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：
10480832
负责人：
Yoshan Moodley
金额：
$ 6.15万
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/10480832
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 Resource-limited setting 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 gradient boosting 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.

项目摘要/摘要大肠癌（CRC）是南非（SA）的新兴公共卫生问题。初步研究 SA夸祖鲁 - 纳塔尔省（KZN）表明，公共医疗保健部门的新诊断的CRC患者中有23％将无法从事肿瘤学护理（FEOC）。这使肿瘤学家和肿瘤学外科医生的努力变得复杂在这种情况下有效地管理CRC疾病。有多种资源密集型干预措施致辞。但是，在所有已诊断出的CRC患者中实施这些都是不可行的，鉴于SA公共医疗保健部门的患者量较高和现有资源限制。临床提出了预测规则（CPR），以识别具有高风险的新诊断的SA CRC患者 FeoC，从而使这些特定的高风险患者更有效地针对寻求干预措施解决Feoc。 CPR将通过以下方式开发：1）确定CRC种群中FEOC的潜在预测指标通过对文献的系统评价和对109名患者的调查； 2）构建适当的电子数据收集工具将简化这些潜在预测指标和从398名新诊断的CRC患者组成的研究结果FEOC，FEOC； 3）应用机器对数据的学习方法得出并在内部验证CPR。心肺复苏将是重要的第一步在解决KZN，SA中新诊断的CRC患者中的高度FEOC率时，最终将贡献在这种情况下，要改善CRC疾病管理和患者结果。拟议的K43 研究有可能扩展到国家一级，这将是未来R01赠款的基础应用。 Moodley博士（K43应用程序）希望成为一名独立的胃肠道癌流行病学家以及CPRS的全球领导者，特别是寻求解决链接的分解以进行护理和减少的CPR 疾病的伯宁归因于胃肠道癌，例如CRC。这个奖项将为他提供保护进行拟议研究并参与密集的职业发展计划的时间夸祖鲁·纳塔尔大学SA的顶级大学之一。他将受到尊敬 SA的高级研究人员（Thandinkosi Madiba教授，夸祖鲁 - 纳塔尔大学）和美国（Ravi教授哥伦比亚大学的Pokala Kiran）在指导年轻研究人员方面拥有良好的记录。研究由其他高级研究人员组成的咨询委员会将提供其他研究和职业指导致穆德利博士。这将与需要的核心能力的教学法和“动手”培训相结合开发CPR。可以预见的是，在他的K43培训结束时，Moodley博士将开发出拟议的 CPR并生成了新的初步数据。他将使用这些新数据成功申请R01赠款，因此确立他作为胃肠道癌症的独立性，并且是CPRS的全球领导者。