Development and Internal Validation of an RPA-Based Model Predictive of Pain Flare Incidence After Spine SBRT

R. O. Kowalchuk, T. C. Mullikin, W. S. Harmsen, P. S. Rose, B. L. Siontis, D. K. Kim, B. A. Costello, J. M. Morris, J. T. Marion, B. Johnson-Tesch, R. W. Gao, S. Shiraishi, J. Lucido, K. Olivier, D. Owen, B. J. Stish, N. N. Laack, S. S. Park, P. D. Brown, K. W. Merrell

Research output: Contribution to journalArticlepeer-review

Abstract

PURPOSE/OBJECTIVE(S): Radiotherapy is a standard palliative treatment for spine metastasis, but pain flares (PF) are a common acute toxicity. Prophylactic corticosteroids can reduce the rate of PF in patients receiving traditional palliative regimens, but less is known about prophylaxis for stereotactic body radiotherapy (SBRT). We aim to identify a subset of patients treated with spine SBRT with the highest rate of PF to optimize the use of prophylactic steroids. MATERIALS/METHODS: From December 2007-August 2019, 469 patients received 680 spine SBRT treatments. After exclusion of benign histology, particle therapy, and patients with missing data, the final cohort included 424 patients with 610 treatments. We defined PF as acute worsening of pain at the treatment site requiring initiation of or higher-dose corticosteroids, opiates, and/or hospitalization. First, data was split into 70% training and 30% validation sets with comparable patient characteristics using a random number generator. Feature importance testing was conducted, and a correlation heatmap helped exclude correlated variables. Feature extraction involved selecting the variables used in the highest-fidelity recursive partitioning analysis (RPA) models. Each RPA model was trained, validated, and tested using only the training dataset. Selected variables were verified using the Fisher exact test and univariate t-test. RESULTS: We identified 125 total PF (20%), treated with steroids (14%), opioids (40%), both (39%), or hospitalization (6%). Six variables were identified by RPA. Of these, 5 met significance on Fisher exact test with P < 0.02: renal primary (OR 2.23), soft tissue involvement (OR 1.96), Bilsky > 0 (OR 2.17), SINS > 6 (OR 2.98), and gross tumor volume > 8 cc (OR 2.80). One point was assigned for each variable. The low-risk (LR) group (score = 0, n = 159) had PF rates of 7.0% and 13.6% in the training and validation sets, respectively; the intermediate-risk (IR) group (score = 1, n = 150) had rates of 14.0% and 16.3%; and the high-risk (HR) group (score > 1, n = 301) had rates of 28.8% and 31.3%. A logistic model confirmed the increased pain flare rate in the HR group compared to LR and IR treatments combined (OR = 3.50, 95% CI: 2.06-5.92) or considered separately (OR = 5.41, 2.48-11.78). The concordance index was 0.66 (0.60-0.73) and 0.62 (0.52-0.71) in the training and internal validation sets. Notably, patients with PF after prior spine SBRT had a 61% rate of PF with subsequent spine SBRT, compared to only 5% for patients without PF after prior spine SBRT. CONCLUSION: Our internally-validated model identifies a high-risk group of patients more likely to develop PF after spine SBRT, for whom prophylactic steroids may confer the greatest benefit. Evaluation in a clinical trial is warranted.

Original languageEnglish (US)
Pages (from-to)S60-S61
JournalInternational journal of radiation oncology, biology, physics
Volume111
Issue number3
DOIs
StatePublished - Nov 1 2021

ASJC Scopus subject areas

  • Radiation
  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

Fingerprint

Dive into the research topics of 'Development and Internal Validation of an RPA-Based Model Predictive of Pain Flare Incidence After Spine SBRT'. Together they form a unique fingerprint.

Cite this