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.

项目总结/摘要 化疗引起的周围神经病变（CIPN）是奥沙利铂（第一治疗的关键药物）的主要副作用 治疗结肠直肠癌的一线方案。剂量限制性CIPN阻止>25%的患者接受完全， 最大有效剂量的奥沙利铂。此外，10-40%接受奥沙利铂治疗的患者 结直肠癌发展为慢性CIPN，这是痛苦的，损害生活质量，并与 阿片类药物使用率较高。预防CIPN的方法尚未取得有意义的成功。 一种可以帮助早期预测CIPN的生物标志物将成为共同决策的主要促进者 (i.e.改变化疗强度、频率或类型）以预防CIPN，并对患者进行分层， 针对CIPN预防的临床试验。为此，我们最近表征了Allo-ColdTM方法 用于CIPN的早期预测，基于冷超敏反应的动态定量。在初步研究中， 该方法显示出有希望的灵敏度和特异性。它是非侵入性的，可扩展的，并且具有潜力 易于实施，包括在资源匮乏的环境中。 我们第一阶段STTR提案的主要目标是开发和测试一个以用户为中心的移动的医疗系统 用于收集、存储、聚集和处理患者报告的关于手掌冷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开发Allo-Cold移动的健康技术原型 approach.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风险预测的移动的应用程序的存储和数据逻辑组件。我们将反复测试和完善 原型。我们将与癌症患者进行访谈，以获得原型可接受性的反馈， 临床医生评估实施障碍。 在目标2中，我们将证明Allo-Cold系统在患者中的依从性和预测性能 接受以奥沙利铂为基础的化疗24例III/IV期结直肠癌患者 接受奥沙利铂为基础的治疗将使用Allo-Cold，并自我报告冷痛和冷不适 每日一次，持续10周（5个周期）化疗。我们将确定患者的依从性和 我们的预测算法在预测剂量限制CIPN。 在第一阶段STTR提案中，我们希望通过确认以下内容来确定Allo-Cold系统的可行性： 其在基于奥沙利铂的结直肠癌治疗背景下的可用性、依从性和预测性能 癌第二阶段STTR提案将重点完成Allo-Cold作为一种 CIPN的预测生物标志物，以获得FDA批准和随后的商业化。