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

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