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

• 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
• 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

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 化疗所致的周围神经病变(CIPN)是奥沙利铂的主要副作用，奥沙利铂是一种重要的药物 治疗结直肠癌的LINE方案。剂量限制的CIPN阻止了25%的患者接受完整的， 奥沙利铂的最大有效剂量。此外，接受奥沙利铂治疗的患者中有10%-40% 结直肠癌发展为慢性CIPN，疼痛，损害生活质量，并与 更高的阿片类药物使用率。预防CIPN的方法没有取得实质性的成功。 有助于早期预测CIPN的生物标记物将成为共同决策的主要促进者 (例如，改变化疗强度、频率或类型)以预防CIPN，并将患者分层为 CIPN预防的靶向临床试验。为此，我们最近对Allo-ColdTM方法进行了表征 根据冷过敏的动态定量，早期预测CIPN。在初步研究中， 该方法具有良好的灵敏度和特异度。它是非侵入性的、可扩展的，并且有潜力 易于实现，包括在资源不足的情况下。 我们第一阶段STTR计划的主要目标是开发和测试以用户为中心的移动医疗系统 用于收集、存储、聚合和处理患者报告的关于手掌感冒敏感性的数据的原型 预测CIPN。 在目标1中，我们将使用以用户为中心的设计来开发Allo-Cool移动医疗技术原型 接近。我们将使用三层架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。我们将反复测试和改进 原型机。我们将与癌症患者进行访谈，以获得对原型可接受性的反馈，并与 临床医生评估实施障碍。 在目标2中，我们将展示异体冷系统在患者中的依从性和预测性能 正在接受以奥沙利铂为基础的化疗。24例III/IV期结直肠癌患者 接受以奥沙利铂为基础的治疗将使用Allo-冷，并自我报告寒冷疼痛和寒冷不适 每日化疗10周(5个周期)。我们将确定患者的依从性和 我们在预测剂量限制CIPN中的预测算法。 在这份第一阶段的STTR提案中，我们希望通过确认以下几点来确定异体冷系统的可行性 其在奥沙利铂治疗结直肠癌中的可用性、依从性和预测性表现 癌症。第二阶段STTR提案将侧重于完成Allo-Cool作为一种 CIPN的预测性生物标记物，FDA批准和随后的商业化。