Identifying and Treating Those at Risk: Disparities in Rapid Relapse Among TNBC Patients in the National Cancer Database.

Health disparities Social determinants of health Triple negative breast cancer

Journal

Annals of surgical oncology
ISSN: 1534-4681
Titre abrégé: Ann Surg Oncol
Pays: United States
ID NLM: 9420840

Informations de publication

Date de publication:
13 Jun 2024
Historique:
received: 10 01 2024
accepted: 09 05 2024
medline: 14 6 2024
pubmed: 14 6 2024
entrez: 13 6 2024
Statut: aheadofprint

Résumé

This study was designed to characterize features of rapid relapse TNBC (rrTNBC), an aggressive, poor prognosis breast cancer subset using the National Cancer Database (NCDB). Patients diagnosed with TNBC between 2010 and 2019 within NCDB were included in analyses. rrTNBC was defined as all-cause mortality ≤24 months from diagnosis. Patient demographic, tumor, and treatment association with rrTNBC were evaluated in univariate, bivariate analyses, and multiple logistic regression models. Two-part models are used to compare receipt of treatment (i.e., receipt of both chemotherapy and breast surgery) versus not in its relationship with rrTNBC. Overall, 14.5% of patients were categorized as rrTNBC. Age older than 75 years (-41.3%), Black race (-1.4%), Medicare (-2.6%), and Charlson-Deyo score ≥2 (-4.9%) were associated with a lower probability of receiving both chemotherapy and breast surgery. Not receiving both treatments (vs. receiving both chemotherapy and breast surgery) was associated with a two-to-three-fold higher probability of rrTNBC among patients aged older than 75 years (16.6% vs. 6%), having Medicare (3.6% vs. 1.6%), and Charlson-Deyo score ≥2 (16.6% vs. 5.9%). Age, insurance, and comorbidity were related to a lower likelihood of treatment; yet receiving treatment reduced the risk of rrTNBC threefold for each. These findings might be valuable to inform clinical care delivery, as well as future research that examines treatment protocols among diverse patients.

Identifiants

pubmed: 38872045
doi: 10.1245/s10434-024-15507-2
pii: 10.1245/s10434-024-15507-2
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

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Auteurs

Saurabh Rahurkar (S)

Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA. saurabh.rahurkar@osumc.edu.
The Center for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research, The Ohio State University, Columbus, OH, USA. saurabh.rahurkar@osumc.edu.

Pallavi Jonnalagadda (P)

The Center for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research, The Ohio State University, Columbus, OH, USA.

Daniel Stover (D)

Department of Internal Medicine, The Ohio State University, Columbus, OH, USA.

Barbara Andersen (B)

Department of Psychology, The Ohio State University, Columbus, OH, USA.

Demond Handley (D)

Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.

Mohamed I Elsaid (MI)

Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.

J C Chen (JC)

Division of Surgical Oncology, Department of Surgery, The Ohio State University, Columbus, OH, USA.

Samilia Obeng-Gyasi (S)

The Center for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research, The Ohio State University, Columbus, OH, USA.
Division of Surgical Oncology, Department of Surgery, The Ohio State University, Columbus, OH, USA.

Classifications MeSH