Biometric and Biological Data for Diagnosis and Therapy of Pain Patients

NCT04835779 | Unknown

• 1 other identifier: 18-018
• Study Type: observational
• Target: 68
• Locations: 1 country
• Sites: 1

Brief Summary

In order to meet the challenge of an unambiguous diagnosis and effective therapy of SFN or the prognosis of susceptibility to the development of SFN, this project aims to create a data basis on which software will be developed during the project. This software should later be able to combine (integrate) quantifiable biometric data collected from the patient (both objectively measured and patient reported parameters) with the results of biological analyses of the patient's own nerve cells from stem cells. We expect that the patient-specific combination and correlation of biometric and biological data can lead to a significant improvement in the diagnosis, prognosis and therapy of chronic pain. The initial data collection required for the development of such a software (Bio2Integrate) will be carried out in three different project parts: Bio2Watch, Bio2Patient and Bio2Cell

Conditions

Small Fiber Neuropathy

Keywords

Pain; SFN

Outcome Measures

Primary Outcomes (16)

• PainWatch Data

  pulse rate (/min)

  12 months

• PainWatch Data

  number of steps

  12 months

• PainWatch Data

  pain perception via App (Questionnaire, pain scale 1-10)

  12 months

• Weather Data tracked according to GPS Location

  Temperature (°C)

  12 months

• Weather Data tracked according to GPS Location

  Air pressure (Pa)

  12 months

• Weather Data tracked according to GPS Location

  Humidity (%)

  12 months

• Test result QST

  Measurement exclusively above the back of the foot that is clinically more severely affected by the SFN, in a balanced row alternately above the right or left foot; one back of the foot as test site per subject

  12 months

• Test result PREP (over the same back of the foot as in QST measurement)

  P1 Latency (ms)

  12 months

• Test result PREP (over the same back of the foot as in QST measurement)

  Peak-to-Peak (microV)

  12 months

• Test result PREP (over the same back of the foot as in QST measurement)

  Current intensity (mA)

  12 months

• Result SF 36 Questionnaire

  Result SF 36 Questionnaire (different scales per question)

  12months

• Results of the Multi-Electrode Array investigations

  Spontaneous activity

  12 months

• Results of the Multi-Electrode Array investigations

  Synchronicity

  12 months

• Results of the Multi-Electrode Array investigations

  Field potential properties

  12 months

• Results of the Multi-Electrode Array investigations

  Activity inducing stimuli

  12 months

• Efficiency of reprogramming and differentiation of iPS cells

  Success of differentiation will be measured by flow cytometry at around d10 of differentiation. The percentage of p75 (CD271)-expressing cells will be meassured. The differentiation is defined as successful if more than 30% of cells express p75. Only those differentiations will be used for MEA-Recordings.

  12 months

Study Arms (4)

SFN Patients

Patients with diagnosed Small Fibre Neuropathy

Patients undergoing chemotherapy

Patients undergoing chemotherapy and are expected to develop SFN as a result

Healthy Volunteer

Healthy test person

Healthy Volunteer PREPs

For the pain-evoked potentials (PREPs), 20 additional healthy control subjects are to be included. Four subjects (2 male, 2 female) from each of the age decades 20-29, 30-39, 40-49, 50-59, 60-69.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

SFN Patients (Group A): Patients diagnosed with Small Fibre Neuropathia Healthy Volunteers (Group B): Healthy grown-up Volunteers Patients undergoing chemotherapy (Group C): Patients with imminent initiation of neurotoxic chemotherapy in cancer with solid tumors (preferably of the gastrointestinal tract) with the side-effect of SFN development. There are no plans for follow-up recruitment in case no neuropathy develops after chemo. Healthy Volunteers PREPs (Group D): Healthy grown-up Volunteers. Four subjects (2 male, 2 female) from each of the age decades 20-29, 30-39, 40-49, 50-59, 60-69.

You may qualify if:

• Group A: Criteria 1-5 Group B: Criteria 2-5 Group C: Criteria 2-6 Group D: Criteria 2-4
• Small fiber neuropathy (after clinical examination or QST or skin biopsy findings)
• Legal age
• Written declaration of consent
• Persons who are legally competent and mentally capable of following the instructions of the staff
• Sufficient affinity for independent handling of the technology used (PainWatch incl. the corresponding apps) for daily digital pain recording
• Imminent initiation of neurotoxic chemotherapy in cancer with solid tumors (preferably of the gastrointestinal tract) There are no plans for follow-up recruitment in case no neuropathy develops after chemo.

You may not qualify if:

• For all Groups:
• Persons who are accommodated in an institution by order of the authorities or courts
• Persons who are in a dependent or employment relationship with the auditor

Sponsors & Collaborators

• RWTH Aachen University: lead
• Grünenthal GmbH: collaborator

Study Sites (1)

Uniklinik RWTH Aachen, Klinik für Palliativmedizin

Aachen, North Rhine-Westphalia, 52074, Germany

RECRUITING

Related Publications (11)

• Lacomis D. Small-fiber neuropathy. Muscle Nerve. 2002 Aug;26(2):173-88. doi: 10.1002/mus.10181.

