Evidence map›Paper›PMID 28328579›Full record

ArticlePain2017

Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome: a MAPP network study.

Jason J Kutch, Jennifer S Labus, Richard E Harris, Katherine T Martucci, Melissa A Farmer, Sonja Fenske, Connor Fling, Eric Ichesco, Scott Peltier, Bogdan Petre and 10 more

Registry-linked trialAbstract read
In one paragraph

Article in Pain, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04994249 (Diagnostic and Prognostic Biomarkers for High-impact Chronic Pain), which is not on this map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
4.2field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04994249 active not recruitingnot on this mapstarted 2022, after this paper: background citation

Diagnostic and Prognostic Biomarkers for High-impact Chronic Pain: Development and Validation

TypeobservationalSponsorStanford UniversityRan2022 to 2027Enrolled250ConditionsChronic Musculoskeletal Pain, Pain, Pain, Chronic, Joint Pain
3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 63 citations in OpenAlex.

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  16. Pathology of pain and its implications for therapeutic interventions.Signal transduction and targeted therapy · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 7 institutions in 1 country.

Jason J KutchaDivision of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, USA bG Oppenheimer Center for Neurobiology of Stress and Resilience, Pain and Interoception Network (PAIN), David Geffen School of Medicine at UCLA, Los Angeles, CA, USA cDepartment of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Ann Arbor, MI, USA dDepartment of Anesthesiology, Perioperative and Pain Medicine, Division of Pain Medicine, Stanford University Medical Center, Stanford, CA, USA eDepartment of Physiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA fNeuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA gFunctional MRI Laboratory, University of Michigan, Ann Arbor, MI, USA hDepartment of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA iNational Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD, USA.
Jennifer S Labus
Richard E Harris
Katherine T Martucci
Melissa A Farmer
Sonja Fenske
Connor Fling
Eric Ichesco
Scott Peltier
Bogdan Petre
Wensheng Guo
Xiaoling Hou
Alisa J Stephens
Chris Mullins
Daniel J Clauw
Sean C Mackey
A Vania Apkarian
J Richard Landis
Emeran A Mayer
MAPP Research Network
Pancreatic Cancer Action Network · USUniversity of Michigan–Ann Arbor · USUniversity of Pennsylvania · USNorthwestern University · USStanford Medicine · USNational Institute of Diabetes and Digestive and Kidney Diseases · USUniversity of Southern California · US

Funding

Tumor Environment and Metastasis (TEAM) Research ProgramP30CA060553 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Daniela E Matei · 1993 to 2026
$153.9M
Pilot and Feasibility ProgramP30DK041301 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ROZENGURT, JUAN ENRIQUE · 1990 to 2019
$18.0M
MAPP Research NetworkU01DK082316 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI LANDIS, J RICHARD · 2008 to 2018
$17.2M
Role of CNS in Modulation of Pelvic Pain SyndromeU01DK082342 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI KLUMPP, DAVID J · 2008 to 2021
$10.5M
Urology Chronic Pelvic Pain Longitudinal Symptom Patterns StudyU01DK082344 · NIDDK · UNIVERSITY OF IOWA · PI KREDER, KARL J · 2008 to 2021
$9.8M
University of Michigan MAPP Research Network Discovery SiteU01DK082345 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CLAUW, DANIEL J, CLEMENS, J. QUENTIN · 2008 to 2021
$9.7M
Neurobiological endophenotypes & gene-environment interactions in IC/PBS & in aU01DK082370 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KUTCH, JASON J., MAYER, EMERAN A · 2008 to 2021
$9.2M
WSU Urologic Chronic Pelvic Pain Syndromes Discovery CenterU01DK082325 · NIDDK · WASHINGTON STATE UNIVERSITY · PI BOGIC, MARIJA · 2008 to 2021
$9.0M
Washington University MAPP Network Discovery SiteU01DK082315 · NIDDK · WASHINGTON UNIVERSITY · PI LAI, HING HUNG HENRY · 2008 to 2021
$9.0M
MAPP Research Network Tissue Analysis and Technology CoreU01DK082333 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI LUCIA, M. SCOTT · 2008 to 2018
$6.1M
Limited Competition for Continuation of the MAPP-RN DCCU24DK082316 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI LANDIS, J RICHARD · 2019 to 2021
$4.9M
MAPP Research Network Tissue Analysis and Technology CoreU24DK082333 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI LUCIA, M. SCOTT · 2019 to 2021
$390k
NCI NIH HHS P30 CA060553NIDDK NIH HHS P30 DK041301NIDDK NIH HHS U01 DK082315NIDDK NIH HHS U01 DK082316NIDDK NIH HHS U01 DK082325NIDDK NIH HHS U01 DK082333NIDDK NIH HHS U01 DK082342NIDDK NIH HHS U01 DK082344NIDDK NIH HHS U01 DK082345NIDDK NIH HHS U01 DK082370NIDDK NIH HHS U24 DK082316NIDDK NIH HHS U24 DK082333
6 · The paper itself

Abstract

Chronic pain symptoms often change over time, even in individuals who have had symptoms for years. Studying biological factors that predict trends in symptom change in chronic pain may uncover novel pathophysiological mechanisms and potential therapeutic targets. In this study, we investigated whether brain functional connectivity measures obtained from resting-state functional magnetic resonance imaging at baseline can predict longitudinal symptom change (3, 6, and 12 months after scan) in urologic chronic pelvic pain syndrome. We studied 52 individuals with urologic chronic pelvic pain syndrome (34 women, 18 men) who had baseline neuroimaging followed by symptom tracking every 2 weeks for 1 year as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. We found that brain functional connectivity can make a significant prediction of short-term (3 month) pain reduction with 73.1% accuracy (69.2% sensitivity and 75.0% precision). In addition, we found that the brain regions with greatest contribution to the classification were preferentially aligned with the left frontoparietal network. Resting-state functional magnetic resonance imaging measures seemed to be less informative about 6- or 12-month symptom change. Our study provides the first evidence that future trends in symptom change in patients in a state of chronic pain may be linked to functional connectivity within specific brain networks.

Indexed as

ConnectomeDisease ProgressionAdultBrainChronic PainFemaleHumansLongitudinal StudiesMagnetic Resonance ImagingMaleNerve NetPelvic PainPostal ServiceReproducibility of ResultsRestSensitivity and Specificity

Identifiers

PMID28328579
PMCPMC5435510
OpenAlexW2598263374

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.