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\begin{document}

\title{Exploratory associations of tacrolimus exposure and clinical outcomes
after lung transplantation: a retrospective, single center experience}



\author[1]{Wenwen Du}%
\author[1]{Xiaoxing Wang}%
\author[1]{Dan Zhang}%
\author[2]{WenQian Chen}%
\author[1]{Xianbo Zuo}%
\affil[1]{China-Japan Friendship Hospital}%
\affil[2]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 21, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Aims: This study aimed to investigate the potential impact of tacrolimus
(TAC) exposure on clinical outcomes after lung transplantation. Methods:
This retrospective observational study enrolled a total of 234 lung
transplant recipients. TAC trough levels (C\textsubscript{0}) were
collected for 3 intervals: 0--3 months, 3--12 months, and 12--24 months.
The intra-patient variability (IPV) was calculated using coefficient of
variation. Genotyping of \emph{CYP3A5*3} (rs776746) was performed.
Patients were further divided into groups based on the
C\textsubscript{0} cut-off value of 8 ng/mL and IPV cut-off value of
30\%. Cox proportional hazards regression models were used to explore
the potential impact of C\textsubscript{0} and IPV on outcomes of
interests, including donor-specific antibodies (DSA), chronic lung
allograft dysfunction (CLAD) and mortality. Results: The influence of
\emph{CYP3A5*3} polymorphism was only significant for C\textsubscript{0}
and IPV during the first 3 months. Low C\textsubscript{0} (\textless{} 8
ng/mL) at 3--12 months increased the risk of DSA (hazard ratio {[}HR{]}
2.820, 95\% confidence interval {[}CI{]} 1.093--7.276) and mortality (HR
2.220, 95\% CI 1.162--4.243), while High IPV (\textgreater{}=30\%)
during this period was associated with an increased risk of mortality
(HR 2.100, 95\% CI 1.120--3.937). Patients with Low
C\textsubscript{0}/High IPV combination had significantly higher risks
for DSA (HR 4.534, 95\% CI 1.326--15.507) and survival (HR 4.205, 95\%
CI 1.739--10.168), surpassing the predictive power provided by
C\textsubscript{0} or IPV alone. Conclusion: A combination of Low
C\textsubscript{0}/High IPV might be considered in categorizing patients
towards risk of adverse clinical outcomes following lung
transplantation.%
\end{abstract}%



\sloppy


\textbf{Exploratory associations of tacrolimus exposure and clinical
outcomes after lung transplantation: a retrospective, single center
experience}

\textbf{Running title}

Tacrolimus exposure in lung transplantation

Wenwen Du \textsuperscript{1}, Xiaoxing Wang \textsuperscript{1}, Dan
Zhang \textsuperscript{1}, Wenqian Chen \textsuperscript{1}, Xianbo
Zuo\textsuperscript{1, 2}

\textsuperscript{1} Department of Pharmacy, China-Japan Friendship
Hospital, Chaoyang District, Beijing, China

\textsuperscript{2} Department of Dermatology, China-Japan Friendship
Hospital, Chaoyang District, Beijing, China

\textbf{Correspondence}

Xianbo Zuo, Department of Dermatology, Department of Pharmacy,
China-Japan Friendship Hospital, Chaoyang District, Beijing, China.

Email: subpharm@163.com

\textbf{KEYWORDS}

Tacrolimus; intra-patient variability; lung transplantation; chronic
lung allograft dysfunction; donor-specific antibody

Word count:3486, table count: 3, figure count: 5.

\textbf{What is already known about this subject}

\begin{itemize}
\tightlist
\item
  There is ongoing controversy regarding the association between
  tacrolimus C\textsubscript{0} or IPV and clinical outcomes after lung
  transplantation.
\item
  The impact of \emph{CYP3A5*3} genotype on C\textsubscript{0} is
  validated. Whether it affects IPV and clinical outcomes remains
  controversial.
\item
  Furthermore, the impact of C\textsubscript{0}/IPV combination on
  clinical outcomes remains unexplored.
\end{itemize}

\textbf{What this study adds}

The combination of IPV \textgreater{} 30\% and
C\textsubscript{0}\textless{} 8 ng/mL during 3--12 months post-lung
transplantation was associated with higher risk of donor-specific
antibodies and mortality.

The impact of \emph{CYP3A5*3} polymorphism on C\textsubscript{0} and IPV
was limited to the initial three months.

\textbf{Abstract}

\textbf{Aims:} This study aimed to investigate the potential impact of
tacrolimus (TAC) exposure on clinical outcomes after lung
transplantation.

\textbf{Methods:} This retrospective observational study enrolled a
total of 234 lung transplant recipients. TAC trough levels
(C\textsubscript{0}) were collected for 3 intervals: 0--3 months, 3--12
months, and 12--24 months. The intra-patient variability (IPV) was
calculated using coefficient of variation. Genotyping of
\emph{CYP3A5*3}(rs776746) was performed. Patients were further divided
into groups based on the C\textsubscript{0} cut-off value of 8 ng/mL and
IPV cut-off value of 30\%. Cox proportional hazards regression models
were used to explore the potential impact of C\textsubscript{0} and IPV
on outcomes of interests, including donor-specific antibodies (DSA),
chronic lung allograft dysfunction (CLAD) and mortality.

\textbf{Results:} The influence of\emph{CYP3A5*3} polymorphism was only
significant for C\textsubscript{0}and IPV during the first 3 months. Low
C\textsubscript{0} (\textless{}8 ng/mL) at 3--12 months increased the
risk of DSA (hazard ratio {[}HR{]} 2.820, 95\% confidence interval
{[}CI{]} 1.093--7.276) and mortality (HR 2.220, 95\% CI 1.162--4.243),
while High IPV (\textgreater{}=30\%) during this period was associated
with an increased risk of mortality (HR 2.100, 95\% CI 1.120--3.937).
Patients with Low C\textsubscript{0}/High IPV combination had
significantly higher risks for DSA (HR 4.534, 95\% CI 1.326--15.507) and
survival (HR 4.205, 95\% CI 1.739--10.168), surpassing the predictive
power provided by C\textsubscript{0} or IPV alone.

