Estimating the Environmental Burden in Two Orphan Lung Diseases

估计两种孤儿肺病的环境负担

• 批准号: 7942891
• 负责人: Paul D Blanc
• 金额: $ 49.77万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7942891
• 关键词: Accounting; Address; Age; Air; Air Pollution; Area; Biochemical; Biological Markers; Birds; Breathing; California; Characteristics; Clinical; Clinical Management; Coupled; Data; Data Sources; Databases; Development; Diagnosis; Diagnostic; Disease; Disease Management; Dust; Environment; Environmental Exposure; Environmental Risk Factor; Etiology; Exposure to; Extrinsic allergic alveolitis; Factor Analysis; Farming environment; Functional disorder; Goals; Health Maintenance Organizations; Health Planning; Home environment; Home visitation; House Call; Indoor Air Quality; Interview; Lead; Link; Lung; Lung diseases; Measures; Medical Records; Methods; Metric; Modality; Modeling; Morbidity - disease rate; Neighborhoods; Occupational; Occupations; Odds Ratio; Orphan; Orphan Disease; Outcome; Patients; Pharmaceutical Preparations; Physiological; Pollution; Population; Population Attributable Risks; Prevention strategy; Process; Psyche structure; Pulmonary Alveolar Proteinosis; Recruitment Activity; Relative (related person); Relative Risks; Research; Research Design; Respiratory System; Respiratory tract structure; Risk; Risk Factors; Severities; Severity of illness; Silicon Dioxide; Source; Specific qualifier value; Structure; Telephone Interviews; Testing; Therapeutic; Uncertainty; Universities; adjudication; base; burden of illness; clinically relevant; disorder prevention; experience; medical specialties; mortality; population based; prevent; response; sex

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (03) Biomarker Research and the specific Challenge Area 03-HL-101: "Identify and validate clinically relevant, quantifiable biomarkers" Background: The population attributable fraction (PAF) estimates the amount of a disease that is due to a specific factor, quantifying the burden of disease that would be prevented if that factor was eliminated. For selected orphan lung diseases, quantifying the environmentally-related PAF would provide important guidance for clinicians in diagnosis and disease management and for prevention strategies to reduce the burden of new disease prospectively. Linking biomarker data to other metrics of exposure in an integrated risk modeling approach will yield more accurate PAF estimates. Hypersensitivity pneumonitis (HP) and pulmonary alveolar proteinosis (PAP) are ideal candidate diseases for which to apply this biomarker-linked PAF strategy. Aims: For HP, identifying the relative contributions of currently known environmental factors, as well as un- identified causes, in particular "non-specified" indoor air sources. For PAP, estimating the PAF linked to dust inhalation, in particular silica (including concrete construction) in salaried occupations as well as in non- salaried avocations and, potentially, through ambient point sources. For both HP and PAP, evaluating the association between selected risk factors and disease activity-severity using selected biomarker data to differentiate among cases and between cases and referents. Experimental Plan: Cases and referents recruited through the data base of the Kaiser Permanente Health Plan (KPHP). The case pool will be supplemented through additional recruitment from a University-based sub- specialty pulmonary practice (UCSF). Target recruitment will yield interviews in 125 HP cases and matching referents with home visits in 75 of each; for PAP, 46 interviews and 25 home visits plus referents. Environ- mental exposures and biomarkers will assessed through structured interviews and through home visits. Residential addresses will be geocoded for linkage to supplemental environmental exposure data. Medical record extraction (cases only) will be used to confirm diagnostic consistency and supplement measures of disease severity. Cases will be compared to referents for environmental exposures and biomarkers of disease. Differences between cases and referents for continuous measures will be tested using approaches for continuous parametric and non-parametric variables and Odds Ratios for dichotomous measures, the PAF for the environmentally-related burden of disease will be estimated. Significance: The varying contributions of occupation, outdoor ambient pollution, and home indoor exposures to HP and PAP are likely to be relevant not only for patient diagnosis but also for management and clinical outcomes. Linking biomarker data to other metrics of exposure in an integrated risk modeling approach is key to deriving more accurate PAF estimates, which is why this Challenge Area is so relevant to this question. 7. Project Narrative The goal of this study is to estimate the relative contributions selected environmental risk factors to the burden to two orphan lung diseases, hypersensitivity pneumonitis and pulmonary alveolar proteinosis. Using environmental exposure data, supplemented with biomarker data relevant to disease activity and severity, this project will lead to findings relevant to disease prevention for these specific conditions and, by application of the approach, potentially to other orphan disease as well.

描述（由申请人提供）：本申请涉及广泛的挑战领域 (03) 生物标志物研究和特定挑战领域 03-HL-101：“识别和验证临床相关的、可量化的生物标志物” 背景：群体归因分数 (PAF) 估计特定因素引起的疾病的数量，量化消除该因素后可以预防的疾病负担。对于选定的孤儿肺病，量化与环境相关的 PAF 将为临床医生的诊断和疾病管理以及预防策略提供重要指导，以减少新疾病的负担。在综合风险建模方法中将生物标志物数据与其他暴露指标联系起来将产生更准确的 PAF 估计。过敏性肺炎 (HP) 和肺泡蛋白沉积症 (PAP) 是应用这种生物标志物相关 PAF 策略的理想候选疾病。目标：对于 HP 来说，确定当前已知环境因素的相对贡献以及未确定的原因，特别是“非指定”室内空气源。对于 PAP，估算与粉尘吸入相关的 PAF，特别是受薪职业和非受薪业余领域的二氧化硅（包括混凝土建筑），并可能通过环境点源吸入。对于 HP 和 PAP，使用选定的生物标志物数据评估选定的风险因素与疾病活动严重程度之间的关联，以区分病例以及病例和参照者。实验计划：通过 Kaiser Permanente 健康计划 (KPHP) 数据库招募的病例和参考对象。病例库将通过从大学亚专科肺科诊所（UCSF）额外招募来补充。目标招募将对 125 个 HP 案例进行访谈，并在每个案例中对 75 个案例进行家访匹配；对于 PAP，进行了 46 次访谈和 25 次家访以及推荐人。将通过结构化访谈和家访来评估环境暴露和生物标志物。住宅地址将进行地理编码，以便链接到补充环境暴露数据。病历提取（仅限病例）将用于确认诊断一致性并补充疾病严重程度的衡量标准。病例将与环境暴露和疾病生物标志物的参考对象进行比较。将使用连续参数和非参数变量的方法以及二分法测量的优势比来测试连续测量的病例和参考对象之间的差异，并将估计与环境相关的疾病负担的 PAF。意义：职业、室外环境污染和家庭室内接触 HP 和 PAP 的不同贡献可能不仅与患者诊断相关，而且还与治疗和临床结果相关。在综合风险建模方法中将生物标志物数据与其他暴露指标联系起来是得出更准确的 PAF 估计的关键，这就是为什么该挑战领域与该问题如此相关的原因。 7. 项目叙述 本研究的目的是估计选定的环境风险因素对两种孤儿肺病（过敏性肺炎和肺泡蛋白沉积症）负担的相对贡献。利用环境暴露数据，辅以与疾病活动和严重程度相关的生物标志物数据，该项目将得出与这些特定条件下的疾病预防相关的发现，并通过应用该方法，也可能与其他孤儿疾病相关。