Impact of Opioid Use on Duration of Therapy and Overall Survival for Patients with Advanced Non-Small Cell Lung Cancer Treated with Immune Checkpoint Inhibitors.
Philip YoungOmar ElghawyJoseph MockEmmett WynterRyan D GentzlerLinda W MartinWendy M NovicoffRichard HallPublished in: Current oncology (Toronto, Ont.) (2024)
Immune checkpoint inhibitors (ICI) have significantly improved outcomes in advanced non-small cell lung cancer (NSCLC). We evaluated the effect of opioid use on outcomes in patients receiving ICI either alone or with chemotherapy. We conducted a retrospective review of 209 patients with advanced NSCLC who received an ICI at the University of Virginia between 1 February 2015 and 1 January 2020. We performed univariate and multivariate analyses to evaluate the impact of opioid use on duration of therapy (DOT) and overall survival (OS). Patients with no or low opioid use (n = 172) had a median DOT of 12.2 months (95% CI: 6.9-17.4) compared to 1.9 months (95% CI: 1.8-2.0) for those with high opioid use (n = 37, HR 0.26 95% CI: 0.17-0.40, p < 0.001). Patients with no or low opioid use had a median OS of 22.6 months (95% CI: 14.8-30.4) compared to 3.8 months (95% CI: 2.7-4.9) for those with high opioid use (HR 0.26 95% CI: 0.17-0.40 p < 0.001). High opioid use was associated with a shorter DOT and worse OS. This difference remained significant when accounting for possible confounding variables. These data warrant investigation of possible mechanistic interactions between opioids, tumor progression, and ICIs, as well as prospective evaluation of opioid-sparing pain management strategies, where possible.
Keyphrases
- advanced non small cell lung cancer
- pain management
- epidermal growth factor receptor
- chronic pain
- small cell lung cancer
- radiation therapy
- squamous cell carcinoma
- electronic health record
- big data
- machine learning
- free survival
- energy transfer
- metabolic syndrome
- data analysis
- mesenchymal stem cells
- robot assisted
- cell therapy
- glycemic control
- brain metastases
- deep learning