A clinical prediction rule for identifying South African colorectal cancer patients who will fail to engage in oncology care

用于识别无法参与肿瘤护理的南非结直肠癌患者的临床预测规则

基本信息

批准号：
10295819
负责人：
Yoshan Moodley
金额：
$ 5.9万
依托单位：
UNIVERSITY OF KWAZULU-NATAL
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：
2021-09-02 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10295819
关键词：
Address Adherence Advisory Committees Algorithmic Analysis Applications Grants Appointment Artificial Intelligence Award Biopsy Books Caring Characteristics Clinic Clinic Visits Clinical Colorectal Cancer Communities Competence Country Coupled Data Data Collection Data Sources Decision Making Diagnosis Disease Disease Management Enrollment Epidemiologist Failure Funding Future Government Grant Health Care Sector Healthcare Systems Intention Intervention Laboratories Literature Logistic Regressions Machine Learning Malignant Neoplasms Malignant neoplasm of gastrointestinal tract Mentors Meta-Analysis Newly Diagnosed Oncologist Oncology Operative Surgical Procedures Outcome Outcome Study Patient-Focused Outcomes Patients Population Prevention strategy Program Development Public Health Public Sector Publishing Research Research Assistant Research Personnel Resources Review Literature South Africa South African Specialist Statistical Data Interpretation Surgical Oncologist Surgical Oncology Surveys Time Training Universities Validation Visit Vocational Guidance advanced disease base burden of illness care systems career development clinical practice cohort colon cancer patients colorectal cancer screening comorbidity data registry design electronic data electronic registry feature selection flexibility high risk improved machine learning algorithm machine learning method model development mortality neural network novel patient registry predictive modeling prospective random forest scale up screening screening program sociodemographics statistics support vector machine systematic review tool

项目摘要

PROJECT SUMMARY/ABSTRACT Colorectal cancer (CRC) is an emerging public health problem in South Africa (SA). Preliminary research from KwaZulu-Natal (KZN), SA shows that 23% of newly diagnosed CRC patients in the public healthcare sector will fail to engage in oncology care (FEOC). This complicates oncologists’ and oncologic surgeons’ efforts to effectively manage CRC disease in this setting. There are a variety of resource-intensive interventions for addressing FEOC. However, implementing these in all newly diagnosed CRC patients would be unfeasible, given the high patient volumes and existing resource constraints in the SA public healthcare sector. A clinical prediction rule (CPR) is proposed for identifying newly diagnosed SA CRC patients who are at high risk of FEOC, thereby enabling more efficient targeting of these specific, high risk patients for interventions which seek to address FEOC. The CPR will be developed by: 1) Identifying potential predictors of FEOC in CRC populations through a systematic review of the literature and a survey of 109 patients; 2) Constructing an appropriate electronic data collection tool that will streamline prospective data collection for these potential predictors and the study outcome, FEOC, from a cohort of 398 newly diagnosed CRC patients; and 3) Applying machine learning methods to the data to derive and internally validate the CPR. The CPR will be an important first step in tackling the high FEOC rates amongst newly diagnosed CRC patients in KZN, SA and will ultimately contribute toward improving both CRC disease management and patient outcomes in this setting. The proposed K43 research has the potential to be scaled up to the national level, and this will be the basis of a future R01 grant application. Dr. Moodley (K43 applicant) wants to become an independent gastrointestinal cancer epidemiologist and a global leader in CPRs, particularly CPRs that seek to address breakdowns in linkage to care and reduce the burden of disease attributed to gastrointestinal cancers, such as CRC. This award will provide him with protected time to conduct the proposed research and engage in an intensive career development program while based at one of the top universities in SA, the University of KwaZulu-Natal. He will be mentored by esteemed senior researchers from SA (Prof. Thandinkosi Madiba, University of KwaZulu-Natal) and the US (Prof. Ravi Pokala Kiran, Columbia University) who have a strong track record of mentoring young researchers. A research advisory committee, comprised of other senior researchers, will provide additional research and career guidance to Dr. Moodley. This will be coupled with didactic and “hands on” training in the core competencies required to develop CPRs. It is envisioned that by the end of his K43 training, Dr. Moodley will have developed the proposed CPR and generated new preliminary data. He will use this new data to successfully apply for an R01 grant, thus establishing his independence as gastrointestinal cancer epidemiologist and a global leader in CPRs.

项目概要/摘要结直肠癌 (CRC) 是南非 (SA) 的一个新出现的公共卫生问题。南非夸祖鲁-纳塔尔省 (KZN) 表明，公共医疗部门新诊断的 CRC 患者中有 23% 将未能参与肿瘤护理（FEOC），这使肿瘤科医生和肿瘤外科医生的努力变得复杂。在这种情况下有效管理结直肠癌疾病有多种资源密集型干预措施。然而，在所有新诊断的 CRC 患者中实施这些措施是不可行的，鉴于南澳州公共医疗保健部门的患者数量较多且现有资源有限。提出预测规则（CPR），用于识别新诊断的 SA CRC 患者，这些患者具有高风险 FEOC，从而能够更有针对性地针对这些特定的高风险患者进行有效的干预措施为了解决 FEOC，CPR 将通过以下方式制定： 1) 确定 CRC 人群中 FEOC 的潜在预测因子。通过对文献的系统回顾和对 109 名患者的调查 2) 构建适当的模型；电子数据收集工具将简化这些潜在预测因素的预期数据收集，来自 398 名新诊断的 CRC 患者的研究结果 FEOC；以及 3) 应用机器；学习数据的方法来导出和内部验证 CPR 将是重要的第一步。违反了 KZN、SA 新诊断的 CRC 患者的高 FEOC 率，并将最终做出贡献旨在改善这种情况下的 CRC 疾病管理和患者预后。研究有可能扩大到国家层面，这将成为未来 R01 拨款的基础 Moodley 博士（K43 申请人）希望成为一名独立的胃肠道癌症流行病学家。以及心肺复苏 (CPR) 领域的全球领导者，特别是致力于解决护理和减少疾病相关问题的心肺复苏 (CPR) 该奖项将为他提供归因于胃肠道癌症（例如结直肠癌）的疾病负担。受保护的时间进行拟议的研究并参与密集的职业发展计划，同时他将在南澳顶尖大学之一夸祖鲁纳塔尔大学接受指导。来自南非（夸祖鲁纳塔尔大学 Thandinkosi Madiba 教授）和美国（Ravi 教授）的高级研究人员 Pokala Kiran（哥伦比亚大学），在指导年轻研究人员方面拥有良好的记录。由其他高级研究人员组成的咨询委员会将提供额外的研究和职业指导这将与所需核心能力的教学和“实践”培训相结合。预计在 K43 培训结束时，Moodley 博士将制定出拟议的心肺复苏术。 CPR 并生成新的初步数据，他将使用这些新数据成功申请 R01 补助金。确立了他作为胃肠道癌症流行病学家和心肺复苏领域全球领导者的独立性。