID : P20 CA233255
Pays : United States

Informations de copyright

© 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

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Auteurs

Nickolas Stabellini (N)

Graduate Education Office, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
Department of Hematology-Oncology, University Hospitals Seidman Cancer Center, Cleveland, Ohio, USA.
Faculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, Brazil.
Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.

Benjamin Tomlinson (B)

Department of Hematology-Oncology, University Hospitals Seidman Cancer Center, Cleveland, Ohio, USA.

Jennifer Cullen (J)

Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
Case Comprehensive Cancer Center, Cleveland, Ohio, USA.

John Shanahan (J)

Cancer Informatics, Seidman Cancer Center at University Hospitals of Cleveland, Cleveland, Ohio, USA.

Kristin Waite (K)

Division of Cancer Epidemiology and Genetics (DCEG), Trans-Divisional Research Program (TDRP), National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Alberto J Montero (AJ)

Department of Hematology-Oncology, University Hospitals Seidman Cancer Center, Cleveland, Ohio, USA.

Jill S Barnholtz-Sloan (JS)

Division of Cancer Epidemiology and Genetics (DCEG), Trans-Divisional Research Program (TDRP), National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Center for Biomedical Informatics and Information Technology (CBIIT), National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Nelson Hamerschlak (N)

Oncohematology Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.

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