我国城市人群常见癌症所致经济负担及DALY负担评价

Cancer is one of the most important chronic diseases which has caused substantial impact on life expectancy and quality of life worldwide, however in China, data at population-level economic burden of cancer during the past two decades are still limited and poorly comparable, meanwhile, the indicator of disability-adjusted life years (DALYs) has not been commonly applied in local cancer registration report system. The aim of the current proposal is to, at a population level, predict economic burden and DALYs related burden of the six most common cancers in urban populations in China (lung cancer, breast cancer, colorectal cancer, stomach cancer, esophageal cancer and liver cancer). Three components will be carried out. 1) To standardize the multi-center large-scale raw expenditure data on cancer diagnosis and treatment which have been recently collected from a Cancer Screening Program in Urban China (CanSPUC), a key public health program supported by the China’s central government, and also to re-analyze the quality of life and health utility data from the same program to get detailed data sets on disability weights. 2) To build three analyzing models with different complexity, including a cancer-registration-system-based cancer prevalence approach, a time table method, and a complex cancer natural history markov model combined with a multi-cohort method. 3) By applying the standardized expenditure and sorted disability weights data to the three models or platforms, to predict the overall economic burden and DALYs related burden in China on population-level during year 2020-2030, the subgroup analysis will be performed by cancer site, gender, age and calendar year, etc. The study will also compare the results from the three different models to evaluate the robustness of the findings and then to provide a recommendation on the platform. Besides, the proposed project will also develop a face-friendly software to facilitate policy maker’s rapid calculation on economic burden and DALYs. The findings are expected to provide important evidence for priority setting among a range of specific cancers in this population, and also to explore evaluation approach for broader cancers and other chronic diseases.

癌症严重危害生命和生活质量，既往20年我国癌症所致人群层面的经济负担数据仍少见且结果可比性低，以伤残调整生命年（DALY）为指标的癌症疾病负担数据也较缺乏。本课题拟在人群层面评价我国城市人群六种常见癌症（肺、乳腺、结直肠、胃、食管和肝癌）所致的经济负担及DALY疾病负担。课题包含三个单元：1）对近期收集的大样本费用数据进行标准化，同时深入分析生活质量评估数据，以获得标准化全病程诊治费用信息和高精度失能权重数据集。2）构建繁简不同的技术平台：肿瘤登记患病数据平台、寿命表法预测平台和癌症疾病自然史多重队列马尔可夫模型。3）将标准化费用和失能权重参数分别代入三种模型，于人群层面预测全国整体及亚组在2020-2030年癌症相关经济负担和DALY负担；也将比较模型间结果及稳健性，开发核心指标预测工具包以服务快速卫生决策。预期结果可为我国具体癌种防控的优先选择及其他慢性病疾病负担评价工作提供参考。

癌症严重危害生命和生活质量，既往20年我国癌症所致人群层面的经济负担数据仍少见且结果可比性低，以伤残调整生命年（DALY）为指标的癌症疾病负担数据也较缺乏。本课题拟在人群层面评价我国城市人群常见癌症所致的经济负担及DALY疾病负担。四年间按计划方案推进实施，整体上完成了设定研究内容，回答了预设研究问题，三个单元均有产出，具体主要研究内容和结果如下。1）个体费用与健康失能权重信息精细化分析：对多个癌种的例均费用、诊断后不同年份、不同分期等维细化费用信息进行挖掘。就个体生活质量数据细化分析不同癌种、性别、病变程度等维度；采用系统综述方法，整合我国常见癌症失能权重，提炼健康效用转化失能权重的方法；采用现场调查比较不同效用测量工具效度。2）不同繁简程度模型方法构建探索：以肺癌为切入点探索了基于患病率的分析方法。从乳腺癌开始，基于寿命表法进行方法学探索。利用TreeAge构建马尔可夫模型，评价不同繁简程度的自然史模型效度。利用Matlab语言建立最小二乘优化模型求解模型中的复杂参数。3）人群层面经济负担和DALY负担分析：基于前两单元获得的参数集和方法平台，量化了肺癌、肝癌和结直肠癌等在我国人群所致经济负担，并进行了长期预测及不确定因素影响分析。采用患病率方法和本土失能权重，估算乳腺癌在女性人群中的DALY负担及筛查所致影响；系统量化肝癌和结直肠癌等所致人群DALY负担。本课题研究结果可为我国具体癌种防控的优先选择提供参考,为相关防控效果评价提供了详实基线参比，所探索方法也为后续深入研究和其他癌种和慢性病的评价提供了参考。