Multifactorial Machine Learning Algorithm Integration of Pain Mechanisms Can Predict the Efficacy of 3-Week NSAID Plus Paracetamol in Patients With Painful Knee Osteoarthritis

Aug 5, 2026

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The study applies multifactorial machine learning to forecast analgesic response to a 3-week NSAID plus paracetamol regimen in patients with painful knee osteoarthritis. Pretreatment assessments cover pain sensitivity, anxiety/depression, pain catastrophizing, health status, and biomarker profiling for inflammation and microRNA. Data integration with DIABLO combines four domains to explain treatment effects. The model highlights 30 significant variables and demonstrates strong cross-validated predictive performance, supporting personalized pain management.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Abstract

Background

Methods

Results

Conclusions

Significance Statement

Aalborg Universitet Multifactorial Machine Learning Algorithm Integration of Pain Mechanisms Can Predict the Efficacy of 3-Week NSAID Plus Paracetamol in Patients With Painful Knee Osteoarthritis Giordano, Rocco; Arendt-Nielsen, Lars; Hertel, Emma; Olesen, Anne Estrup; Petersen, Kristian Kjær-Staal Published in: European Journal of Pain DOI (link to publication from Publisher): 10.1002/ejp.70140 Creative Commons License CC BY 4.0 Publication date: 2025 Document Version Publisher's PDF, also known as Version of record Link to publication from Aalborg University Citation for published version (APA): Giordano, R. , Arendt-Nielsen, L. , Hertel, E. , Olesen, A. E. , & Petersen, K. K.-S. (2025) . Multifactorial Machine Learning Algorithm Integration of Pain Mechanisms Can Predict the Efficacy of 3-Week NSAID Plus Paracetamol in Patients With Painful Knee Osteoarthritis. European Journal of Pain, 29(10), Article e70140 . [https://doi.org/10.1002/ejp.70140](https://doi.org/10.1002/ejp.70140) General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. -Users may download and print one copy of any publication from the public portal for the purpose of private study or research. -You may not further distribute the material or use it for any profit-making activity or commercial gain -You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact [us at vbn@aub.aau.dk](us at vbn@aub.aau.dk) providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from [vbn.aau.dk](vbn.aau.dk) on: August 04, 2026 European Journal of Pain ORIGINAL ARTICLE OPEN ACCESS Multifactorial Machine Learning Algorithm Integration of Pain Mechanisms Can Predict the Efficacy of 3-Week NSAID Plus Paracetamol in Patients With Painful Knee Osteoarthritis Rocco Giordano1 | Lars Arendt-Nielsen1,2,3,4 | Emma Hertel1,2 | Anne Estrup Olesen5,6 | Kristian Kjær-Staal Petersen1,2 1Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark | 2Center for Mathematical Modeling of Knee Osteoarthritis (MathKOA), Department of Material and Production, Faculty of Engineering and Science, Aalborg University, Aalborg, Denmark | 3Department of Gastroenterology & Hepatology, MechSense, Aalborg University Hospital, Aalborg, Denmark | 4Steno Diabetes Center North Denmark, Aalborg University Hospital, Aalborg, Denmark | 5Department of Clinical Medicine, Aalborg University, Aalborg, Denmark | 6Department of Clinical Pharmacology, Aalborg University Hospital, Aalborg, Denmark Correspondence: Kristian Kjær-Staal Petersen ([kkp@hst.aau.dk](kkp@hst.aau.dk)) Received: 17 April 2025 | Revised: 3 September 2025 | Accepted: 19 September 2025 Funding: The Center for Neuroplasticity and Pain (CNAP) is supported by the Danish National Research Foundation (DNRF121) . The Center for Mathematical Modelling of Knee Osteoarthritis (MathKOA) is funded by the Novo Nordisk Foundation (NNF21OC0065373) . The Danish Rheumatism Association is acknowledged for funding (A7645) . ABSTRACT Background: Studies demonstrate that pain sensitization, epigenetic mechanisms, inflammation, and psychological factors might be predictive of treatment outcomes. Anti-inflammatory therapy is recommended, but efficacy varies among patients. This study aimed to utilise machine learning to predict the analgesic responses of 3-week NSAID plus paracetamol therapy using pretreatment assessments of pain sensitivity, inflammation, microRNA, and psychological factors. Methods: Patients (n = 101) underwent 3-week combined NSAID pl

FAQs

What treatment did the study evaluate in knee osteoarthritis patients?

Patients received a 3-week combined therapy of NSAIDs plus paracetamol. Analgesic response was assessed by a knee osteoarthritis pain outcome score before and after treatment.

Which pretreatment factors were used for prediction?

Pretreatment pain sensitivity measures, psychological scales, health status, inflammatory biomarkers, and microRNA profiles were collected. These variables were integrated across domains for model building.

How was the machine learning model validated and what did it identify?

The DIABLO model was cross-validated, yielding strong predictive metrics, including an area under the precision-recall curve of 85%. It identified 30 significant variables across four data domains that contributed to analgesic effect prediction.

Aug 5, 2026

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