Revealing a Brain-Gut Microbiome Connection Following Chronic Opioid Treatment

Less Well-Known Consequences of the Long-Term Use of Opioid Analgesics: A Comprehensive Literature Review

BACKGROUND

The adverse effects of short-term opioid analgesics are well known and acknowledged; however, the spectrum of the sequelae of long-term use seems less clear. Some effects may remain undetected but still have the potential to cause harm and reduce patients' quality of life.

OBJECTIVE

To review the literature on the adverse effects of long-term opioid therapy.

METHODS

We performed a quasi-systematic search, analyzing articles published in the MEDLINE database between January 2000 and March 2021 that identified adverse effects of opioids used for chronic pain treatment.

RESULTS

Growing evidence indicates that there are multiple serious adverse effects of opioid treatment. Long-term opioid use may have significant effects on the endocrine, immune, cardiovascular, respiratory, gastrointestinal, and neural systems. Studies show that long-term opioid treatment increases the risk of fractures, infections, cardiovascular complications, sleep-disordered breathing, bowel dysfunction, overdose, and mortality. Opioids may potentially affect cancer development. Most consequences of the long-term use of opioids have been identified in studies of patients with non-malignant pain.

CONCLUSION

Studies indicate that long-term use of opioids increases the risk of drug-related events in a significant number of patients. Clinicians should be aware of these complications associated with prescribing opioids, discuss them with patients, prevent complications, if possible, and diagnose them early and manage adequately. More human studies are needed to assess the risk, including trials with individual opioids, because they have different adverse effect profiles.

Integrated analysis of concomitant medications and oncological outcomes from PD-1/PD-L1 checkpoint inhibitors in clinical practice

Background

Concomitant medications, such as steroids, proton pump inhibitors (PPI) and antibiotics, might affect clinical outcomes with immune checkpoint inhibitors.

Methods

We conducted a multicenter observational retrospective study aimed at evaluating the impact of concomitant medications on clinical outcomes, by weighing their associations with baseline clinical characteristics (including performance status, burden of disease and body mass index) and the underlying causes for their prescription. This analysis included consecutive stage IV patients with cancer, who underwent treatment with single agent antiprogrammed death-1/programmed death ligand-1 (PD-1/PD-L1) with standard doses and schedules at the medical oncology departments of 20 Italian institutions. Each medication taken at the immunotherapy initiation was screened and collected into key categories as follows: corticosteroids, antibiotics, gastric acid suppressants (including proton pump inhibitors - PPIs), statins and other lipid-lowering agents, aspirin, anticoagulants, non-steroidal anti-inflammatory drugs (NSAIDs), ACE inhibitors/Angiotensin II receptor blockers, calcium antagonists, β-blockers, metformin and other oral antidiabetics, opioids.

Results

From June 2014 to March 2020, 1012 patients were included in the analysis. Primary tumors were: non-small cell lung cancer (52.2%), melanoma (26%), renal cell carcinoma (18.3%) and others (3.6%). Baseline statins (HR 1.60 (95% CI 1.14 to 2.25), p=0.0064), aspirin (HR 1.47 (95% CI 1.04 to 2.08, p=0.0267) and β-blockers (HR 1.76 (95% CI 1.16 to 2.69), p=0.0080) were confirmed to be independently related to an increased objective response rate. Patients receiving cancer-related steroids (HR 1.72 (95% CI 1.43 to 2.07), p<0.0001), prophylactic systemic antibiotics (HR 1.85 (95% CI 1.23 to 2.78), p=0.0030), prophylactic gastric acid suppressants (HR 1.29 (95% CI 1.09 to 1.53), p=0.0021), PPIs (HR 1.26 (95% CI 1.07 to 1.48), p=0.0050), anticoagulants (HR 1.43 (95% CI: 1.16 to 1.77), p=0.0007) and opioids (HR 1.71 (95% CI 1.28 to 2.28), p=0.0002) were confirmed to have a significantly higher risk of disease progression. Patients receiving cancer-related steroids (HR 2.16 (95% CI 1.76 to 2.65), p<0.0001), prophylactic systemic antibiotics (HR 1.93 (95% CI 1.25 to 2.98), p=0.0030), prophylactic gastric acid suppressants (HR 1.29 (95% CI 1.06 to 1.57), p=0.0091), PPI (HR 1.26 (95% CI 1.04 to 1.52), p=0.0172), anticoagulants (HR 1.45 (95% CI 1.14 to 1.84), p=0.0024) and opioids (HR 1.53 (95% CI 1.11 to 2.11), p=0.0098) were confirmed to have a significantly higher risk of death.

Conclusion

We confirmed the association between baseline steroids administered for cancer-related indication, systemic antibiotics, PPIs and worse clinical outcomes with PD-1/PD-L1 checkpoint inhibitors, which can be assumed to have immune-modulating detrimental effects.

Concomitant medications and immune checkpoint inhibitor therapy for cancer: causation or association?

The majority of cancer patients assume concomitant medications for the treatment of cancer-related symptoms or co-morbidities. As immune checkpoint inhibitors expand in the treatment of a widening range of malignancies, drug-drug interactions have become an area of increasing interest due to the potential for some concomitant medications to exert immune-modulatory effects and influence outcomes from immunotherapy. Here, we review the evidence supporting this association across selected drug classes including antibiotics, proton pump inhibitors, metformin, and opioids.

The Microbiome and the Gut-Liver-Brain Axis for Central Nervous System Clinical Pharmacology: Challenges in Specifying and Integrating In Vitro and In Silico Models

The complexity of integrating microbiota into clinical pharmacology, environmental toxicology, and opioid studies arises from bidirectional and multiscale interactions between humans and their many microbiota, notably those of the gut. Hosts and each microbiota are governed by distinct central dogmas, with genetics influencing transcriptomics, proteomics, and metabolomics. Each microbiota's metabolome differentially modulates its own and the host's multi‐omics. Exogenous compounds (e.g., drugs and toxins), often affect host multi‐omics differently than microbiota multi‐omics, shifting the balance between drug efficacy and toxicity. The complexity of the host‐microbiota connection has been informed by current methods of in vitro bacterial cultures and in vivo mouse models, but they fail to elucidate mechanistic details. Together, in vitro organ‐on‐chip microphysiological models, multi‐omics, and in silico computational models have the potential to supplement the established methods to help clinical pharmacologists and environmental toxicologists unravel the myriad of connections between the gut microbiota and host health and disease.

Drug-Abuse Nanotechnology: Opportunities and Challenges

Opioid drug abuse and dependence/addiction are complex disorders regulated by a wide range of interacting networks of genes and pathways that control a variety of phenotypes. Although the field has been extensively progressed since the birth of the National Institute on Drug Abuse in 1974, the fundamental knowledge and involved mechanisms that lead to drug dependence/addiction are poorly understood, and thus, there has been limited success in the prevention of drug addiction and development of therapeutics for definitive treatment and cure of addiction disease. The lack of success in both identification of addiction in at-risk populations and the development of efficient drugs has resulted in a serious social and economic burden from opioid drug abuse with global increasing rate of mortality from drug overdoses. This perspective aims to draw the attention of scientists to the potential role of nanotechnologies, which might pave the way for the development of more practical platforms for either drug development or identification and screening of patients who may be vulnerable to addiction after using opioid drugs.