Socioeconomic inequality in prostate cancer diagnostics, primary treatment, rehabilitation, and mortality in Sweden

医学 前列腺癌 社会经济地位 优势比 危险系数 前列腺切除术 置信区间 内科学 癌症 人口学 肿瘤科 人口 环境卫生 社会学
作者
Ulf Strömberg,Anders Berglund,Stefan Carlsson,Camilla Thellenberg Karlsson,Mats Lambe,Ingela Franck Lissbrant,Pär Stattin,Ola Bratt
出处
期刊:International Journal of Cancer [Wiley]
卷期号:155 (4): 637-645 被引量:3
标识
DOI:10.1002/ijc.34932
摘要

Abstract We designed a nationwide study to investigate the association between socioeconomic factors (household income and education) and different aspects of prostate cancer care, considering both individual‐ and neighbourhood‐level variables. Data were obtained from Prostate Cancer data Base Sweden (PCBaSe), a research database with data from several national health care registers including clinical characteristics and treatments for nearly all men diagnosed with prostate cancer in Sweden. Four outcomes were analysed: use of pre‐biopsy magnetic resonance imaging (MRI) in 2018–2020 ( n = 11,843), primary treatment of high‐risk non‐metastatic disease in 2016–2020 ( n = 6633), rehabilitation (≥2 dispensed prescriptions for erectile dysfunction within 1 year from surgery in 2016–2020, n = 6505), and prostate cancer death in 7770 men with high‐risk non‐metastatic disease diagnosed in 2010–2016. Unadjusted and adjusted odds and hazard ratios (OR/HRs) with 95% confidence intervals (CIs) were calculated. Adjusted odds ratio (ORs) comparing low versus high individual education were 0.74 (95% CI 0.66–0.83) for pre‐biopsy MRI, 0.66 (0.54–0.81) for primary treatment, and 0.82 (0.69–0.97) for rehabilitation. HR gradients for prostate cancer death were significant on unadjusted analysis only (low vs. high individual education HR 1.41, 95% CI 1.17–1.70); co‐variate adjustments markedly attenuated the gradients (low vs. high individual education HR 1.10, 95% CI 0.90–1.35). Generally, neighbourhood‐level analyses showed weaker gradients over the socioeconomic strata, except for pre‐biopsy MRI. Socioeconomic factors influenced how men were diagnosed with prostate cancer in Sweden but had less influence on subsequent specialist care. Neighbourhood‐level socioeconomic data are more useful for evaluating inequality in diagnostics than in later specialist care.
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