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\begin{document}

\title{Population Pharmacokinetics of Linezolid: A Systematic Review}



\author[1]{Yan Qin}%
\author[2]{Li-li Zhang}%
\author[2]{Yan-rong Ye}%
\author[2]{Yue-ting Chen}%
\author[3]{Zheng Jiao}%
\affil[1]{Shanghai Chest Hospital}%
\affil[2]{Affiliation not available}%
\affil[3]{Shanghai Jiao Tong University Affiliated Chest Hospital}%


\vspace{-1em}



  
  \date{May 29, 2024}


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\selectlanguage{english}
\begin{abstract}
Background Linezolid is often used for the infections caused by
drug-resistant Gram-positive bacteria. Recent studies suggested that
large between-subject variability (BSV) and within-subject variability
could alter drug pharmacokinetics (PK) during linezolid therapy due to
pathophysiological changes. Objective The review synthesized information
on linezolid population PK studies and summarized the significant
covariates that influence the PKs of linezolid. Methods A literature
search was performed from PubMed, Web of Science, and Embase from their
inception to 30 September 2021. Published studies were included if they
contained data analyzing linezolid PK parameters in humans using a
population approach with a nonlinear mixed-effects model. Results
Twenty-five studies were included in adults and five studies in
pediatric patients. One- and two-compartment models were the commonly
used structural models for linezolid. Body size {[}weight, lean body
weight, and body surface area{]}, creatinine clearance (CLcr), and age
significantly influenced linezolid PK. The median clearance (CL) values
(range) in infants {[}0.128 L/h/kg (0.121-0.135){]} and children
{[}0.107 L/h/kg (0.088-0.151){]} were higher than in adults {[}0.098
L/h/kg (0.044-0.237){]}. For patients with severe renal impairment (CLcr
[?] 30 mL/min), the CL was 37.2\% (15.2-55.3\%) lower than in patients
with normal renal function. Conclusion Linezolid's optimal dosage could
be adjusted based on the patient's body size, renal function, and age.
More studies are needed to explore the exact mechanism of elimination of
linezolid and evaluate PK characteristics in pediatric patients.%
\end{abstract}%



\sloppy


\textbf{Population Pharmacokinetics of Linezolid: A Systematic Review}

Yan Qin\textsuperscript{1,2*}, Li-Li Zhang\textsuperscript{3*}, Yan-Rong
Ye\textsuperscript{2*}, Yue-Ting Chen\textsuperscript{1}, Zheng
Jiao\textsuperscript{1}

\textsuperscript{1} Department of Pharmacy, Shanghai Chest Hospital,
Shanghai Jiao Tong University, Shanghai, China.

\textsuperscript{2} Department of Pharmacy, Zhongshan Hospital, Fudan
University, Shanghai, China

\textsuperscript{3} Department of Pharmacy and Purchasing Management,
the 900th Hospital of PLA joint logistics support force, Fuzhou, China.

Running heading: population pharmacokinetics of linezolid

Correspondence:

Zheng Jiao, Professor

Email: jiaozhen@online.sh.cn

ORCID: \emph{0000-0001-7999-7162}

\textsuperscript{*} Yan Qin, Li-Li Zhang and Yan-Rong Ye contributed
equally to this work

\subsection*{Acknowledgments}

{\label{acknowledgments}}

The authors would like to sincerely thank Dr Jason A. Roberts from
Burns, Trauma and Critical Care Research Centre, The University of
Queensland, Australia for providing details about the research and
active discussions on the coding. We would like to thank Chen-yu Wang
MPharm from Shanghai Chest Hospital; and Ye Zou Pharmacist from
Department of Pharmacy, Zhongshan Hospital, Fudan University, China for
their critical comments.

\subsection*{Abstract}

{\label{abstract}}

\emph{Background} ~Linezolid is often used for the infections caused by
drug-resistant Gram-positive bacteria. Recent studies suggested that
large between-subject variability (BSV) and within-subject variability
could alter drug pharmacokinetics (PK) during linezolid therapy due to
pathophysiological changes.

\emph{Objective} ~The review synthesized information on linezolid
population PK studies and summarized the significant covariates that
influence the PKs of linezolid.

\emph{Methods} ~A literature search was performed from PubMed, Web of
Science, and Embase from their inception to 30 September 2021. Published
studies were included if they contained data analyzing linezolid PK
parameters in humans using a population approach with a nonlinear
mixed-effects model.

