Objective: Improvement in cancer survival over recent decades has not been accompanied by a narrowing of socioeconomic disparities. This study aimed to quantify the loss of life expectancy(LOLE) resulting from a cance...Objective: Improvement in cancer survival over recent decades has not been accompanied by a narrowing of socioeconomic disparities. This study aimed to quantify the loss of life expectancy(LOLE) resulting from a cancer diagnosis and examine disparities in LOLE based on area-level socioeconomic status(SES).Methods: Data were collected for all people between 50 and 89 years of age who were diagnosed with cancer, registered in the NSW Cancer Registry between 2001 and 2019, and underwent mortality follow-up evaluations until December 2020. Flexible parametric survival models were fitted to estimate the LOLE by gender and area-level SES for 12 common cancers.Results: Of 422,680 people with cancer, 24% and 18% lived in the most and least disadvantaged areas, respectively. Patients from the most disadvantaged areas had a significantly greater average LOLE than patients from the least disadvantaged areas for cancers with high survival rates, including prostate [2.9 years(95% CI: 2.5±3.2 years) vs. 1.6 years(95% CI: 1.3±1.9 years)] and breast cancer [1.6 years(95% CI: 1.4±1.8 years) vs. 1.2 years(95% CI: 1.0±1.4 years)]. The highest average LOLE occurred in males residing in the most disadvantaged areas with pancreatic [16.5 years(95% CI: 16.1±16.8 years) vs. 16.2 years(95% CI: 15.7±16.7 years)] and liver cancer [15.5 years(95% CI: 15.0±16.0 years) vs. 14.7 years(95% CI: 14.0±15.5 years)]. Females residing in the least disadvantaged areas with thyroid cancer [0.9 years(95% CI: 0.4±1.4 years) vs. 0.6 years(95% CI: 0.2±1.0 years)] or melanoma [0.9 years(95% CI: 0.8±1.1 years) vs. 0.7 years(95% CI: 0.5±0.8 years)] had the lowest average LOLE.Conclusions: Patients from the most disadvantaged areas had the highest LOLE with SES-based differences greatest for patients diagnosed with cancer at an early stage or cancers with higher survival rates, suggesting the need to prioritise early detection and reduce treatment-related barriers and survivorship challenges to improve life expectancy.展开更多
矿产资源开采引发的地表沉陷积水是高潜水位矿区耕地资源破坏的重要原因,也是制约矿山绿色发展的瓶颈之一。面向矿区沉陷积水早期监测识别需求,建立了基于多时相合成孔径雷达(SAR)遥感影像的矿区沉陷积水监测方法,命名为矿区雷达水分指...矿产资源开采引发的地表沉陷积水是高潜水位矿区耕地资源破坏的重要原因,也是制约矿山绿色发展的瓶颈之一。面向矿区沉陷积水早期监测识别需求,建立了基于多时相合成孔径雷达(SAR)遥感影像的矿区沉陷积水监测方法,命名为矿区雷达水分指数(Mining-area Radar Water Index,MRWI)。以山东省龙堌镇某井工(地下开采)煤矿区为研究区域,收集并处理了2017年哨兵1号(Sentinel-1)GRD产品IW模式29景10 m空间分辨率的SAR影像数据,进行了沉陷区积水的动态监测及其演变分析。利用查准率P(precision)、查全率R(recall)以及两者的调和平均数F1这3种定量指标,对比分析了MRWI与光学水体指数(Visible and Shortwave Infrared Drought Index,VSDI)和单时相雷达水体指数(Sentinel-1 Dual-polarized Water Index,SDWI)的监测性能。结果表明:对于存在明显地表水体覆盖区域,MRWI、VSDI以及SDWI均能有效识别出水体范围,其中MRWI与VSDI相比的P、R和F1平均值分别达到了94.45%、94.83%和94.46%;MRWI与SDWI相比,P、R和F1平均值分别达到了99.86%、94.03%和96.85%。MRWI具有较强的沉陷积水早期监测能力,以2号积水区为例,MRWI在2017年6月6日监测到了沉陷积水现象,此时VSDI和SDWI均不能指示这一现象;在2017年7月12日左右,沉陷积水导致地表被水体覆盖,此时MRWI、VSDI和SDWI均能指示出沉陷积水现象。MRWI具备较强的时序监测能力,基于Sentinel-1雷达数据的MRWI能够做到至少每12 d为一期的时序监测,并且能够利用长时序的结果对矿区沉陷区积水变化进行时空演变趋势分析。MRWI可为高潜水位矿区沉陷积水现象的早期监测与治理提供有力技术支撑。展开更多
