Detalhes bibliográficos
| Ano de defesa: |
2018 |
| Autor(a) principal: |
Menezes, Max Oliveira |
| Orientador(a): |
Gonçalves, Leila Luíza Conceição |
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Não Informado pela instituição
|
| Programa de Pós-Graduação: |
Pós-Graduação em Enfermagem
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Palavras-chave em Espanhol: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://ri.ufs.br/jspui/handle/riufs/8572
|
Resumo: |
Introduction: Breast cancer stands out in the female population due to its high incidence and mortality. It is seen as a serious public health problem, especially in developing countries, where there are perceptible gaps in breast cancer care, especially regarding the identification of prognostic factors predictive of survival in women with this neoplasm. Biological characteristics intrinsic to carcinogenesis, clinical stage and socioeconomic factors are highlighted. Objective: To analyze predictors of survival in female breast cancer. Method: This is a retrospective observational cohort study of women diagnosed with assisted breast cancer at a clinical oncology service of a philanthropic hospital, located in a capital of the Northeast. The data were extracted from secondary sources by means of a structured script. The study population consisted of 100 women diagnosed with breast cancer started neoadjuvant or adjuvant chemotherapy, between 08/01/2011 and 31/12/2012, in the service where they were performed the research. The data were analyzed in a descriptive way and analytical. The MedCalc Statistical Software version 18 was used. Survival curves are presented as Kaplan-Meier curves, and the meaning was classified by the Log-rank test. The Cox regression model was used for multivariate prognostic analysis, and a binary logistic regression model was used to analyze the clinical factors of influence. Results: Most of the women were aged 50 or over, lived with a partner, had schooling less than or equal to eight years, family income between R$ 200.00 and R$ 1200.00 and lived outside the state capital. The sign most frequently mentioned by the women, who determined the search for health care was the nodule, and was identified through accidental palpation. Multivariate analysis using the Cox multivariate regression model with forced entry method showed that staging was an independent factor that affected the specific survival curve of women with breast cancer. The specific five-year survival rate for the non-advanced stage was 88.5%. Binary logistic regression identified that the advanced stage, age ≥50 years and delayed search for health care after identification of signs and symptoms were associated with death for women with breast cancer. Conclusion: It was identified that among the prognostic factors, the staging, has a significant impact on the reduction of the specific survival rates. It is essential to strengthen actions in primary health care, in addition to the implementation of an organized and permanent screening program.________________________________________________________________________________________________________________________________ |