\emph{Results~} Twenty-five studies were included in adults and five
studies in pediatric patients. One- and two-compartment models were the
commonly used structural models for linezolid. Body size {[}weight, lean
body weight, and body surface area{]}, creatinine clearance (CLcr), and
age significantly influenced linezolid PK. The median clearance (CL)
values (range) in infants {[}0.128 L/h/kg (0.121-0.135){]} and children
{[}0.107 L/h/kg (0.088-0.151){]} were higher than in adults {[}0.098
L/h/kg (0.044-0.237){]}. For patients with severe renal impairment (CLcr
[?] 30 mL/min), the CL was 37.2\% (15.2-55.3\%) lower than in patients
with normal renal function.

\emph{Conclusion~} Linezolid's optimal dosage could be adjusted based on
the patient's body size, renal function, and age. More studies are
needed to explore the exact mechanism of elimination of linezolid and
evaluate PK characteristics in pediatric patients.

\subsection*{Key words}

{\label{key-words}}

linezolid, individualized drug therapy, nonlinear mixed-effects model,
population pharmacokinetics

\subsection*{1 Introduction}

{\label{introduction}}

Linezolid, an oxazolidinone antibiotics, plays an essential role against
drug-resistant Gram-positive bacteria, such as
methicillin-resistant\emph{Staphylococcus} \emph{aureus} ,
vancomycin-resistant\emph{Enterococci} , coagulase-negative
S\emph{taphylococci} , penicillin-insensitive \emph{Streptococcus
pneumoniae} , \emph{and}multidrug-resistant and extensively
drug-resistant \emph{Mycobacterium tuberculosis} {[}1-4{]}\emph{.} It is
approved for treating infections induced by susceptible strains of
designated microorganisms, such as bacteremia, nosocomial pneumonia,
skin and soft tissue infections, and community-acquired pneumonia {[}1,
5{]}.

Linezolid bioavailability is approximately 100\%, and no dosage
adjustment is necessary when switching from intravenous to oral therapy.
Food does not affect linezolid absorption {[}6{]}. Linezolid plasma
protein binding is approximately 31\%, and its volume of distribution is
approximately 40-50 L in adults {[}7, 8{]}. Linezolid is primarily
metabolized in the liver through oxidation of the morpholine ring,
producing two major inactive metabolites: PNU142586 and PNU142300.
Linezolid inhibits its own metabolism. Linezolid clearance can be
inhibited to 51.3-85.5\% of its initial value over time, resulting in
nonlinear elimination {[}9-11{]}. Approximately 30\% of linezolid is
excreted unchanged in the urine through the kidneys. Non-renal clearance
is around 65\% of total linezolid clearance {[}12, 13{]}. Linezolid has
a time-dependent antibacterial activity with mild to moderate
post-antibiotic effects. The efficacy pharmacodynamic targets are the
ratio of the area under the concentration-time curve over 24 hours
(AUC\textsubscript{0}-\textsubscript{24 h}) to the minimum inhibitory
concentration (MIC) of 80-120 (AUC\textsubscript{0-24 h}/MIC = 80-120,
ideal 100) and the percentage of time the drug concentration remains
greater than the MIC (T\% \textgreater{} MIC) for at least 85\% of the
dosing interval, ideal 100\%, at a steady-state {[}14{]}.

Recent studies suggest a large between-subject variability (BSV) for
linezolid with a remarkable percentage of subtherapeutic levels in
critically ill patients {[}15-18{]}. Inadequate exposure can lead to
therapy failure and bacterial resistance. Among the adverse effects of
linezolid, reversible thrombocytopenia has attracted the most attention
and is associated with increased exposure and a longer duration of
therapy {[}8, 19-21{]}. Furthermore, sepsis, diabetes, total body weight
(TBW), renal function, renal replacement therapies, and liver function
could influence linezolid clearance {[}11, 22-25{]}. Therefore, it is
necessary to perform an individualized drug therapy considering the
pharmacokinetics (PK) of linezolid and factors that affect drug
exposure.

