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Improving the prediction of life expectancy among older adults with advanced cancer using geriatric assessment

使用老年评估改善患有晚期癌症的老年人的预期寿命预测

基本信息

批准号：
10392477
负责人：
Jennifer Lund
金额：
$ 22.52万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-05-01 至 2024-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10392477
关键词：
Address Adult Advanced Malignant Neoplasm Age Aging Calibration Cancer Patient Caregivers Caring Characteristics Chronic Classification Clinical Clinical Data Cluster randomized trial Cognitive Communication Communities Community Clinical Oncology Program Complex Data Data Linkages Decision Making Discrimination Disease Elderly Evaluation Family Future Geriatric Assessment Goals Health Heterogeneity Impaired cognition Individual Lead Life Life Expectancy Link Malignant Neoplasms Measures Medical Medicare Methods Modeling National Institute on Aging Nutritional status Oncologist Oncology Outcome Palliative Care Patient Self-Report Patients Performance Performance Status Personal Satisfaction Physical Performance Polypharmacy Population Positioning Attribute Predictive Analytics Prognosis Provider Quality of Care Reporting Research Research Support Role Sampling Social support Statistical Methods Syndrome Testing Training Translating Universities Vital Status Vulnerable Populations Work age related aged analytical method base cancer care cancer therapy cancer type comorbidity cost data resource demographics design functional disability functional status improved individualized medicine mortality mortality risk multidisciplinary novel older patient patient oriented patient population patient-clinician communication predictive modeling preference prognostic prognostic model prognostication programs psychologic shared decision making statistics tool treatment planning

项目摘要

ABSTRACT Predicting life expectancy in older adults with advanced (stage IV or incurable stage III) cancers is challenging due to heterogeneity in the presence of chronic conditions and geriatric syndromes, which independently increase the risk of death. Accurate prediction and communication of life expectancy is a key component of shared decision-making for older adults with advanced cancers and their providers. However, evidence shows that oncologists tend to overestimate life expectancy in older adults with advanced cancer. Standard tools currently available for predicting life expectancy perform poorly in this population. The geriatric assessment is a set of validated, patient-reported and objective measures to assess comorbidity, functional status, physical performance, cognitive status, psychological status, nutritional status, polypharmacy, and social support, and has potential to improve prediction of life expectancy for older adults with advanced cancer. Yet, no studies have explicitly sought to harness information captured from the geriatric assessment to develop a clinical prediction model for life expectancy in older adults with advanced cancers. This study will leverage detailed information from geriatric assessment and advanced statistical methods to develop and validate a new life expectancy prediction model for older adults (age 70 and over) with advanced cancer. We will then evaluate the extent of improvement in predictive performance of this new GA model compared with oncologists’ self- reported estimates of life expectancy and a model based on routinely collected clinical data (age, comorbidities, and performance status). To achieve these aims, we will link the most up-to-date vital status data from the Medicare program with detailed geriatric assessments for >800 patients aged 70 years and older with advanced cancer and their oncologists participating in two community-based, cluster-randomized trials. Our multidisciplinary study team has the requisite expertise in data linkage, predictive modeling, geriatric oncology, and palliative care to conduct this research and translate our findings into meaningful advances for this vulnerable population. Our work will lead to the develop of a clinical prediction tool that can be used in future experimental work to test whether the life expectancy prediction model based on geriatric assessment can improve patient-provider communication about prognosis and the delivery of high-quality, patient-centered cancer care.

摘要