Competing Risk of Death in Elderly Patients with Newly Diagnosed Stage I Breast Cancer.


Journal

Journal of the American College of Surgeons
ISSN: 1879-1190
Titre abrégé: J Am Coll Surg
Pays: United States
ID NLM: 9431305

Informations de publication

Date de publication:
07 2019
Historique:
received: 08 01 2019
revised: 18 03 2019
accepted: 18 03 2019
pubmed: 2 4 2019
medline: 19 5 2020
entrez: 2 4 2019
Statut: ppublish

Résumé

The majority of newly diagnosed breast cancers in the US are in women aged older than 65 years who can have additional comorbidities. Balancing the risks and benefits of treatment should take into account these competing risks of death. The Surveillance, Epidemiology, and End Results Program-Medicare database was used to identify women with stage I breast cancer undergoing operations from 2004-2012. Using neural network analysis, comorbidities associated with mortality were grouped into clinically relevant categories. Cumulative incidence graphs and Fine and Gray competing risk regression analyses were used to study the association of age, race, comorbidity groupings, and tumor variables with 3 competing mortality outcomes: dead of disease (DOD), dead of other cancers (DOC), and non-cancer death (NCD). The overall cumulative incidence of mortality was 4.9% for DOD, 3.7% for DOC, and 21.3% for NCD for the 47,220 patients studied. For all patients, the 5- and 8-year probability of DOD was 3% and 4.7%, for DOC 1.9% and 3.5%, and for NCD 9.8% and 18.9%, respectively. The presence of any major comorbidity (eg cardiovascular or neurologic disorders) significantly increased the probability of NCD, and estrogen receptor status was the strongest predictor of DOD. Given patient age, comorbidity, and estrogen receptor status, an estimate of competing risks of death from DOD, DOC, and NCD can be calculated. To aid clinical decision making, we quantify competing risks of death in patients with stage I breast cancer by taking into account patient age, comorbidity, and estrogen receptor status.

Sections du résumé

BACKGROUND
The majority of newly diagnosed breast cancers in the US are in women aged older than 65 years who can have additional comorbidities. Balancing the risks and benefits of treatment should take into account these competing risks of death.
STUDY DESIGN
The Surveillance, Epidemiology, and End Results Program-Medicare database was used to identify women with stage I breast cancer undergoing operations from 2004-2012. Using neural network analysis, comorbidities associated with mortality were grouped into clinically relevant categories. Cumulative incidence graphs and Fine and Gray competing risk regression analyses were used to study the association of age, race, comorbidity groupings, and tumor variables with 3 competing mortality outcomes: dead of disease (DOD), dead of other cancers (DOC), and non-cancer death (NCD).
RESULTS
The overall cumulative incidence of mortality was 4.9% for DOD, 3.7% for DOC, and 21.3% for NCD for the 47,220 patients studied. For all patients, the 5- and 8-year probability of DOD was 3% and 4.7%, for DOC 1.9% and 3.5%, and for NCD 9.8% and 18.9%, respectively. The presence of any major comorbidity (eg cardiovascular or neurologic disorders) significantly increased the probability of NCD, and estrogen receptor status was the strongest predictor of DOD. Given patient age, comorbidity, and estrogen receptor status, an estimate of competing risks of death from DOD, DOC, and NCD can be calculated.
CONCLUSIONS
To aid clinical decision making, we quantify competing risks of death in patients with stage I breast cancer by taking into account patient age, comorbidity, and estrogen receptor status.

Identifiants

pubmed: 30930100
pii: S1072-7515(19)30234-0
doi: 10.1016/j.jamcollsurg.2019.03.013
pii:
doi:

Types de publication

Journal Article Multicenter Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

30-36.e1

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2019 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Auteurs

Nabil Wasif (N)

Department of Surgery, Division of Surgical Oncology, Mayo Clinic Arizona, Phoenix, AZ; Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Surgical Outcomes Program, Mayo Clinic Arizona, Phoenix, AZ. Electronic address: wasif.nabil@mayo.edu.

Matthew Neville (M)

Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Surgical Outcomes Program, Mayo Clinic Arizona, Phoenix, AZ; Department of Biostatistics, Mayo Clinic Arizona, Phoenix, AZ.

Richard Gray (R)

Department of Surgery, Division of Surgical Oncology, Mayo Clinic Arizona, Phoenix, AZ.

Patricia Cronin (P)

Department of Surgery, Division of Surgical Oncology, Mayo Clinic Arizona, Phoenix, AZ.

Barbara A Pockaj (BA)

Department of Surgery, Division of Surgical Oncology, Mayo Clinic Arizona, Phoenix, AZ.

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