The population PK \textbf{(} PPK\textbf{)} approach is a powerful tool
for evaluating factors that influence PK in target patients and helps
physicians identify high-risk patient subgroups for therapy failure. The
PPK model can optimize individual doses through Bayesian forecasting.
Moreover, Monte Carlo simulations based on the PPK model allow for the
prediction of covariate effects in the target population and estimation
of the probabilities of target attainment (PTA). Extensive PPK studies
for linezolid have been performed in various populations; however, data
regarding linezolid PPK modeling have not been summarized so far. This
review provides synthetic information on linezolid PPK studies and aims
to summarize the significant covariates that influence the
pharmacokinetics of linezolid and identify any issues that need further
exploration.

\subsection*{2 Methods}

{\label{methods}}

\subsubsection*{2.1 Search strategy}

{\label{search-strategy}}

The review focused on the PPK of linezolid. The literature was
systemically searched from PubMed, Web of Science, and Embase from its
inception to 30 September 2021 according to the Preferred Reporting
Items for Systematic Reviews and Meta-Analyses (PRISMA-2020) guidelines
{[}26{]}. The following search terms were used: `linezolid' or `Zyvox'
or `PNU-100766' or `U-100766' or `oxazolidinone' and `population
pharmacokinetic*' or `pharmacokinetic model*' or `nonlinear mixed effect
model' or `NONMEM' or `WINNONMIX' or `ADAPT' or `P-PHARM' or `nlmixed'
or `NLME' or `MONOLIX.' Detailed search strategies were listed in the
electronic Supplementary Table S1. In addition, reference lists of the
selected articles were screened to identify other relevant papers. Two
independent authors conducted the title and abstract screening followed
by the full-text screening using EndNote (version 9.2; Thomson
Scientific, Box Hill, Victoria, Australia). Discrepancies were resolved
by consulting a senior investigator.

Identified studies included in this review should meet the following
criteria: (1) study population: human studies (healthy subjects or
patients); (2) treatment: linezolid administered by oral route or
intravenous infusion; (3) modeling approach: a parametric non-linear
mixed effect modeling approach. Studies were excluded if (1) they were
reviews or methodology articles; (2) data overlapped with later
published articles; (3) studies lacked the necessary model information;
and (4) studies written in a language other than English.

\subsubsection*{2.2 Data Extraction}

{\label{data-extraction}}

The following information was extracted from eligible articles by two
independent authors: (1) demographic data of the population (e.g.,
country, age, body size, gender), (2) study characteristics (e.g.,
dosage regimens, bioanalytical methods, sample numbers, sampling
schedule), and (3) PPK characteristics such as analysis software and
algorithm, structural models, covariates, covariate screening method, PK
parameters and formula, BSV, and residual unexplained variability (RUV).

\subsubsection*{2.3 Quality Assessment}

{\label{quality-assessment}}

The quality of the included studies was assessed using a 35 item
checklist (Table S2) considered essential for the reporting of clinical
PK studies {[}27, 28{]}. The items proposed in the checklist were
categorized into five parts based on relevance to a traditional PPK
research report: title/abstract, background, methods, results, and
discussion/conclusion. One point was given for each item if the
information contained in the identified study met the criteria.
Otherwise, the item was given 0 points. Compliance was used to evaluate
the quality of each PPK study, which was calculated using the following
equation:

\emph{compliance} (\%) = (sum of items reported / sum of all items) \selectlanguage{ngerman}×
100\%

\subsubsection*{2.4 Study comparison}

{\label{study-comparison}}

The characteristics of the studies and PPK analyses were summarized in a
tabular format for comparison. One thousand virtual patients were
simulated and their concentration-time profiles were plotted according
to the published PPK models in each identified study. Virtual patients
were defined as follows: neonates (4 kg, 14 days) taking 40 mg of
linezolid every 8 h (q8h), infants (10 kg, 1 year) taking 100 mg of
linezolid q8h, children (25 kg, 7 years) taking 250 mg of linezolid q8h,
adults (70 kg, 40 years) taking 600 mg of linezolid q12h, and elderly
(70 kg, 80 years) taking 600 mg of linezolid q12h. A steady-state was
assumed if a patient received multiple doses of linezolid. All virtual
patients were set as men. The simulation was run using NONMEM (version
7.5; ICON Development Solutions, Ellicott City, MD, USA). The
concentration-time profiles were plotted using R software (version
4.1.1;\emph{http://www.r-project.org/}).

