Objective: A case-cohort study was conducted to investigate associations between occupational exposures and endometrial cancer nested within a large cohort of textile workers in Shanghai, China.

Methods: The study included 176 incident endometrial cancer cases diagnosed from 1989 to 1998 and a randomly-selected age-stratified reference subcohort (n = 3,061). Study subjects' complete work histories were linked to a job-exposure matrix developed specifically for the textile industry to assess occupational exposures. Hazard ratios (HR) and 95% confidence intervals were calculated using Cox proportional hazards modeling adapted for the case-cohort design, adjusting for age at menarche and a composite variable of gravidity and parity.

Results: An increased risk of endometrial cancer was detected among women who had worked for > or =10 years in silk production (HR = 3.8, 95% CI 1.2-11.8) and had exposure to silk dust (HR = 1.7, 95% CI 0.9-3.4). Albeit with few exposed women (two cases and eight subcohort women), there was a 7.4-fold increased risk associated with > or =10 years of silica dust exposure (95% CI 1.4-39.7).

Conclusions: The findings suggest that some textile industry exposures might play a role in endometrial carcinoma and should be further replicated in other occupational settings.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2574926PMC
http://dx.doi.org/10.1002/ajim.20614DOI Listing

Publication Analysis

Top Keywords

endometrial cancer
16
textile workers
8
workers shanghai
8
occupational exposures
8
textile industry
8
increased risk
8
=10 years
8
endometrial
5
occupational
4
occupational risk
4

Similar Publications

Exploring the potential of advanced artificial intelligence technology in predicting microsatellite instability (MSI) and Ki-67 expression of endometrial cancer (EC) is highly significant. This study aimed to develop a novel hybrid radiomics approach integrating multiparametric magnetic resonance imaging (MRI), deep learning, and multichannel image analysis for predicting MSI and Ki-67 status. A retrospective study included 156 EC patients who were subsequently categorized into MSI and Ki-67 groups.

View Article and Find Full Text PDF

Netrin-1 (NTN1) is a laminin-related secreted protein involved in axon guidance and cell migration. Previous research has established a significant connection between NTN1 and nervous system development. In recent years, mounting evidence indicates that NTN1 also plays a crucial role in tumorigenesis and tumor progression.

View Article and Find Full Text PDF

[Solid, endometrial-like and transitional growth patterns of ovarian high-grade serous carcinoma: a clinicopathological analysis of 25 cases].

Zhonghua Bing Li Xue Za Zhi

February 2025

Department of Pathology, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou 215002, China.

To investigate the clinicopathological characteristics of solid, endometrial-like and transitional (SET) cell growth subtype in high-grade serous ovarian carcinoma (HGSC). Clinical data of 25 cases of HGSC-SET were collected from January 2020 to March 2024 at the Affiliated Suzhou Hospital of Nanjing Medical University, and their histological features were analyzed. Immunohistochemical stains were used to analyze the expression of ER, PR, PAX8, WT-1, p16, p53 and Ki-67.

View Article and Find Full Text PDF

To investigate whether the immunohistochemical results of two markers PMS2 and MSH6 (2-MMR) could replace the four markers MLH1, PMS2, MSH2 and MSH6 (4-MMR) to detect mismatch repair deficient (dMMR) cancers. A retrospective analysis was conducted with summary of immunohistochemical data from 7 867 cases of gastric cancer, colorectal cancer, endometrial cancer, and other diseases in the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China, from March 2018 to March 2023. The consistency of 2-MMR and 4-MMR results was examined.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!