Implementing measurement-based care in the analgesic management of cancer pain patients receiving intrathecal drug infusion
摘要
To evaluate the efficacy and safety of a structured measurement-based care (MBC) strategy with a “Monitor-Assess-Adjust” closed-loop protocol for managing moderate-to-severe cancer pain in patients receiving intrathecal morphine patient-controlled analgesia (IT-PCA). A retrospective observational study was conducted at two pain centers, enrolling 15 patients with cancer pain (Visual Analog Scale [VAS] ≥ 7). All patients initially received intravenous patient-controlled analgesia (IV-PCA) for dose titration, followed by IT-PCA implantation. A structured MBC protocol was implemented, including three core components: (1) Multidimensional assessment: regular evaluations using the VAS, Brief Pain Inventory (BPI), and leeds assessment of neuropathic symptoms and signs (LANSS) scale; (2) Dynamic individualized titration: a standardized dosing algorithm based on pain reassessment every 15 min during IT-PCA initiation, with adjustments as follows: 50–100% dose increase for unchanged/elevated VAS, 50% increase for VAS 4–6, and dose maintenance for VAS 1–3 (target: VAS < 4); (3) Systematic follow-up: assessments at baseline, post-IV-PCA, post-IT-PCA, discharge, and 1, 3, 6 months after discharge. After IT-PCA under the MBC protocol, the mean VAS score decreased significantly from 8.28 ± 0.76 at baseline to 2.14 ± 0.90, representing a 76.4% pain reduction (P < 0.05), and this effect was sustained throughout follow-up. Pain relief and quality of life (BPI scores) were significantly improved compared with baseline and post-IV-PCA stages (P < 0.01). Notably, the incidence of opioid-related adverse reactions was extremely low: only 1 patient (6.7%) experienced mild, manageable constipation, with no cases of nausea, vomiting, or respiratory depression. Implementing IT-PCA within an MBC framework enables effective, individualized analgesia, sustains long-term pain relief, and optimizes the therapeutic benefit-risk profile by minimizing adverse effects, thus improving the quality of life in cancer pain patients. This study provides evidence for a data-driven, precision medicine approach to intrathecal analgesia management.