The impact of identified covariates on clearance (CL) in each study was
summarized and compared using the forest map, conducted using the
forestplot package (version 1.9; https://gforge.se/packages/) within the
R packages. Continuous covariates were scaled to the same range for
comparison. If continuous covariates were identified in only one study,
the minimum and maximum values of the covariates in this study were
used. For binary covariates such as dialysis, 0 was for dialysis
patients during linezolid treatment and 1 for patients without dialysis.
The minimum and maximum CL values were calculated according to the range
of the identified covariates in each study. The reference value of CL
was normalized to the median covariate values in each study. The effect
of each covariate on CL was expressed as the percentage of the CL range
divided by the CL reference value. A change in CL of less than 80\% or
more than 125\% was considered clinically significant {[}29{]}.

\subsection*{3 Results}

{\label{results}}

\subsubsection*{3.1 Study identification}

{\label{study-identification}}

A total of 851 studies were identified: 354 from PubMed, 107 from
Embase, and 390 from Web of Science. An additional study was obtained by
checking the reference lists of the included articles. Forty-four
studies were eligible for full-text screening after duplicate removal
and title and/or abstract selection. Fourteen studies were excluded due
to missing PPK parameters, not being written in English, using a
nonparametric method to establish PPK models or duplicate data reported
in other articles. Finally, 30 studies were included in this review for
further analysis. The PRISMA flow diagram of study identification is
presented in Fig.1.

\subsubsection*{3.2 Evaluation of the
literature}

{\label{evaluation-of-the-literature}}

The quality results of the PPK studies are shown in Table 1. Compliance
with each study ranged from 68.6 to 97.1\%, with a median value of
85.7\%. Most studies did not report the route of linezolid
administration in the tile/abstract section, co-medications, food
interactions, methods for handling missing data in the method section,
and the schematics of the final model in the results section.

\subsubsection*{3.3 Study characteristics}

{\label{study-characteristics}}

All studies were published between 2003 and 2021. The characteristics of
the included PPK studies are listed in Table 2. Six studies were
conducted in China {[}17, 30-34{]}, six in Japan {[}24, 35-39{]}, four
in Germany {[}22, 40-42{]}, and two in Italy {[}4, 43{]}. Another 12
studies were conducted in the US, UK, Brazil, Australia, Spain, France,
Korea, Greece, Canada, and South Africa {[}18, 25, 44-49{]}. Most of the
studies were single-center and seven were multicenter studies {[}7, 11,
33, 38, 47, 50, 51{]}. Sparse samplings were employed in 19 studies
including pre-dose and 1-2 h post-dose {[}4, 17, 22, 25, 32-34, 36-39,
44-50{]}. The number of participants in each study ranged from 9 to 603,
and 19 studies included less than 50. In most studies, subjects were
patients with Gram-positive bacterial infections, with comorbidity of
sepsis, burns, liver impairment, and renal impairment with or without
renal replacement therapy. Two studies were conducted in tuberculosis
patients {[}46, 48{]}. Only one study consisted of both patients and
healthy volunteers {[}11{]}. Among the included studies, five studies
were conducted in pediatrics and another 25 studies were conducted in
adults.

In most studies, linezolid was administered at a dose of 600 mg q12h to
adults (Table 2). The dose regimens for pediatric patients were 10 mg/kg
q8h or q12h or q24h. Plasma linezolid concentrations were determined by
liquid chromatography with ultraviolet detection (n=23) or mass
spectrometry (n=7). The lowest limit of quantification ranged from 0.001
to 0.78 mg/L.

\subsubsection*{3.4 Population pharmacokinetic
characteristics}

{\label{population-pharmacokinetic-characteristics}}

Most PPK models were developed with NONMEM software, with the exception
of five studies that were developed by ADAPT II {[}44{]}, Monolix
{[}50{]}, Pumas {[}49{]}, and Phoenix NLME {[}32, 34{]}. The algorithms
used mainly were first-order conditional estimation (FOCE) or FOCE
with\selectlanguage{greek}\emph{η-ε} \selectlanguage{english}interaction. Eighteen studies described linezolid PPK as
a one-compartment model and 11 as a two-compartment model. Only one
study used a three-compartment model. First-order elimination was
reported in 27 studies. One study suggested that linezolid followed the
elimination of time-dependent autoinhibition {[}11{]}. Another two
studies reported that parallel first-order renal and Michaelis-Menten
(MM) nonrenal elimination was superior to a simple first-order or MM
elimination model {[}42, 44{]} (Table 2).

