Comparative Efficacy of Non-opioid Analgesic Drugs for Chronic Cancer Pain: A Bayesian Network Meta-analysis.

Sebastiano Mercadante; Giovanbattista Vizzini; Alessio Lo Cascio

doi:10.1007/s40265-026-02356-4

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Comparative Efficacy of Non-opioid Analgesic Drugs for Chronic Cancer Pain: A Bayesian Network Meta-analysis.

Sebastiano Mercadante·Giovanbattista Vizzini·Alessio Lo Cascio

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Abstract

PURPOSE: While opioids remain the primary pharmacological intervention for cancer pain management, their clinical utility is frequently compromised by dose-limiting toxicities. This study aimed to determine the comparative efficacy, opioid-sparing potential, and clinical hierarchy of non-opioid adjuvant drug classes. The study was structured around the PICO framework to evaluate the pharmacological strategies currently utilized in multimodal clinical oncology. METHODS: A systematic search of electronic databases (PubMed, Embase, Cochrane) was conducted for randomized controlled trials (RCTs) published between 2000 and 2025. The primary outcome was global analgesic efficacy (standardized mean difference [SMD]), while secondary outcomes included the opioid-sparing effect, defined as the percentage reduction in morphine equivalent daily dose (MEDD) and the incidence of treatment-emergent adverse events (Harms). A Bayesian network meta-analysis (NMA) was performed to rank treatments using SUCRA values. The methodological quality was assessed using the Cochrane Risk of Bias (RoB 2.0) tool. RESULTS: Twenty-three RCTs (n = 1845) met the inclusion criteria. Nonsteroidal anti-inflammatory drugs (NSAIDs) (-1.10) and anticonvulsants (-1.06) demonstrated the most robust analgesic effects. The SUCRA ranking confirmed a clear hierarchy, with the combination of anticonvulsants and antidepressants showing the highest probability of efficacy. A significant opioid-sparing effect was observed for gabapentinoids and ketamine, facilitating MEDD reduction. While serious adverse events were rare, minor harms (somnolence, dizziness) were more frequent in the most effective classes. CONCLUSION: Our NMA provides a robust evidence base for a "Clinical Tier" system, ranking adjuvants by their balance of efficacy and safety. These findings support the early integration of Tier I agents (anticonvulsants and NSAIDs) to optimize pain control and reduce opioid-related toxicities in chronic cancer pain management.

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Humans Bayes Theorem Cancer Pain Chronic Pain Anti-Inflammatory Agents, Non-Steroidal Randomized Controlled Trials as Topic Analgesics, Non-Narcotic Analgesics, Opioid Anticonvulsants Analgesics Journal Article Network Meta-Analysis Comparative Study Systematic Review

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Sebastiano Mercadante, Giovanbattista Vizzini, Alessio Lo Cascio. 2026-07-09. Comparative Efficacy of Non-opioid Analgesic Drugs for Chronic Cancer Pain: A Bayesian Network Meta-analysis.. https://doi.org/10.1007/s40265-026-02356-4

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Analgesics subject Analgesics, Opioid subject Anti-Inflammatory Agents, Non-Steroidal subject Bayes Theorem subject Comparative Study subject Humans subject Journal Article subject Network Meta-Analysis subject Systematic reviews study

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