Predictive Biosignature for Endoscopic Therapy for Chronic Pancreatitis Pain

慢性胰腺炎疼痛内镜治疗的预测生物特征

基本信息

  • 批准号:
    10794609
  • 负责人:
  • 金额:
    $ 124.48万
  • 依托单位:
  • 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:
    2023-09-22 至 2025-08-31
  • 项目状态:
    未结题

项目摘要

Pain occurs in more than 80% of patients with chronic pancreatitis (CP) , which is most commonly caused by chronic alcohol use. Management of CP pain is challenging, and greater than 50% of patients with CP pain are placed on chronic opioids, contributing to the opioid epidemic. CP with ductal obstruction can be treated by endoscopic therapies. However, success rates vary, and despite technically successful procedures, some CP patients continue to experience pain. The lack of tools for predicting pain treatment response to endoscopic therapies presents challenges for clinical care, potentially delaying care, leading to more invasive therapies such as surgery, or unnecessarily exposing patients to opioids. In this proposal we aim to use machine learning to develop multimodal predictive biosignatures for pain response to endoscopic therapies utilizing electroencephalography (EEG), quantitative sensory testing (QST), and biopsychosocial variables. Our study is founded on the premise that while pancreatic pathology initially drives pain, over time alterations in central pain processing may become a dominant driver of pain in some patients with CP, making them resistant to therapies aimed at the periphery. Neuroimaging with EEG, sensory testing with QST, and psychosocial questionnaires assess central vs peripheral changes in pain processing. Combining these tools in a multimodal biosignature can improve sensitivity and specificity of prediction and advance s election of appropriate treatment of CP pain. In the UG3 phase of our proposal, we will measure EEG and QST and assess psychosocial factors in ~100 patients with alcohol-induced CP pain undergoing endoscopic therapy as part of standard clinical care. Using machine learning algorithms, we will extract features and develop candidate predictive biosignatures for pain treatment response to endoscopic therapy. In the UH3 phase we will validate and select the biosignature with the highest area under the curve met ric in a new cohort of patients. Our success will have direct clinical impact, improving care of this refractory chronic pain syndrome and enabling similar studies in other chronic abdominal pain syndromes.
超过80%的慢性胰腺炎(CP)患者会出现疼痛,这是最常见的原因

项目成果

期刊论文数量(0)
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Zhe Sage Chen其他文献

Mediodorsal thalamus regulates task uncertainty to enable cognitive flexibility
内侧背侧丘脑调节任务不确定性以实现认知灵活性
  • DOI:
    10.1038/s41467-025-58011-1
  • 发表时间:
    2025-03-18
  • 期刊:
  • 影响因子:
    15.700
  • 作者:
    Xiaohan Zhang;Arghya Mukherjee;Michael M. Halassa;Zhe Sage Chen
  • 通讯作者:
    Zhe Sage Chen
Prefrontal transthalamic uncertainty processing drives flexible switching
前额叶经丘脑不确定性处理驱动灵活切换
  • DOI:
    10.1038/s41586-024-08180-8
  • 发表时间:
    2024-11-13
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Norman H. Lam;Arghya Mukherjee;Ralf D. Wimmer;Matthew R. Nassar;Zhe Sage Chen;Michael M. Halassa
  • 通讯作者:
    Michael M. Halassa

Zhe Sage Chen的其他文献

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{{ truncateString('Zhe Sage Chen', 18)}}的其他基金

Data and Analytical Core
数据和分析核心
  • 批准号:
    10633812
  • 财政年份:
    2023
  • 资助金额:
    $ 124.48万
  • 项目类别:
Cortical information integration as a model for pain perception and behavior
皮质信息整合作为疼痛感知和行为的模型
  • 批准号:
    10205303
  • 财政年份:
    2021
  • 资助金额:
    $ 124.48万
  • 项目类别:
CRNS: An Integrative Study of Hippocampal-Neocortical Memory Coding during Sleep
CRNS:睡眠期间海马-新皮质记忆编码的综合研究
  • 批准号:
    10401807
  • 财政年份:
    2018
  • 资助金额:
    $ 124.48万
  • 项目类别:
CRNS: An Integrative Study of Hippocampal-Neocortical Memory Coding during Sleep
CRNS:睡眠期间海马-新皮质记忆编码的综合研究
  • 批准号:
    9920779
  • 财政年份:
    2018
  • 资助金额:
    $ 124.48万
  • 项目类别:
CRCN: Dissecting Neural Circuits for Acute Pain
CRCN:剖析急性疼痛的神经回路
  • 批准号:
    9313960
  • 财政年份:
    2016
  • 资助金额:
    $ 124.48万
  • 项目类别:
CRCN: Dissecting Neural Circuits for Acute Pain
CRCN:剖析急性疼痛的神经回路
  • 批准号:
    9242180
  • 财政年份:
    2016
  • 资助金额:
    $ 124.48万
  • 项目类别:

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