3.4.1 Clearance and volume of distribution

{\label{clearance-and-volume-of-distribution}}

The median CLs in infants and children were higher than in adults, and
the median CL in neonates was much lower than in other populations. The
estimated median CL of linezolid was 0.042 L/h/kg for neonates (4kg, 14
days), 0.128 L/h/kg (range: 0.121-0.135) for infants (10kg, 1 year),
0.107 L/h/kg (range: 0.088-0.151) for children (25kg, 7 years), and
0.098 L/h/kg (range: 0.044-0.237) for adults (70 kg 40 years).
Additionally, no significant ethnic differences were shown in the PK
profile of linezolid. The PK parameters were close among Caucasians,
Asians, and Africans. The median volumes of distribution (V) per
kilogram in neonates and children were higher than in adults and
infants. The median V was 0.675 L/kg for neonates (4kg, 14 days), 0.5
L/kg (range: 0.41-0.59) for infants (10kg, 1 year), 0.784 L/kg (range:
0.592-1.36) for children (25kg, 7 years), and 0.594 L/kg (range:
0.197-2.99) for adults (70 kg, 40 years).

3.4.2 Random effects

{\label{random-effects}}

BSV was described by an exponential model in all studies. The median
coefficient of variation (CV) for BSV was as follows: CL, 46.6\% (range:
23.2- 66.9\%), and V, 33.9\% (range: 10.9-142.0\%). RUV was described by
proportional models in 14 studies {[}7, 11, 24, 31, 32, 34, 36, 37, 39,
42, 46, 47, 49, 50{]}, additive models in two studies {[}25, 35{]}, and
combined proportional and additive models in 14 studies {[}4, 17, 18,
22, 30, 33, 38, 40, 41, 43-45, 48, 51{]}. The proportional RUV ranged
from 2.5\% to 102\% (median 17.5\%) and the additive RUV ranged from
0.007 mg/L to 1.9 mg/L (median 0.26 mg/L) among all studies. Only one
study reported an inter-occasion variability of 23.0\% in CL and V.

3.4.3 Covariate screening

{\label{covariate-screening}}

Most studies were intended to identify covariates to explain the BSV of
linezolid PK, except for three studies, in which no covariates were
investigated due to the limited included subjects. A stepwise method
including forward inclusion and backward elimination was the most
frequently used method for covariate screening. All covariates tested
and identified on CL and V are summarized in Table S3. The most
influential covariates were body size, renal function, and age. The
impact of each covariate on CL is shown in Fig.2.

Body sizes, including total body weight (TBW) and body surface area
(BSA), were reported in 16 (53.3\%) studies, all of which except one
study had a significant influence on CL with a change of larger than
20\%, as shown in Fig.2. Furthermore, the effect of renal function (CLcr
or eGFR) was reported in 13 (43.3\%) studies, and nine of them showed a
change of CL greater than 20\%. For patients with severe renal
impairment (CLcr [?] 30 mL/min), the CL was 37.2\% (15.2-55.3\%) lower
than that in patients with normal renal function.

Five studies investigated the influence of postnatal age on CL in
pediatric patients, and two of them showed that the change was greater
than 20\%. Furthermore, CL was found to increase with increasing
postnatal age. The linezolid concentration-time profile in neonates (4
kg, 14 days) was significantly higher than in infants and children with
the same dose per weight, as shown in Fig.3.

Five of the 25 studies found that age was associated with linezolid CL
in adult patients, and the influence of age on CL was greater than 20\%
in three reported studies. Meanwhile, four studies indicated that age
was negatively correlated with CL. Elderly patients (70 kg, 80 years)
showed considerably higher PK profiles than adults (70 kg, 40 years) in
three studies {[}4, 39, 50{]}.

Seventeen studies investigated the impact of liver function on CL, seven
of which found that CL in patients with liver dysfunction was reduced by
36.4-71.5\% {[}36, 37, 44, 53, 58-60{]}. Liver cirrhosis, liver
transplant, or liver resection, and laboratory tests such as alanine
aminotransferase (ALT), aspartate aminotransferase (AST), maximal liver
function capacity (LiMAx), and prothrombin (PTA) were identified as
significant covariates on CL.

Body sizes, including TBW, lean body weight (LBW), and BSA, were the
most reported covariates influencing V. Additionally, peritonitis was
reported to affect V (Table 3). No other covariates were identified.

