Evidence map›Paper›PMID 28615951›Full record

ArticleBreast cancer : basic and clinical research2017

Long-Term Cause-Specific Mortality After Surgery for Women With Breast Cancer: A 20-Year Follow-Up Study From Surveillance, Epidemiology, and End Results Cancer Registries.

Gabriel Escarela, Alan Jiménez-Balandra, Gabriel Núñez-Antonio, Antonio Gordillo-Moscoso

Abstract read
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Article in Breast cancer : basic and clinical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

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2citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Gabriel EscarelaDepartamento de Matemáticas, Universidad Autónoma Metropolitana-Unidad Iztapalapa, Mexico City (CDMX), Mexico.
Alan Jiménez-BalandraDepartamento de Matemáticas, Universidad Autónoma Metropolitana-Unidad Iztapalapa, Mexico City (CDMX), Mexico.
Gabriel Núñez-AntonioDepartamento de Matemáticas, Universidad Autónoma Metropolitana-Unidad Iztapalapa, Mexico City (CDMX), Mexico.
Antonio Gordillo-MoscosoFacultad de Medicina, Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResearch into long-term cause-specific mortality of women diagnosed with breast cancer is important because it allows for the splitting of the population into patients who eventually die from breast cancer and from other causes. The adoption of this approach helps to identify patients with an elevated risk of eventual death from breast cancer.

objectiveThe primary aim of this study was to examine the associations between both sociodemographic and clinicopathologic characteristics and the underlying risks of death from breast cancer and from other causes for women diagnosed with breast cancer. A second aim was to propose a predictive biomarker of cause-specific mortality in terms of treatment and several important characteristics of a patient.

methodsA cohort of 16 511 female patients diagnosed with breast cancer in 1990 was obtained from the Surveillance, Epidemiology, and End Results cancer registries and followed for 20 years. A mixture model for the regression analysis of competing risks was used to identify factors and confounders that affected either the eventual cause-specific mortality or conditional cause-specific hazard rates, or both. Missing data were handled with multiple imputation.

resultsCurvilinear relationships of age at diagnosis along with race, marital status, breast cancer type, tumor size, estrogen receptor status, extension, lymph node status, type of surgery, and radiotherapy status were significant risk factors for the cause-specific mortality, with extension and lymph node status appearing to be confounded with the effects of both type of surgery and radiotherapy status. The score obtained from combining a set of predictors showed to be an accurate predictive biomarker.

conclusionsIn cause-specific mortality of women diagnosed breast cancer, prognosis appears to depend on both sociodemographic and clinicopathologic factors. The predictive biomarker proposed in this study may help identifying the level of seriousness of the disease earlier than traditional methods, potentially guiding future allocation of resources for better patient care and management strategies.

Indexed as

Breast carcinomacauses of deathhazards modelslogistic modelrisk assessmentrisk factors

Identifiers

PMID28615951
PMCPMC5459512

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.