诊断后生命损失年数(FLYLAD):以人为中心的癌症负担指标。

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Population Health Metrics Pub Date : 2023-09-13 DOI:10.1186/s12963-023-00314-w
David Banham, Jonathan Karnon, Alex Brown, David Roder, John Lynch
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引用次数: 0

摘要

背景:癌症控制举措是通过量化通过有效干预减轻癌症负担的能力来实现的。使用卫生行政数据的负担措施是支持监测和评估患者和人群结果的可持续方式。诊断后生命损失年数(FLYLAD)就是这样一种负担衡量标准。我们使用1990年至2010年南澳大利亚土著人和非土著人的数据来显示FLYLAD如何量化癌症负担的差异:人口之间;在诊断阶段可用的亚人群队列之间;以及当随访被限制在诊断后24个月时。方法:FLYLADCances是指每个人因癌症(YLLcancer)而失去的预期寿命与癌症诊断(LYAR)时面临风险的预期寿命之比。全球疾病负担标准寿命表提供了参考预期寿命。FLYLADCances是针对1990年至2010年在南澳大利亚诊断的癌症病例进行估计的。癌症诊断阶段也适用于在土著人和一组非土著人中诊断的癌症,按性别、出生年份、原发癌症部位和诊断年份匹配。结果:癌症诊断(N = 144891)包括777名原住民。FLYLACancer描述的癌症负担在土著人中高于非土著人(0.55,95%CI 0.52-0.59对0.39,95%CI 0.39-0.40)。在土著人的年轻诊断中,LYAR高7年(31.0,95%CI 30.0-32.0对24.1,95%CI 24.1-24.2),癌症早期死亡率较高(YLLcancer = 16.3,95%CI 15.1-17.5与YLLcancer = 8.2、95%置信区间8.2-8.3)影响了这一点。匹配的原住民和非原住民队列之间的癌症负担差异在诊断为FLYLADCancec后24个月分别表现为0.44,95%CI 0.40-0.47和0.28,95%CI 0.25-0.31。结论:FLYLAD描述了土著人癌症负担不成比例地高,包括:所有被诊断为癌症的人;匹配的队列;以及在被诊断为同一阶段疾病的组内。诊断后24个月差异明显。这证明土著人民有很大的能力受益于癌症控制举措,特别是那些能够早期发现和治疗癌症的举措。FLYLAD使用现成的个人级行政记录可以帮助评估解决这一需求的医疗保健举措。
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The fraction of life years lost after diagnosis (FLYLAD): a person-centred measure of cancer burden.

Background: Cancer control initiatives are informed by quantifying the capacity to reduce cancer burden through effective interventions. Burden measures using health administrative data are a sustainable way to support monitoring and evaluating of outcomes among patients and populations. The Fraction of Life Years Lost After Diagnosis (FLYLAD) is one such burden measure. We use data on Aboriginal and non-Aboriginal South Australians from 1990 to 2010 to show how FLYLAD quantifies disparities in cancer burden: between populations; between sub-population cohorts where stage at diagnosis is available; and when follow-up is constrained to 24-months after diagnosis.

Method: FLYLADcancer is the fraction of years of life expectancy lost due to cancer (YLLcancer) to life expectancy years at risk at time of cancer diagnosis (LYAR) for each person. The Global Burden of Disease standard life table provides referent life expectancies. FLYLADcancer was estimated for the population of cancer cases diagnosed in South Australia from 1990 to 2010. Cancer stage at diagnosis was also available for cancers diagnosed in Aboriginal people and a cohort of non-Aboriginal people matched by sex, year of birth, primary cancer site and year of diagnosis.

Results: Cancers diagnoses (N = 144,891) included 777 among Aboriginal people. Cancer burden described by FLYLADcancer was higher among Aboriginal than non-Aboriginal (0.55, 95% CIs 0.52-0.59 versus 0.39, 95% CIs 0.39-0.40). Diagnoses at younger ages among Aboriginal people, 7 year higher LYAR (31.0, 95% CIs 30.0-32.0 versus 24.1, 95% CIs 24.1-24.2) and higher premature cancer mortality (YLLcancer = 16.3, 95% CIs 15.1-17.5 versus YLLcancer = 8.2, 95% CIs 8.2-8.3) influenced this. Disparities in cancer burden between the matched Aboriginal and non-Aboriginal cohorts manifested 24-months after diagnosis with FLYLADcancer 0.44, 95% CIs 0.40-0.47 and 0.28, 95% CIs 0.25-0.31 respectively.

Conclusion: FLYLAD described disproportionately higher cancer burden among Aboriginal people in comparisons involving: all people diagnosed with cancer; the matched cohorts; and, within groups diagnosed with same staged disease. The extent of disparities were evident 24-months after diagnosis. This is evidence of Aboriginal peoples' substantial capacity to benefit from cancer control initiatives, particularly those leading to earlier detection and treatment of cancers. FLYLAD's use of readily available, person-level administrative records can help evaluate health care initiatives addressing this need.

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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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