Objective: To describe the epidemiological profile of malignant gynecological tumors in a third-level referral medical center located in Western Mexico.
Material And Methods: Cross sectional study. We took the register of patients with cancer confirmed histopathologically at the Gynecology and Obstetrics Hospital, Western National Medical Center. The results are presented as frequencies, means and standard deviations.
Results: We captured 1025 medical charts from patients with cancer between January 1981 and May 2003. Mean age was 51.55 years with 16 to 94 years range. Breast cancer was the most prevalent disease (67.5%) with predominance of the left breast. Bilateral disease was identified in patients 10 years younger than those with unilateral disease. Cervix cancer was the second most common disease (17.2%), followed by ovarian cancer (91 cases; 8.8%), endometrium cancer (44 cases, 4.2%). Clinical stages were II and III in 87% of cases with breast cancer. Stages I and II in 81% of patients with cancer of the cervix, stage III in 39.5% of cases with ovarian carcinoma and stage III in 58% of patients with endometrial carcinoma.
Conclusions: Breast cancer was the first condition of medical care and detected in clinical stages II and III. Cervix was the second even with suboptimal registers. Ovarian cancer was detected in advanced stages in the majority of patients. It is important to register all patients with gynecologic cancer in only one referral hospital in order to obtain better attention. In this way, strategies for medical management improvement could be established. Long-term prognosis of patients may improve.
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World J Surg Oncol
January 2025
Department of Gynecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China.
Objective: This study aimed to evaluate and compare the clinicopathologic features of primary fallopian tubal carcinoma (PFTC) and high-grade serous ovarian cancer (HGSOC) and explore the prognostic factors of these two malignant tumors.
Methods: Fifty-seven patients diagnosed with PFTC from 2006 to 2015 and 60 patients diagnosed with HGSOC from 2014 to 2015 with complete prognostic information were identified at Women's Hospital of Zhejiang University. The clinicopathological and surgical data were collected, and the survival of the patients was followed for 5 years after surgery.
BMC Health Serv Res
January 2025
Institute for Health and Nursing Science, Faculty of Medicine, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.
Background: Cancer requires interdisciplinary intersectoral care. The Care Coordination Instrument (CCI) captures patients' perspectives on cancer care coordination. We aimed to translate, adapt, and validate the CCI for Germany (CCI German version).
View Article and Find Full Text PDFJ Med Case Rep
January 2025
Department of Pathology and Laboratories, University Hospital Fundación Santa Fe de Bogotá, Bogotá, DC, Colombia.
Background: Adenoid cystic carcinoma of the breast is a rare subtype, constituting less than 3.5% of primary breast carcinomas. Despite being categorized as a type of triple-negative breast cancer, it generally has a favorable prognosis.
View Article and Find Full Text PDFWorld J Surg Oncol
January 2025
Institute of Oncology, Tel Aviv Sourasky Medical Center, Weizmann St 6, Tel Aviv, Israel.
Background: De-intensification of anti-cancer therapy without significantly affecting outcomes is an important goal. Omission of axillary surgery or breast radiation is considered a reasonable option in elderly patients with early-stage breast cancer and good prognostic factors. Data on avoidance of both axillary surgery and radiation therapy (RT) is scarce and inconclusive.
View Article and Find Full Text PDFBiomark Res
January 2025
Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, P.R. China.
Background: Disease progression within 24 months (POD24) significantly impacts overall survival (OS) in patients with follicular lymphoma (FL). This study aimed to develop a robust predictive model, FLIPI-C, using a machine learning approach to identify FL patients at high risk of POD24.
Methods: A cohort of 1,938 FL patients (FL1-3a) from seventeen centers nationwide in China was randomly divided into training and internal validation sets (2:1 ratio).
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