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Background: The differential expression of oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2) or Ki-67 between primary tumour and the recurrence has been described. We aimed to determine these changes and their prognostic implications.
Patients And Methods: We retrospectively reviewed 45 breast cancer patients with relapsed biopsy that were classified into local relapse (LR) or metastatic disease (MD) groups. We analyzed the conversion rate and the value of the immunophenotype of the primary tumour and the relapse as a prognostic factor for relapse-free survival (RFS), progression-free survival (PFS) and overall survival (OS).
Results: The conversion rate was 34.8% for Ki-67, 20% for ER, 20% for PR, and 15.6% for HER2. For the LR group, the RFS was 71.9 months and the OS was 141.6 months, without statistical differences according to the immunophenotype of the primary or the relapsed biopsy. For the MD group, the PFS was 20.8 months. According to immunophenotype of the relapse, the PFS were ER+ 24.7 months vs. ER- 9.3 months; PR+ 25.1 months vs. PR- 12.7 months without statistical differences according to HER2 or Ki67. The OS for MD group was 54.4 months without statistical differences according to immunophenotype.
Conclusion: The characteristics of breast cancer can change over the time. Variations of the ER or PR status in MD group have prognostic value for PFS. To perform a biopsy of relapses is warranted in order to establish the prognostic of the current disease, and probably a more accurate treatment.
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http://dx.doi.org/10.1159/000505591 | DOI Listing |
EBioMedicine
September 2025
Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, PR China; Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, PR China. Electronic address:
JMIR Cancer
September 2025
Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.
Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative.
View Article and Find Full Text PDFEpidemiol Serv Saude
September 2025
Universidade Estadual do Norte do Paraná, Programa de Pós-Graduação em Enfermagem em Atenção Primária à Saúde Bandeirantes, PR, Brazil.
Objectives: To analyze the temporal trend and identify spatial clusters of breast cancer mortality in Paraná state between 2012 and 2021.
Methods: This was a time series study, with spatial analysis of breast cancer mortality rates in the 399 municipalities of Paraná. Data were selected from the Mortality Information System.
Cien Saude Colet
August 2025
Faculdade de Medicina da Universidade Federal de Pelotas. Pelotas RS Brasil.
The objective of this study was to analyze the characteristics of avoidable mortality in the population aged five to 69 years living in the city of Pelotas/RS, comparing it with the rest of the state of Rio Grande do Sul, from 2000 to 2021. An ecological study was conducted analyzing avoidable mortality coefficients according to sex and age, from 2000 to 2021. The data source was the Mortality Information System, and the trend analysis was performed using Prais-Winsten regression, with standardization of coefficients.
View Article and Find Full Text PDFCien Saude Colet
August 2025
Programa de Pós-Graduação em Nutrição e Saúde, Universidade Estadual do Ceará. R. Betel 1958, Itaperi. 60714-230 Fortaleza CE Brasil.
This study aimed to evaluate mortality due to female breast cancer attributable to overweight and obesity and to estimate the number of preventable deaths with a reduction in the Body Mass Index in Brazil. An ecological study was carried out with investigation of information on overweight, obesity, sociodemographic characteristics based on a national survey carried out in 2013-14; breast cancer mortality rate in 2019 using the Online Atlas of Mortality and Relative Risk Meta-Analyses. The Potential Impact Fraction analysis was carried out, considering the following counterfactual scenarios related to the reduction in BMI: Scenario A - population contingent of women that make up the prevalence of overweight and obesity now composes the prevalence of eutrophy; Scenario B - population contingent of women that make up the prevalence of overweight starts to make up the prevalence of eutrophy; Scenario C - population contingent of women that make up the prevalence of obesity becomes part of the prevalence of overweight.
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