Second Primary Cancers Following Female Breast Cancer in Osaka, Japan—A Population-Based Cohort Study

PLoS ONE ◽  
2019 ◽  
Vol 14 (9) ◽  
pp. e0222860 ◽  
Author(s):  
Hsin-Hua Chen ◽  
Ching-Heng Lin ◽  
Der-Yuan Chen ◽  
Wen-Cheng Chao ◽  
Yi-Hsing Chen ◽  
...  

PLoS ONE ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. e0148597 ◽  
Author(s):  
Man-Hsin Hung ◽  
Chia-Jen Liu ◽  
Chung-Jen Teng ◽  
Yu-Wen Hu ◽  
Chiu-Mei Yeh ◽  
...  

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 933
Author(s):  
Michael Rosskamp ◽  
Julie Verbeeck ◽  
Sylvie Gadeyne ◽  
Freija Verdoodt ◽  
Harlinde De Schutter

Background: Socio-economic position is associated with cancer incidence, but the direction and magnitude of this relationship differs across cancer types, geographical regions, and socio-economic parameters. In this nationwide cohort study, we evaluated the association between different individual-level socio-economic and -demographic factors, cancer incidence, and stage at diagnosis in Belgium. Methods: The 2001 census was linked to the nationwide Belgian Cancer Registry for cancer diagnoses between 2004 and 2013. Socio-economic parameters included education level, household composition, and housing conditions. Incidence rate ratios were assessed through Poisson regression models. Stage-specific analyses were conducted through logistic regression models. Results: Deprived groups showed higher risks for lung cancer and head and neck cancers, whereas an inverse relation was observed for malignant melanoma and female breast cancer. Typically, associations were more pronounced in men than in women. A lower socio-economic position was associated with reduced chances of being diagnosed with known or early stage at diagnosis; the strongest disparities were found for male lung cancer and female breast cancer. Conclusions: This study identified population groups at increased risk of cancer and unknown or advanced stage at diagnosis in Belgium. Further investigation is needed to build a comprehensive picture of socio-economic inequality in cancer incidence.


2018 ◽  
Vol 8 (1) ◽  
pp. 400-407 ◽  
Author(s):  
Guoqiao Zheng ◽  
Akseli Hemminki ◽  
Asta Försti ◽  
Jan Sundquist ◽  
Kristina Sundquist ◽  
...  

BMJ Open ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. e037069
Author(s):  
Ming Li ◽  
David Roder ◽  
Katina D'Onise ◽  
David Walters ◽  
Gelareh Farshid ◽  
...  

ObjectiveUsing linked cancer registry and administrative data to monitor, tumour, node and metastases (TNM) stage and survival from female breast cancer in Australia.MethodAnalysis of 2000–2014 diagnoses with linked population-based data to investigate: (1) sociodemographic predictors of advanced stage (stages III and IV), using unadjusted and adjusted logistic regression; and (2) sociodemographic factors and stage as predictors of breast cancer survival using competing risk regression.DesignPopulation-based registry cohort.Setting and participants14 759 South Australian women diagnosed in 2000–2014.Primary and secondary outcome measuresStage and survival.ResultsAt diagnosis, 46% of women were classified as stage I, 39% as stage II, 12% as stage III and 4% as stage IV. After adjusting for sociodemographic factors, advanced stage was more common: (1) for ages <50 years; and although not statistically significant, for ages 80+ years; and (2) in women from socioeconomically disadvantaged areas. Compared with 2000–2004 diagnoses, stage and sociodemographic adjusted risks (sub-HRs (SHRs)) of breast cancer death were lower in 2005–2009 (SHR 0.75, 95% CI 0.67 to 0.83) and 2010–2015 (SHR 0.57, 95% CI 0.48 to 0.67). Compared with stage I, the SHR was 3.87 (95% CI 3.32 to 4.53) for stage II, 10.87 (95% CI 9.22 to 12.81) for stage III, and 41.97 (95% CI 34.78 to 50.65) for stage IV. Women aged 70+ years at diagnosis and those living in the most socioeconomically disadvantaged areas were at elevated risk of breast cancer death, independent of stage and sociodemographic factors.ConclusionsStage varied by age, diagnostic period and socioeconomic status, and was a stronger predictor of survival than other statistically significant sociodemographic predictors. Achieving earlier diagnosis outside the original BreastScreen target of 50–69 years (as applying <2014) and in residents of socioeconomically disadvantaged areas likely would increase cancer survival at a population level.


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