  PMID: 12210380 BACKGROUND

• Devigili G, Tugnoli V, Penza P, Camozzi F, Lombardi R, Melli G, Broglio L, Granieri E, Lauria G. The diagnostic criteria for small fibre neuropathy: from symptoms to neuropathology. Brain. 2008 Jul;131(Pt 7):1912-25. doi: 10.1093/brain/awn093. Epub 2008 Jun 4.

  PMID: 18524793 BACKGROUND

• Rolke R, Rolke S, Hiddemann S, Mucke M, Cuhls H, Radbruch L, Elsner F, Peuckmann-Post V. [Update palliative pain therapy]. Internist (Berl). 2016 Oct;57(10):959-970. doi: 10.1007/s00108-016-0126-7. German.

  PMID: 27631529 BACKGROUND

• Dworkin RH, O'Connor AB, Kent J, Mackey SC, Raja SN, Stacey BR, Levy RM, Backonja M, Baron R, Harke H, Loeser JD, Treede RD, Turk DC, Wells CD. Interventional management of neuropathic pain: NeuPSIG recommendations. Pain. 2013 Nov;154(11):2249-2261. doi: 10.1016/j.pain.2013.06.004. Epub 2013 Jun 6.

  PMID: 23748119 BACKGROUND

• Coluzzi F, Rolke R, Mercadante S. Pain Management in Patients with Multiple Myeloma: An Update. Cancers (Basel). 2019 Dec 17;11(12):2037. doi: 10.3390/cancers11122037.

  PMID: 31861097 BACKGROUND

• Meents JE, Bressan E, Sontag S, Foerster A, Hautvast P, Rosseler C, Hampl M, Schuler H, Goetzke R, Le TKC, Kleggetveit IP, Le Cann K, Kerth C, Rush AM, Rogers M, Kohl Z, Schmelz M, Wagner W, Jorum E, Namer B, Winner B, Zenke M, Lampert A. The role of Nav1.7 in human nociceptors: insights from human induced pluripotent stem cell-derived sensory neurons of erythromelalgia patients. Pain. 2019 Jun;160(6):1327-1341. doi: 10.1097/j.pain.0000000000001511.

  PMID: 30720580 BACKGROUND

• Mucke M, Cuhls H, Radbruch L, Baron R, Maier C, Tolle T, Treede RD, Rolke R. [Quantitative sensory testing]. Schmerz. 2014 Dec;28(6):635-46; quiz 647-8. doi: 10.1007/s00482-014-1485-4. German.

  PMID: 25403802 BACKGROUND

• Lefaucheur JP, Ahdab R, Ayache SS, Lefaucheur-Menard I, Rouie D, Tebbal D, Neves DO, Ciampi de Andrade D. Pain-related evoked potentials: a comparative study between electrical stimulation using a concentric planar electrode and laser stimulation using a CO2 laser. Neurophysiol Clin. 2012 Jun;42(4):199-206. doi: 10.1016/j.neucli.2011.12.003. Epub 2012 Jan 20.

  PMID: 22632868 BACKGROUND

• Hansen N, Obermann M, Uceyler N, Zeller D, Mueller D, Yoon MS, Reiners K, Sommer C, Katsarava Z. [Clinical application of pain-related evoked potentials]. Schmerz. 2012 Feb;26(1):8-15. doi: 10.1007/s00482-011-1117-1. German.

  PMID: 22134376 BACKGROUND

• Jenkinson C, Coulter A, Wright L. Short form 36 (SF36) health survey questionnaire: normative data for adults of working age. BMJ. 1993 May 29;306(6890):1437-40. doi: 10.1136/bmj.306.6890.1437.

  PMID: 8518639 BACKGROUND

• Lee J, Mawla I, Kim J, Loggia ML, Ortiz A, Jung C, Chan ST, Gerber J, Schmithorst VJ, Edwards RR, Wasan AD, Berna C, Kong J, Kaptchuk TJ, Gollub RL, Rosen BR, Napadow V. Machine learning-based prediction of clinical pain using multimodal neuroimaging and autonomic metrics. Pain. 2019 Mar;160(3):550-560. doi: 10.1097/j.pain.0000000000001417.

  PMID: 30540621 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

Whole Blood

MeSH Terms

Conditions

Small Fiber Neuropathy; Pain

Condition Hierarchy (Ancestors)

Peripheral Nervous System Diseases; Neuromuscular Diseases; Nervous System Diseases; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Officials

• Roman Rolke, Prof. Dr.

  Universitätsklinikum Aachen, AöR

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Roman Rolke, Prof. Dr.

CONTACT

+49 241 8080880; rrolke@ukaachen.de

Lampert Angelika, Prof. Dr.

CONTACT

+49 241 80 88811; alampert@ukaachen.de

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Direktor Klinik für Palliativmedizin

Study Record Dates

• First Submitted: February 11, 2021
• First Posted: April 8, 2021
• Study Start: October 10, 2020
• Primary Completion: October 1, 2023
• Study Completion: October 1, 2023
• Last Updated: January 9, 2023

Record last verified: 2023-01

Data Sharing

• IPD Sharing: Will not share

Locations

DE (1)