3.4.4 Model evaluation

{\label{model-evaluation}}

All models were assessed by an internal evaluation. Diagnostic plots,
bootstraps, and visual predictive checks were the most commonly used
methods. A normalized prediction distribution error (NPDE) was adopted
in three studies {[}30, 33, 47{]}. Furthermore, only one study was
evaluated using an independent dataset and showed acceptable
predictability {[}51{]}. External validation is recommended to evaluate
the predictive performance of the PPK model prior to clinical
implementation.

3.4.5 Model informed precision dosing

{\label{model-informed-precision-dosing}}

Sixteen studies conducted a model-based simulation to propose dosing
regimens to achieve the [?] 80\% or 90\% PTA, defined as AUC/MIC 80-120
{[}17, 24, 25, 30, 32-35, 42, 46, 48, 49, 51{]}. Six studies also
adopted T\% \textgreater{} MIC being 100\% or 85\% as a supplementary
target {[}17, 24, 42, 47, 49, 51{]}. In addition, three other studies
used only linezolid trough concentration (C\textsubscript{0}) as the
target index.

Linezolid dosage regimens were proposed based on the developed models.
For neonates, 8 mg/kg (q8h) for an MIC of 1 mg/L and 12 mg/kg (q8h) for
an MIC of 2 mg/L were required to reach PTA \textgreater{} 90\%
{[}25{]}. Dosage regimens ranging from 10 to 20 mg/kg of body weight q6h
or q8h were recommended for children {[}30, 34{]}. For obese patients
with body weights over 100 kg, 600 mg q8h or more was required to
achieve PTAs of [?] 90\% for a MIC of 2 mg/L {[}42, 49{]}. A linezolid
dosing regimen for adult patients with renal impairment was recommended,
which ranged from 300 to 1,200 mg q12 h based on renal function {[}4,
24, 32, 33, 35, 37{]} (Table 4). Dosing regimens of 200 mg or 300 mg
(q12h) were recommended for patients with liver impairment {[}32, 35{]}.
Some studies also found that if MICs were [?] 4 mg/L, low PTAs were
obtained even with increased linezolid dosing {[}33, 42, 49{]}.

\subsection*{4 Discussion}

{\label{discussion}}

Linezolid is an essential therapeutic choice against multidrug-resistant
Gram-positive bacteria. Unfortunately, linezolid's large variabilities
make individualized dosing regimens necessary {[}52{]}. Several PPK
studies of linezolid have been conducted to identify the source of
variability among different populations. Our systematic review is the
first to summarize the PPK of linezolid to facilitate the optimal
pharmacotherapy of linezolid.

Weight was the most significant covariate that affected linezolid PK in
pediatric patients. Total clearance increased with increasing weight in
most studies. Infants and children showed higher CL per weight than
adults, which could be attributed to a higher body fat/lean mass ratio,
decreased kidney blood flow, and lower total body water in adults. Two
studies reported that postnatal age was also a significant covariate
that influenced linezolid CL in pediatric patients {[}25, 39{]}, which
probably reflects the maturation of the liver and kidney, which are
essential for linezolid PK.

For adult patients, nine studies reported that weight had a significant
influence on CL {[}7, 22, 36, 38, 40, 44, 45, 47, 49{]}, with eight
studies indicating a considerable change greater than 20\%. For patients
with a bodyweight of 40 kg, the CL of linezolid decreased by 34.3\%
(15.8-46.6\%) compared to patients with a normal body weight of 70 kg,
indicating that a reduced dose may be needed in patients with low body
weight. On the contrary, for obese patients with a body weight of 120
kg, the CL of linezolid increased by 54.3\% (42.2-82.9\%) compared to
the CL of 70 kg patients. Therefore, obese patients may be at higher
risk of not achieving the pharmacodynamic target at the standard dose of
linezolid, and an increased dose may be appropriate.

