Evidence map›Paper›PMID 42345067›Full record

ArticleGlobal spine journal2026

Optimized OF-Score- Therapy Prediction in Successfully Treated Patients With Osteoporotic Spine Fractures Using Minimal Clinically Important Difference.

Philipp Schenk, Bernhard Wilhelm Ullrich, Felix Kohler, Marx Ribeiro, Ulrich J Spiegl, Michael A Scherer, Gregor Schmeiser, Michael Müller, Martin Bäumlein, Sebastian Katscher and 6 more

Abstract read
In one paragraph

Article in Global spine journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Philipp SchenkInnovationhub for Musculoskeletal Surgery Halle, BG Klinikum Bergmannstrost Halle gGmbH, Halle (Saale), Germany.ORCID 0000-0002-3610-2469
Bernhard Wilhelm UllrichDepartment of Trauma and Reconstructive Surgery, BG Klinikum Bergmannstrost Halle gGmbH, Halle (Saale), Germany.ORCID 0000-0001-8748-1190
Felix KohlerDepartment of Trauma, Hand and Reconstructive Surgery, University Hospital Jena, Jena, Germany.
Marx RibeiroInnovationhub for Musculoskeletal Surgery Halle, BG Klinikum Bergmannstrost Halle gGmbH, Halle (Saale), Germany.ORCID 0000-0003-3341-3605
Ulrich J SpieglClinic for Trauma, Orthopedic, Reconstructive and Hand Surgery, Munich Clinic Harlaching, Munich, Germany.ORCID 0000-0002-5179-4192
Michael A SchererMedical Faculty, Technical University of Munich, Munich, Germany.
Gregor SchmeiserDepartment of Spine Surgery, Schoen Clinic Hamburg Eilbek, Hamburg, Germany.ORCID 0000-0002-2432-8276
Michael MüllerDepartment of Orthopedics and Trauma Surgery, University Medical Center Schleswig-Holstein, Campus Kiel, Germany.
Martin BäumleinDepartment of Orthopaedics and Traumatology, University Hospital Marburg, Marburg, Germany.ORCID 0000-0003-3010-5156
Sebastian KatscherInterdisciplinary Center for Spine and Neurotrauma, Sana Klinikum Borna, Borna, Germany.
Max J ScheyererDepartment for Orthopedics and Traumatology, University Hospital Düsseldorf, Düsseldorf, Germany.
Georg OsterhoffDepartment of Traumatology and Orthopedics, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Kai SprengelPraxis medOT, Hirslanden Clinic St. Anna, Lucerne, Switzerland.ORCID 0000-0001-5921-8272
Falko SchwarzDepartment of Neurosurgery, Friedrich Schiller University, Jena University Hospital, Jena, Germany.ORCID 0000-0003-0821-193X
Klaus John SchnakeInterdisciplinary Center for Spine and Scoliosis Surgery, Malteser Waldkrankenhaus St. Marien, Erlangen, Germany.
Working Group Osteoporotic Fractures Spine Section of the German Society of Orthopedics and Trauma

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Study DesignMulticenter study with prospective collected data.ObjectivesThis study investigates the relationship between individual score components and treatment success, defined by achieving Minimal Clinically Important Difference (MCID) thresholds in functional outcomes, using multicenter prospectively collected data. This work aimed to optimize the OF-Score while maintaining its original structure. By using outcome-oriented data, we refined this established decision-support tool to improve its predictive accuracy for successful clinical outcomes.MethodsData from 518 patients from the EOFTT study with osteoporotic vertebral fractures were analyzed. Only patients with clinically successful outcomes, defined by improvement beyond MCID thresholds in functional scores after conservative or surgical treatment, were selected from this cohort. Optimization was performed using a data-driven reweighting approach combined with structured clinical expert evaluation, adjusting variable weights within predefined limits to improve alignment with successful therapies.ResultsThe subset data of 374 successfully treated patients were analyzed. Before optimization, the OF-Score showed an accuracy of 73%, with pain and mobilization being the most important parameters. After optimization, the OF-Score showed an accuracy of 80.7% (sensitivity 85.2%, specificity 71.2%). The number of nonapplicable (indifferent) therapy recommendations dropped from 144 (37%) to 72 (19%). A threshold of 5 points provided optimal discrimination between conservative treatment (≤5) and surgical treatment (>5).DiscussionThe optimized OF-Score, targeted weight adjustments, improves the alignment between clinical recommendations and treatment success. This refinement enhances the score's predictive accuracy for treatment responders while maintaining the simple, practical structure.

Indexed as

data driven optimizationminimal clinically important difference (MCID)OF-ScoreOsteoporotic vertebral fracturesspinal fracture outcomestreatment decision-making

Identifiers

PMID42345067
PMCPMC13303261

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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.