Clinical Calibration and Evaluation of the QSPainRelief Platform in Patients With Disabling Pain Using Functional Biomarkers of Nociception, Sedation and Cognition
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 180
- 试验地点
- 2
- 主要终点
- Correlation between change in magnitude of laser-evoked brain potentials (LEP) and change in the Brief Pain Inventory (BPI) pain severity score
研究概览
简要总结
QSPainRelief-patientCNS is a monocentric prospective longitudinal study conducted in patients suffering from disabling post-surgical pain for which the treating physician is about to prescribe a given drug combination for the treatment of their pain with the aim of identifying measures of drug-induced effects on CNS activity that could be used as biomarkers of real-life clinical outcome, both in terms of desired treatment effects (treatment-induced pain relief) but also in terms of undesired treatment effects (treatment-induced sedation and treatment-induced cognitive dysfunction).
详细描述
QSPainRelief-patientCNS is one of three clinical studies that will be conducted as part of the QSPainRelief project funded by the European Union's Horizon 2020 research and innovation program (grant agreement 848068; http://qspainrelief.eu).
Chronic pain is a complex disease affecting about 20% of Europeans, and up to 60% of patients with chronic pain do not experience adequate pain relief from currently available analgesic combinational therapies and/or suffer confounding adverse effects. Of the many conceivable combinations, only a few have been studied in formal clinical trials. Thus, physicians have to rely on clinical experience when treating chronic pain patients. The vision of the QSPainRelief project is that alternative novel drug combinations with improved analgesic and reduced adverse effects can be identified and assessed by mechanism-based Quantitative Systems Pharmacology (QSP) in silico modelling. The QSPainRelief consortium will setup, calibrate and validate an in silico QSPainRelief platform which integrates recently developed (1) physiologically based pharmacokinetic models to quantitate and adequately predict drug pharmacokinetics in human CNS, (2) target-binding kinetic models; (3) cellular signaling models and (4) a proprietary neural circuit model to quantitate the drug effects on the activity of relevant brain neuronal networks, that also adequately predicts clinical outcome.
Calibration of the QSPainRelief platform modelling the biological processes and neuronal circuits underlying the pain relief and adverse effects induced by drug combinations requires patient data on how different drug combinations affect the central processing of nociceptive input, the central processes underlying pain modulation, as well as the central nervous system (CNS) networks underlying drug-induced adverse effects. After calibration of the QSPainRelief platform, additional patient data is required to evaluate the ability of the platform to actually predict CNS effects of drug combinations in patients. Finally, real-world evidence is needed to relate the effects of drug combinations on CNS activity with the therapeutic and adverse effects self-reported by the patients.
The aims of the QSPainRelief-patientCNS study are thus two-fold.
The first aim is to obtain data from a first set of 60 patients to calibrate the QSPainRelief platform, and from a second set of 120 patients to evaluate the ability of the QSPainRelief platform to predict therapeutic and adverse effects of drug combinations. It will focus on pain relief and its impact on daily life activities as therapeutic effects, and on drug-induced sedation, drug-induced cognitive dysfunction (memory and attention) and pain medication misuse as adverse effects. These adverse effects have been chosen because (1) CNS biomarkers sensitive to drug-induced sedation and drug-induced cognitive dysfunction can be readily obtained using non-invasive measurements of the electroencephalogram (EEG) and (2) the chosen adverse effects can be assessed in patients after a short treatment period using validated patient-reported outcome measures (PROMs).
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 75 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Aged 18-75 years.
- •Presence of disabling post-operative pain for more than two weeks following thoracotomy, sternotomy or breast cancer surgery.
- •Current treatment of their post-operative pain with an opioid analgesic (along with possible other drugs).
- •Decision by the treating physician to introduce an additional non-opioid treatment for their post-operative pain such as (but not necessarily) an antiepileptic or an anti-depressant.
- •Capacity to understand and voluntarily sign an informed consent form.
排除标准
- •Insufficient French language skills.
- •Planned chemotherapy, hormonotherapy or radiotherapy during the time interval between Visits 1 and
- •Clinically evident psychiatric disease that is likely to interfere with the study, according to judgment by the investigator.
- •History of peripheral or central nervous system disease before the surgical intervention.
- •Dermatological condition involving the sensory testing areas.
- •Severe alcohol use disorder (as defined in DSM-5).
- •Severe sedative, hypnotic of anxiolytic-related use disorder (as defined in DSM-5).
- •Any other mild, moderate or severe substance use disorder except tobacco and caffeine (as defined in DSM-5).
- •Consumption of recreational drugs, including cannabis, in the last 4 weeks prior to the study.
- •Signs of polyneuropathy at clinical examination.
- •Signs of a neurological deficit due to a CNS lesion or dysfunction at clinical examination.
- •Any other reason to exclude the subject because it may interfere with the study, according to judgment by the investigator. The reason will be documented.
结局指标
主要结局
Correlation between change in magnitude of laser-evoked brain potentials (LEP) and change in the Brief Pain Inventory (BPI) pain severity score
时间窗: three months
To assess whether inter-individual differences in the drug-induced change in the magnitude of LEPs (in microvolts) predicts pain relief, the post-drug-combination vs. pre-drug-combination change in magnitude of LEPs between Visit 1 and Visit 2 (expressed as percentage of change between the two visits) will be correlated with the post-drug-combination minus pre-drug-combination change in the pain severity score obtained from the BPI (score between 0 and 40; Gjeilo et al., 2007) between Visit 1 and Month 3.
Correlation between change in the alpha attenuation coefficient (AAC) and change in the Stanford Sleepiness Scale (SSS)
时间窗: 10 days
To assess whether inter-individual differences in the drug-induced change in AAC (ratio between alpha-band power eyes closed vs. eyes open; Kaida et al., 2006) predicts self-reported sleepiness, the post-drug-combination minus pre-drug combination change in the AAC measured in the resting EEG between Visits 1 and 2 will be correlated with the post-drug-combination minus pre-drug-combination change in self-reported sleepiness assessed using the Stanford Sleepiness Scale (SSS; score between 1 and 7) between Visits 1 and 2.
Correlation between change in magnitude of cognitive P3b potential and change in the PROMIS Neuro-QOL score for cognitive function
时间窗: 10 days
To assess whether inter-individual differences in the drug-induced change in magnitude of the P3b component of auditory-evoked potentials (in microvolts; Komerchero \& Polich 1999) predicts self-reported cognitive dysfunction, the post-drug-combination vs. pre-drug-combination change in P3b magnitude between Visits 1 and 2 (expressed as percentage of change) will be correlated with the post-drug-combination minus pre-drug-combination change in self-reported cognitive dysfunction assessed using the short-form cognitive function measurement of the PROMIS Neuro-QOL (Quality of Life in Neurological Disorders) between Visits 1 and 2 (standardized T score for "cognitive function", having a mean of 50 and a standard deviation of 10 in a reference population).
次要结局
- Correlation between change in magnitude of the N13 spinal-cord evoked potential and change in the PQ-NEURO score for neuropathic pain(10 days)
- Correlation between change in the variation coefficient of pupillary dilation (VCPD) and change in the Brief Pain Inventory (BPI) score(10 days)
- Correlation between change in pupil constriction velocity (PCV) and change in the Brief Pain Inventory (BPI) score(10 days)
- Correlation between change in saccadic peak velocity (SPV) and change in the Stanford Sleepiness Scale (SSS)(10 days)
- Correlation between change in performance of the 2-back working memory task (2-WM) and change in the PROMIS Neuro-QOL score for cognitive function(10 days)