Both the classic PK analysis and the PPK approach suggested that renal
clearance accounted for about 30\% of the total clearance of linezolid
{[}8, 12, 44{]}. Fourteen population PK studies in this review
identified CL\textsubscript{CR} as a covariate on CL {[}4, 11, 22, 23,
30, 32, 33, 35-38, 43, 44, 51{]}. Furthermore, serum creatinine instead
of CLcr was selected as a covariate on CL in one study of neonates
{[}25{]} and four studies conducted in adults {[}31, 42, 43, 49{]}.
Patients with renal replacement therapy (such as hemodialysis,
hemodiafiltration, and hemofiltration) had a higher clearance of
linezolid {[}22, 24, 40{]}. Clearance varied with the dialysis method,
the afferent flow rate, and the efferent flow rate {[}22, 24{]}. In
studies in which CL\textsubscript{CR} or creatinine was not identified
as a covariate on CL, most study subjects had a normal renal function or
mild renal impairment {[}17, 25, 34, 37, 47{]}. Linezolid dosing
regimens need to be adjusted according to renal impairment.

Five studies indicated that linezolid PK was influenced by age in adult
patients {[}4, 7, 17, 38, 47{]}, and 80\% of these studies found that
linezolid CL decreased with age. CL in elderly patients (70 kg, 80
years) was reduced by 20.82-79.66\% compared to that of adult patients
(70 kg, 40 years), possibly due to the decrease in renal or liver
function as a result of aging. Previous studies showed that reduced ROS
production could be caused by aging, but the exact mechanism of aging
remains unexplained, which requires further investigation {[}7{]}.

Linezolid is mainly metabolized in the liver. Liver function (ALT, AST)
influenced linezolid clearance in several studies. A notable decrease in
CL (about 50\%-60\%) was observed in patients with liver
transplantation/resection or patients with severe liver cirrhosis
(Child-Pugh C) {[}35, 36{]}. The decrease is possibly due to fibrosis,
damage to the lobular structure, altered enzyme expression, and reduced
blood flow. These changes result in less transport of drugs and oxygen
to hepatocytes {[}53{]}.

Several classic PK studies demonstrated that clearance after multiple
doses was smaller than that of a single dose or the first dose, which
could be explained by time-dependent autoinhibition of linezolid
elimination in the liver {[}54-57{]}. Linezolid could inhibit the enzyme
activity of the mitochondrial oxidative respiratory chain at therapeutic
levels, resulting in less ATP produced from oxidative phosphorylation
and reduced linezolid metabolisms{[}9, 12, 58, 59{]}. However, many
included PPK studies in this review reported that linezolid showed
first-order elimination. Only one study reported time-dependent
autoinhibition, and two described parallel first-order and MM
elimination. The results could be attributed to the treatment being not
long enough to produce time-dependent autoinhibition.

\subsection*{5 Limitations}

{\label{limitations}}

Our systematic review has the following limitations. Models developed
from nonparametric methods were omitted. Only studies published in
English were selected. Since this review aimed to identify critical
covariates that influence linezolid PKs and compare linezolid PKs among
different age groups, PK/PD models were not summarized.

\subsection*{6 Conclusion}

{\label{conclusion}}

This review summarized key aspects related to linezolid PPK for clinical
application and future research. Weight, renal function, and age
significantly influenced linezolid CL, and linezolid dose should be
individualized. Meanwhile, considering the high BSV and RUV of linezolid
PKs, therapeutic drug monitoring may be helpful in maintaining optimal
linezolid exposure. More PPK studies are needed in pediatric patients,
along with larger sample sizes. The exact mechanism of elimination of
linezolid needs to be explored to facilitate the design of optimal
dosing regimens.

\subsection*{Declarations}

{\label{declarations}}

\textbf{Conflict of Interest Disclosure} Yan Qin, Li-li Zhang, Yan-rong
Ye, Yue-ting Chen, and Zheng Jiao declare they have no conflicts of
interest.

\textbf{Ethics Approval Statement} Not applicable.

\textbf{Funding Statement} Not applicable.

\textbf{Patient Consent Statement} Not applicable.

\textbf{Consent for Publication} Not applicable.

\textbf{Availability of Data and Material} The datasets generated during
and/or analysed during the current study are available from the
corresponding author on reasonable request.

\textbf{Code Availability} Not applicable.

\textbf{Author contributions Yan Qin:} Investigation, Data curation,
Write- Original draft, Writing-Reviewing and Editing,
Visualization;\textbf{Li-li Zhang:} Investigation, Write- Original
draft, Writing- Reviewing and Editing; \textbf{Yan-rong Ye:} Writing-
Reviewing and Editing, Supervision; \textbf{Yue-ting Chen:} Soft,
Validation;\textbf{Zheng Jiao:} Conceptualization, Methodology, Writing-
Reviewing and Editing, Supervision.

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