Evidence map›Paper›PMID 39964488›Full record

ReviewEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2025

Development and application of predictive clinical biomarkers for low back pain care: recommendations from the ISSLS phenotype/precision spine focus group.

Paul W Hodges, Gwendolyn Sowa, Conor O'Neill, Nam Vo, Nadine Foster, Dino Samartzis, Jeffrey Lotz

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07248943 (Contralateral Neural Tissue Mobilization for Cervical Radiculopathy), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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.

NCT07248943 nanot yet recruitingnot on this map

Contralateral Neural Tissue Mobilization for Cervical Radiculopathy: An Exploratory Study

TypeinterventionalSponsorEvidence In MotionRan2025 to 2026Enrolled40ConditionsCervical Radiculopathy, Pain, Neuropathic Pain, Radicular PainArmsContralateral Neural Tissue Mobilization (NTM)
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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

7 authors.

Paul W HodgesUniversity of Queensland, Brisbane, Australia. p.hodges@uq.edu.au.
Gwendolyn SowaUniversity of Pittsburgh, Pittsburgh, USA.
Conor O'NeillUniversity of California, San Francisco, San Francisco, USA.
Nam VoUniversity of Pittsburgh, Pittsburgh, USA.
Nadine FosterUniversity of Queensland, Brisbane, Australia.
Dino SamartzisRush University Medical Center, Chicago, USA.
Jeffrey LotzUniversity of California, San Francisco, San Francisco, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predictive biomarkers (or moderators of treatment) are features, or more likely feature clusters, that discriminate individuals who are more likely to experience a favourable or unfavourable effect from a specific treatment. Utilization of validated predictive biomarkers for chronic low back pain (CLBP) treatments is a plausible strategy to guide patients more rapidly to effective treatments thereby reducing wastage of finite healthcare funds on treatments that are ineffective (or potentially harmful). Yet, few predictive biomarkers have been successfully validated in clinical studies. This paper summarizes work by the Phenotype/Precision Spine Focus Group of the International Society for the Study of the Lumbar Spine that addressed: (1) relevant definitions for terminology; (2) advantages and disadvantages of different research approaches for the specification of predictive biomarkers; (3) methods for assessment of clinical validity; (4) approaches for their implementation; (5) barriers to predictive biomarker identification; and (6) a prioritised list of recommendations for the development and refinement of predictive biomarkers for CLBP. Key recommendations include the harmonisation of data collection, data sharing, integration of theoretical models, development of new treatments, and health economic analyses to inform cost-benefit of assessments and the application of matched treatments. The complexity of CLBP demands large datasets to derive meaningful progress. This will require coordinated and substantive collaboration involving multiple disciplines and across the research spectrum from the basic sciences to clinical applications.

Indexed as

BiomarkersLow Back PainFocus GroupsHumansPhenotypeBiomarkersBack painEffect modifierPesponse predictive biomarkerPrecision medicineRecommendationsTreatment moderatorsValidation

Identifiers

What OpenQuestion holds

Textmetadata
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.