Introduction

Oliceridine is a newly developed opioid that has already been approved in 2020 in the United States by the Food and Drug Administration (FDA) for the intravenous treatment of acute opioid-requiring pain [1]. Oliceridine has a fast onset time. Analgesia sets in after only 5 to 10 minutes and a maximum plasma level is reached after one administration after 10 minutes. After a one-hour infusion, oliceridine has a half-life of 1.6 to 2.7 hours. The drug is metabolized via the liver isoenzymes CYP2D6 and CYP3A4 [2]. Neither mild nor moderate liver insufficiency nor renal insufficiency necessitates dose adjustment [3]. These properties make oliceridine a suitable analgesic for severe pain in almost all patients.

The special feature of this new opioid is the biased agonism [4]. Conventional opioids, such as morphine, bind to the μ-opioid-receptor and activate the G-protein and the ß-arrestin pathway. The G-protein cascade leads to pain relief, while activation of the ß-arrestin cascade causes negative side effects such as, e.g., nausea, vomiting, or constipation. The unique property of oliceridine is to activate the G-protein cascade while activating the ß-arrestin pathway to a much lesser extent and so leading to fewer side effects.

In postoperative pain management, the practitioner is often faced with moderate to severe acute pain [5]. In postoperative pain therapy, opioids are used in combination with nonopioid analgesics and co-analgesics [6]. This usually leads to pain relief. However, ’conventional’ opioids sometimes have a pronounced side effect profile, as mentioned above, which may require further therapy [7]. For example, nausea and vomiting are treated with antiemetics and constipation with peripheral opioid receptor antagonists [8]. Respiratory depression may result in respiratory support, admission to the ICU, or antagonization with return of pain [9].

All these countermeasures increase costs and can prolong the length of stay in the post-anesthesia care unit (PACU) or even the hospital length of stay [10–12]. In high-risk patients there is a savings potential of 363,944 $ per 1,000 patients with oliceridine [13]. Therefore, avoiding these negative effects of pain therapy while administering sufficient analgesia is highly favorable for patients, caregivers, hospitals and health insurance providers.

The purpose of the planned systematic review and meta-analysis is to investigate the efficacy of a novel biased opioid oliceridine compared to placebo and morphine as a reference substance in moderate to severe postoperative pain. In addition, we will examine the occurrence of side effects and safety compared to placebo and morphine. To date there has been no systematic review or meta-analysis investigating the efficacy, safety, and side effects of oliceridine.

Materials and methods

The meta-analysis will be performed and reported in accordance with the current Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA-P) statement and protocol [14]. The PRISMA-P-checklist can be found as S1 Checklist. The study was conceptualized by AnWo, MiAd, and AlWo. The protocol was registered on the International Platform of Registered Systematic Reviews and Meta-analysis Protocols (INPLASY; http://inplasy.com) with the registration number INPLASY202310063.

Study records and data items

The identified literature will be stored in the Endnote 20 reference management program (Clarivate Analytics, Philadelphia, USA). Duplicates will be removed, and so studies with duplicates will only be considered once. Two researchers (AlWo, AnWo) will independently identify eligible randomized controlled trials with at least single blinding reporting any data listed in Table 1 of the collected references. The results of each researcher will be compared and, in case of discrepancies, a third party (MaUn) will be involved for decision making.

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Table 1. Data that will be extracted from the included trials.

https://doi.org/10.1371/journal.pone.0299320.t001

Data from included trials will be extracted and transferred to an MS Excel sheet (Microsoft, Redmond, Washington, USA) by two researchers independently (AlWo and MaUn) and compared. In case of disagreement, a third party will be involved (AnWi). For data that will be extracted from the trial publications, please see Table 1.

Discussion

Oliceridine seems to be a promising analgesic with an improved side-effect profile compared to conventional non-biased opioids. To further evaluate the efficacy, safety, and side effects of this drug, we will perform this meta-analysis.

To ensure the most holistic search possible, we will search several databases. Especially CENTRAL also covers various databases such as Pubmed, Embase, CINAHL, ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform (ICTRP). The search terms are also broad, with only the drug name and synonyms. Oliceridine has been approved by the FDA since 2020. With this open-search strategy, we expect no more than an average of 250 hits per database and can thus detect almost all published studies with a high probability.

We will include patients in a time frame of up to 72 hours postoperatively. Pain perception is greatest in the first three days after surgery. This is also associated with analgesic or opioid use. Subsequently, both pain and opioid consumption decrease [22, 23]. By examining this time window, we are more likely to capture postoperative acute pain and thus understand the efficacy, safety, and side effects of oliceridine.

In addition to study and population-specific data from patients, we will extract a multitude of relevant opioid-related side effects. Opioid-related side effects may limit its use and may cause a negative patient experience. There are indications that there is an increasing dose-dependent occurrence of side-effects [2]. To address this issue, we will perform a subgroup analysis and a meta-regression regarding the initial dose and the time-dependent cumulative dose.

We will use Comprehensive Meta-Analysis (CMA) for data synthesis in the current version. CMA has the advantage over other meta-analysis software to allow data input in various formats which are then automatically transformed into the effect size. Another advantage is the automatically generated prediction interval. Apart from the mean effect size with its confidence interval from current studies, the prediction interval tells us the true effect size of any population and should be presented in each meta-analysis [17].

Many meta-analyses use the fixed or random effect model based on statistical heterogeneity based on the I² statistics. This approach is inappropriate [24]. We assume a natural heterogeneity based on varying drug dosing, surgery, anesthesia, and populations. Thus, we will use a random-effects model to generate generalizable results.

As effect size for dichotomous data, we will use the risk ratio (RR). Compared to the odds ratio (OR), the RR is more clinically intuitive [25] and seems to us and the potential readership appropriate. As effect size for continuous or mixed data we will use Hedges’s g, a slightly modified version of Cohen D that provides a better estimate as the difference in estimates converges with larger numbers [26].

This will be the first meta-analysis to evaluate the efficacy and effectiveness of oliceridine compared to placebo or morphine in postoperative acute pain. Our aim with this work is to evaluate and classify the clinical utility of this relatively new substance in a broad postoperative context.

Supporting information