SPOT: An Early Detection Tool for Predicting Pain Trajectories Following Intra-Articular Injections

Why clinicians should know about it

• Picked for Orthopedics and Sports Medicine (top studies of the week, 18 October 2026): Prediction tool for pain after intra‑articular injections, orthopaedic relevance

Abstract

The purpose of this study was to identify 12-month postinjection knee osteoarthritis (KOA) pain trajectories and develop an early prediction model using patient-reported pain scores. Data were derived from a multi-site, single-blind randomized controlled trial of intra-articular injections for KOA. The primary analysis focused on participants assigned to autologous bone marrow aspirate concentrate, umbilical cord tissue-derived mesenchymal stromal cells, or stromal vascular fraction. After data-quality screening, the primary trajectory cohort included 317 participants and the prediction cohort included 295 participants with Screening and Month-3 KOOS-12 Pain scores. Latent class mixed-effects modeling identified a two-class solution selected for clinical interpretability: 66.6% of patients followed an Improved Pain trajectory and 33.4% followed a Persistent Pain trajectory. Although a three-class model had slightly lower BIC, the additional class included only 2.5% of participants and was not retained for the clinical prediction tool. A logistic regression model using KOOS-12 Pain at Screening and 3-month change predicted trajectory membership with AUC = 0.785 in training and AUC = 0.792 in the held-out test set. A training-selected threshold of 0.656 yielded held-out test sensitivity = 0.790, specificity = 0.692, PPV = 0.860, NPV = 0.581, and accuracy = 0.761. The resultant model was implemented as the Symptom Prediction for Outcomes of Treatment (SPOT) web calculator. Clinical Significance: The SPOT web calculator only requires KOOS-12 Pain data from Screening and Month 3 to classify patients as likely to follow an Improved Pain vs. Persistent Pain trajectory after orthobiologic KOA treatment. Trial Registration: ClinicalTrials.gov identifier: NCT03818737.

Abstract as published, via PubMed.