Molecular subtypes as a prognostic breast cancer factor in women users of the São Paulo public health system, Brazil.

OBJECTIVE: This study aimed to analyze the prognosis of women with breast cancer by molecular subtypes, sociodemographic variables, and clinical and treatment characteristics. METHODS: This hospital-based retrospective cohort study analyzed 1,654 women over 18 years of age diagnosed with invasive breast cancer from 2000 to 2018. Data were extracted from Brazil's Oncocenter Foundation of São Paulo. The variables analyzed were age, histology, molecular subtypes, clinical staging, treatment type, and diagnosis-to-treatment time. Cox regression analysis was applied to estimate death risk. RESULTS: Women with HER-2-positive (nonluminal) and triple-negative molecular subtypes were more than twice more likely to be at risk of death, with adjusted hazard ratio - HRadj=2.30 (95% confidence interval - 95%CI 1.34-3.94) and HRadj=2.51 (95%CI 1.61-3.92), respectively. A delayed treatment associated with an advanced clinical stage at diagnosis increased fourfold the risk of death (HRadj=4.20 (95%CI 2.36-7.49). CONCLUSION: In summary, besides that interaction between advanced clinical stage and longer time between diagnosis and treatment, HER-2-positive (nonluminal) and triple-negative phenotypes were associated with a worse prognosis. Therefore, actions to reduce barriers in diagnosis and treatment can provide better outcome, even in aggressive phenotypes.

Molecular subtypes as a prognostic breast cancer factor in women users of the São Paulo public health system, Brazil / Subtipos moleculares como fator prognóstico do câncer de mama em mulheres usuárias do sistema público de saúde de São Paulo, Brasil

ABSTRACT Objective: This study aimed to analyze the prognosis of women with breast cancer by molecular subtypes, sociodemographic variables, and clinical and treatment characteristics. Methods: This hospital-based retrospective cohort study analyzed 1,654 women over 18 years of age diagnosed with invasive breast cancer from 2000 to 2018. Data were extracted from Brazil's Oncocenter Foundation of São Paulo. The variables analyzed were age, histology, molecular subtypes, clinical staging, treatment type, and diagnosis-to-treatment time. Cox regression analysis was applied to estimate death risk. Results: Women with HER-2-positive (nonluminal) and triple-negative molecular subtypes were more than twice more likely to be at risk of death, with adjusted hazard ratio — HRadj=2.30 (95% confidence interval — 95%CI 1.34-3.94) and HRadj=2.51 (95%CI 1.61-3.92), respectively. A delayed treatment associated with an advanced clinical stage at diagnosis increased fourfold the risk of death (HRadj=4.20 (95%CI 2.36-7.49). Conclusion: In summary, besides that interaction between advanced clinical stage and longer time between diagnosis and treatment, HER-2-positive (nonluminal) and triple-negative phenotypes were associated with a worse prognosis. Therefore, actions to reduce barriers in diagnosis and treatment can provide better outcome, even in aggressive phenotypes.

RESUMO Objetivo: O objetivo deste estudo foi analisar o prognóstico de mulheres com câncer de mama de acordo com os subtipos moleculares, variáveis sociodemográficas, características clínicas e de tratamento. Métodos: Este foi um estudo de coorte retrospectivo de base hospitalar. Foram analisadas 1.654 mulheres maiores de 18 anos diagnosticadas com câncer de mama invasivo entre 2000 a 2018. Os dados foram extraídos da Fundação Oncocentro de São Paulo, Brasil. As variáveis analisadas foram idade, histologia, subtipo moleculares, estadiamento clínico, tipo de tratamento e tempo entre o diagnóstico e tratamento. A análise de regressão de Cox foi aplicada para estimar o risco de morte. Resultados: As mulheres que apresentaram os subtipos moleculares HER-2-positivo (não luminal) e triplo negativo tiveram risco de morte quase duas vezes maior respectivamente, com razão de risco ajustada — HRaj=2,30 (intervalo de confiança de 95% — 95%IC 1,34-3,94) e HRaj=2,51 (95%IC 1,61-3,92). O atraso no tratamento associado ao avanço do estadiamento clínico ao diagnóstico aumentou em quatro vezes o risco de morte (HRaj=4,20 (IC95% 2,36-7,49). Conclusão: Os fenótipos HER-2-positivo (não luminal) e triplo negativo, além da interação entre estágio clínico avançado e maior tempo entre o diagnóstico e o tratamento, associaram-se a pior prognóstico. Assim, ações para reduzir as barreiras no diagnóstico e tratamento podem proporcionar melhores resultados, mesmo em fenótipos agressivos.

Differences in mortality of cancer patients with COVID-19 in a Brazilian cancer center.

INTRODUCTION: To analyze COVID-19 mortality in cancer patients and associated factors such as age, sex, type of insurance, situation at COVID-19 diagnosis, and cancer histology during the pandemic at a cancer center in Brazil. METHODS: Cross-sectional study carried out from April 02, 2020 to August 31, 2020 at A.C. Camargo Cancer Center (ACCCC), in São Paulo, Brazil. Cases were extracted from the Hospital Cancer Registry. COVID-19 lethality rates by histology were calculated; multiple logistic regression was used to identify factors associated with COVID-19 mortality. The log-rank test was applied to compare the survival curves for each variable. RESULTS: Of the 411 patients analyzed, 51 (12.4%) died due to COVID-19. Death occurred at an average age of 63 years. The fatality rate was higher for lung (0.333) and hematological (0.213) cancers and was associated with age over 60 years. The greatest chances of death from COVID-19 were in cases of lung (odds ratio, OR, 4.05, 95% confidence interval, CI 1.33-12.34) and hematological (OR 2.17, 95% CI 0.96-4.90) cancers, and in patients currently undergoing cancer treatment (OR 2.77, 95% CI 1.25-6.13). There were no statistical differences in survival by sex, age group, type of insurance, situation at the diagnosis of COVID-19, and histology of cancer for COVID-19. CONCLUSIONS: Mortality due to COVID-19 in cancer patients is heterogeneous. These findings reinforce the need for individualized strategies for the management of different types of cancer that reduce the risk of death from COVID-19.