基金supported by National Health and Research Council of Australia Leadership Investigator Grants (NHMRCAPP1194679)+1 种基金the ACPCC has received equipment and a funding contribution from Roche Molecular Diagnostics USAco-PI on a major implementation programme Elimination of Cervical Cancer in the Western Pacific,which has received support from the Minderoo Foundation。
文摘Objective: Improvement in cancer survival over recent decades has not been accompanied by a narrowing of socioeconomic disparities. This study aimed to quantify the loss of life expectancy(LOLE) resulting from a cancer diagnosis and examine disparities in LOLE based on area-level socioeconomic status(SES).Methods: Data were collected for all people between 50 and 89 years of age who were diagnosed with cancer, registered in the NSW Cancer Registry between 2001 and 2019, and underwent mortality follow-up evaluations until December 2020. Flexible parametric survival models were fitted to estimate the LOLE by gender and area-level SES for 12 common cancers.Results: Of 422,680 people with cancer, 24% and 18% lived in the most and least disadvantaged areas, respectively. Patients from the most disadvantaged areas had a significantly greater average LOLE than patients from the least disadvantaged areas for cancers with high survival rates, including prostate [2.9 years(95% CI: 2.5±3.2 years) vs. 1.6 years(95% CI: 1.3±1.9 years)] and breast cancer [1.6 years(95% CI: 1.4±1.8 years) vs. 1.2 years(95% CI: 1.0±1.4 years)]. The highest average LOLE occurred in males residing in the most disadvantaged areas with pancreatic [16.5 years(95% CI: 16.1±16.8 years) vs. 16.2 years(95% CI: 15.7±16.7 years)] and liver cancer [15.5 years(95% CI: 15.0±16.0 years) vs. 14.7 years(95% CI: 14.0±15.5 years)]. Females residing in the least disadvantaged areas with thyroid cancer [0.9 years(95% CI: 0.4±1.4 years) vs. 0.6 years(95% CI: 0.2±1.0 years)] or melanoma [0.9 years(95% CI: 0.8±1.1 years) vs. 0.7 years(95% CI: 0.5±0.8 years)] had the lowest average LOLE.Conclusions: Patients from the most disadvantaged areas had the highest LOLE with SES-based differences greatest for patients diagnosed with cancer at an early stage or cancers with higher survival rates, suggesting the need to prioritise early detection and reduce treatment-related barriers and survivorship challenges to improve life expectancy.
文摘矿产资源开采引发的地表沉陷积水是高潜水位矿区耕地资源破坏的重要原因,也是制约矿山绿色发展的瓶颈之一。面向矿区沉陷积水早期监测识别需求,建立了基于多时相合成孔径雷达(SAR)遥感影像的矿区沉陷积水监测方法,命名为矿区雷达水分指数(Mining-area Radar Water Index,MRWI)。以山东省龙堌镇某井工(地下开采)煤矿区为研究区域,收集并处理了2017年哨兵1号(Sentinel-1)GRD产品IW模式29景10 m空间分辨率的SAR影像数据,进行了沉陷区积水的动态监测及其演变分析。利用查准率P(precision)、查全率R(recall)以及两者的调和平均数F1这3种定量指标,对比分析了MRWI与光学水体指数(Visible and Shortwave Infrared Drought Index,VSDI)和单时相雷达水体指数(Sentinel-1 Dual-polarized Water Index,SDWI)的监测性能。结果表明:对于存在明显地表水体覆盖区域,MRWI、VSDI以及SDWI均能有效识别出水体范围,其中MRWI与VSDI相比的P、R和F1平均值分别达到了94.45%、94.83%和94.46%;MRWI与SDWI相比,P、R和F1平均值分别达到了99.86%、94.03%和96.85%。MRWI具有较强的沉陷积水早期监测能力,以2号积水区为例,MRWI在2017年6月6日监测到了沉陷积水现象,此时VSDI和SDWI均不能指示这一现象;在2017年7月12日左右,沉陷积水导致地表被水体覆盖,此时MRWI、VSDI和SDWI均能指示出沉陷积水现象。MRWI具备较强的时序监测能力,基于Sentinel-1雷达数据的MRWI能够做到至少每12 d为一期的时序监测,并且能够利用长时序的结果对矿区沉陷区积水变化进行时空演变趋势分析。MRWI可为高潜水位矿区沉陷积水现象的早期监测与治理提供有力技术支撑。
