Predictive factors for efficacy and safety of intrathecal infusion devices for oncological pain.

Abstract

Introduction:

In an important percentage of intrathecal infusion therapy, the pain after implantation of a spinal device does not improve. Our objective is to identify factors that can predict therapeutic success and complications, developing a predictive model based on univariate and multivariate analyses.

Methods:

Retrospective observational study, including 132 patients with oncological pain who were implanted with a fixed-flow device for intrathecal infusion. Four time points were established for data collection and, in addition to demographic and anthropometric data, variables related to oncologic pain pathology, initiation of therapy, pain control and complications were collected. Based on univariate and multivariate analyses, we performed predictive models on efficacy and complications.

Results:

The mean baseline pain intensity was VAS 7.78, and when comparing the values before implantation with those at month 1, we observed an overall decrease of 4.75 points, maintained at months 3 and 6. Nocturnal pain progressively decreased in incidence from 50.0% before implantation to 21.8%, 9.1% and 4.3% at 1, 3 and 6 months. Episodic pain was present in 90.1% of the patients before implantation (7.79 episodes/day), and at 6 months the incidence remained at 53.8%. Most of the patients (66.6%) had no complications related to therapy. We constructed a highly significant multivariate model for the efficacy of the therapy with a predictive capacity of 30.2% and composed of factors: absence of nocturnal pain before implantation and clinical improvement on day 2 after implant. Regarding the prediction of complications, it was not possible to achieve a significantly multivariate effective model.

Conclusion:

We identify two factors that predict therapeutic success in a multivariate model: the absence of nocturnal pain before implantation and the improvement of pain on the second day after implantation.

• Authors: Bartolomé Fernández-Torres, Isabel M Fontán-Atalaya, Estefanía Peralta-Espinosa, Diego Díaz-Rodríguez
• Journal: British journal of pain (Br J Pain) Vol. 17 Issue 6 Pg. 569-578 (Dec 2023) ISSN: 2049-4637 [Print] England
• PMID: 37974633 (Publication Type: Journal Article)
• Copyright: © The Author(s) 2023.