Clinical biomarker for early prediction of chemotherapy-induced peripheral neuropathy

早期预测化疗引起的周围神经病变的临床生物标志物

基本信息

批准号：
10604018
负责人：
Simon Haroutounian
金额：
$ 40.32万
依托单位：
NEWVENTUREIQ, LLC
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-19 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10604018
关键词：
Acute Adherence Adoption Affect Agreement Algorithms Analgesics Antineoplastic Agents Architecture Area Biological Markers Biopsy Cancer Patient Cancer Survivor Caring Characteristics Chemotherapy-induced peripheral neuropathy Chronic Clinical Clinical Trials Colorectal Colorectal Cancer Communication Complication Data Data Collection Data Reporting Data Set Data Storage and Retrieval Development Devices Dose Dose Limiting Early identification Environment Equipment Feedback Frequencies Goals Hand Health Technology Health system Home Hypersensitivity Hypersensitivity skin testing Impairment Individual Intervention Interview Legal patent Life Logic Malignant neoplasm of gastrointestinal tract Measures Medical Device Metals Methods Morbidity - disease rate Neural Conduction Opioid Outcome Pain Paper Patient Self-Report Patient risk Patient-Centered Care Patient-Focused Outcomes Patients Performance Pharmaceutical Preparations Phase Prevention Prospective Studies Quality of life ROC Curve Regimen Reporting Resource-limited setting Resources Risk Rod Schedule Self Assessment Sensitivity and Specificity Skin Small Business Technology Transfer Research System Technology Temperature Testing Universities Validation Washington chemotherapy clinical biomarkers clinical decision support clinical decision-making colorectal cancer treatment commercial application commercialization compliance behavior cost data management digital health duloxetine early detection biomarkers implementation barriers implementation evaluation improved mHealth mobile application novel opioid use oxaliplatin pain symptom patient stratification prediction algorithm predictive marker prescription opioid prevent prospective prototype public health relevance risk prediction risk stratification shared decision making side effect success symptomatic improvement technological innovation tool usability user centered design

项目摘要

Project Summary / Abstract Chemotherapy induced peripheral neuropathy (CIPN) is a major side effect of oxaliplatin, a key drug in 1st line regimens for treating colorectal cancer. Dose-limiting CIPN prevents >25% of patients from receiving full, maximally effective dose of oxaliplatin. In addition, 10-40% of patients receiving oxaliplatin-based therapy for colorectal cancer with develop chronic CIPN, which is painful, impairs quality of life, and is associated with higher opioid use rates. Approaches for CIPN prevention have not yielded meaningful success. A biomarker that can help with early prediction of CIPN will be a major facilitator of shared decision making (i.e. changing chemotherapy intensity, frequency, or type) to prevent CIPN, and in stratifying patients to targeted clinical trials for CIPN prevention. To that end, we have recently characterized the Allo-ColdTM method for early prediction of CIPN, based on dynamic quantification of cold hypersensitivity. In preliminary studies, the method demonstrated promising sensitivity and specificity. It is non-invasive, scalable, and has a potential to be readily implementable, including in low-resource settings. Our main goal for this Phase I STTR proposal is to develop and test a user-centered mobile health system prototype for collecting, storing, aggregating and processing patient-reported data on palmar cold sensitivity to predict CIPN. In Aim 1, we will develop the Allo-Cold mobile health technology prototype using a user-centered design approach. We will use three-tier architecture to develop the patient user interface, data management and storage, and data logic components of a mobile app for CIPN risk prediction. We will iteratively test and refine the prototype. We will conduct interviews with cancer patients for feedback on prototype acceptability, and with clinicians to assess implementation barriers. In Aim 2, we will demonstrate adherence and predictive performance of Allo-Cold system in patients undergoing oxaliplatin-based chemotherapy. Twenty-four patients with stage III/IV colorectal cancer undergoing oxaliplatin-based therapy will use Allo-Cold, and self-report cold pain and cold unpleasantness daily for 10 weeks (5 cycles) of chemotherapy. We will determine patient adherence and the performance of our predictive algorithm in predicting dose-limiting CIPN. In this Phase I STTR proposal, we expect to determine the feasibility of the Allo-Cold system by confirming its usability, adherence, and predictive performance in the context of oxaliplatin-based therapy for colorectal cancer. Phase II STTR proposal will focus on completing full clinical and analytical validation of Allo-Cold as a predictive biomarker for CIPN, toward FDA approval and subsequent commercialization.

项目摘要 /摘要化学疗法诱导的周围神经病（CIPN）是奥沙利铂的主要副作用，奥沙利铂是1st中的关键药物治疗结直肠癌的线方案。限制剂量的CIPN可防止25％的患者接受全部奥沙利铂的最大有效剂量。此外，接受基于奥沙利铂的治疗的患者中有10-40％结直肠癌具有发展慢性CIPN，这是痛苦的，会损害生活质量，并且与较高的阿片类药物使用率。预防CIPN的方法尚未取得有意义的成功。可以帮助早期预测CIPN的生物标志物将是共同决策的主要促进者（即改变化疗强度，频率或类型）以防止CIPN，并将患者分层为针对预防CIPN的临床试验。为此，我们最近表征了Allo-ColdTM方法对于CIPN的早期预测，基于冷过敏性的动态定量。在初步研究中，该方法表现出有希望的灵敏度和特异性。它是无创的，可扩展的，并且具有潜力可以易于实现，包括在低资源设置中。我们这阶段I STTR提案的主要目标是开发和测试以用户为中心的移动卫生系统用于收集，存储，汇总和处理患者报告的有关手掌冷敏感的数据的原型预测CIPN。在AIM 1中，我们将使用以用户为中心的设计开发Allo-Cold移动健康技术原型方法。我们将使用三层体系结构来开发患者用户界面，数据管理和用于CIPN风险预测的移动应用程序的存储和数据逻辑组件。我们将迭代测试和完善原型。我们将对癌症患者进行访谈，以寻求原型的反馈，并与临床医生评估实施障碍。在AIM 2中，我们将展示患者中Allo-Cold系统的依从性和预测性能接受奥沙利铂的化学疗法。 24例III/IV期结肠癌患者接受奥沙利铂的疗法将使用异源，自我报告冷痛和冷不愉快每天持续10周（5个周期）化学疗法。我们将确定患者的依从性和表现我们在预测剂量限制CIPN方面的预测算法。在此阶段I STTR提案中，我们希望通过确认Allo-Cold系统的可行性在基于奥沙利铂的疗法的情况下，其可用性，依从性和预测性能癌症。第二阶段的STTR提案将重点侧重完成对Allo-Cold的全面临床和分析验证 CIPN的预测生物标志物，朝着FDA批准和随后的商业化。