\textbf{Conclusion:} A combination of Low C\textsubscript{0}/High IPV
might be considered in categorizing patients towards risk of adverse
clinical outcomes following lung transplantation.

\textbf{KEYWORDS}

Tacrolimus; intra-patient variability; lung transplantation; chronic
lung allograft dysfunction; donor-specific antibody

\textbf{1 Introduction}

Tacrolimus (TAC) is the primary immunosuppressive agent for lung
transplantation recipients.\textsuperscript{1}Despite its clinical
superiority, prescribing TAC is complicated by its high inter- and
intra-individual variability and narrow therapeutic window. The optimal
therapeutic range for TAC in lung transplant recipients has not yet been
established,\textsuperscript{2} and even when the trough level
(C\textsubscript{0}) falls within predefined range, there is still a
risk of sub-therapeutic or supra-therapeutic fluctuations with each
individual measurement, leading to under- or over- immunosuppression.
Therefore, TAC intra-patient variability (IPV) has been proposed as a
potential risk factor for adverse clinical outcomes. Previous studies
have confirmed the correlation between high IPV and rejection, graft
failure and mortality in kidney and liver transplantation;
\textsuperscript{3-6} however, limited research has been conducted in
lung transplantation.\textsuperscript{7-9}

Furthermore, conflicting evidence exists regarding the reference ranges
of TAC C\textsubscript{0} in lung transplant recipients. Some lung
transplantation centers recommend target ranges of C\textsubscript{0} to
be 10--25 ng/mL within the first two weeks, 10--20 ng/mL for the
subsequent 6--10 weeks, and 10--15 ng/mL thereafter,\textsuperscript{10}
or 12--15 ng/mL during the first year, and lowered to 9--12 ng/ml
thereafter. \textsuperscript{11, 12} However, recent evidence suggests
that these recommendations may need to be revised downwards due to an
increased risk of acute kidney injury (AKI) associated with elevated
C\textsubscript{0} levels following lung transplantation, particularly
when they exceeded 15 ng/mL.\textsuperscript{13,14} On the other hand,
emerging data indicates a potential correlation between lower
C\textsubscript{0} and inferior outcomes. For instance, Ryu reported an
increased risk of rejection when C\textsubscript{0} was below 9 ng/mL at
one month after lung transplantation, \textsuperscript{15} while
Gallagher found that lower C\textsubscript{0} at 6--12 months
post-transplantation was a significant risk factor for chronic lung
allograft dysfunction (CLAD).\textsuperscript{7}

Previous studies have also indicated that the combined effect of dose
corrected concentration (C/D) and high IPV may exert a more pronounced
influence on adverse allograft outcomes. However, this combined effect
has only been observed in kidney transplant recipients thus far;
therefore, it remains to be fully explored in the context of lung
transplantation. \textsuperscript{16, 17}

The cytochrome P450 (CYP) 3A5 isoenzyme plays a crucial role in the
metabolism of TAC. The presence of \emph{CYP3A5*3} (rs776746) mutation
leads to reduced CYP3A5 activity, thereby influencing TAC concentration
and dose requirement. However, at present, the association
between\emph{CYP3A5} genotype and TAC IPV has not been definitely
recognized and further validation is required. \textsuperscript{18}

Therefore, the primary aim of this study was to investigate and validate
the impact of TAC C\textsubscript{0} and IPV on clinical outcomes,
including the development of DSA, CLAD, and mortality, with an objective
to establish optimal TAC exposure values. Furthermore, we conducted an
assessment on the synergistic effect of TAC C\textsubscript{0} and IPV.
Additionally, we examined how the \emph{CYP3A5} genotype influenced TAC
exposure during different time periods following lung transplantation.

\textbf{2 Materials and Methods}

\textbf{2.1 Study design and population}

This is a retrospective, single center study. Patients who received lung
transplantation at China-Japan Friendship Hospital from August 2016 to
August 2022 were selectively enrolled according to the criteria for the
study. The inclusion criteria were: (1) lung transplantation for the
first time; (2) received TAC-based immunosuppressive therapy. The
exclusion criteria were: (1) unable to participate in
\emph{CYP3A5}genotyping; (2) switched to cyclosporine or sirolimus; (3)
incomplete baseline data; (4) survived less than three months.

All procedures in this study were in accordance with the 1964 Helsinki
declaration and its amendments, and was approved by the Ethics Committee
of China-Japan Friendship Hospital in June, 2022 (No. 2022-KY-056-1).

\textbf{2.2 Immunosuppressive regimens}

For induction therapy, patients received methylprednisolone alone or in
combination with basiliximab. Methylprednisolone was given
intraoperatively at a dose of 500--1000 mg. Basiliximab were given both
before transplantation and on post-operative day (POD) 4 at a dose of 20
mg.

The maintenance immunosuppressive regimen consists of immediate-release
capsules of TAC, immediate-release tablets of mycophenolate mofetil, and
prednisone. TAC administration was initiated on POD 1 at a standard
dosage of 2 mg per day, divided into two doses, unless the patient had
an exceptionally high or low body weight. Monitoring of
C\textsubscript{0} commenced on POD 3 and continued thrice weekly during
hospitalization, with additional blood draws conducted monthly or during
follow-up visits. Per protocol in our center, the target ranges for TAC
C\textsubscript{0} were set at 8--10 ng/mL within the first year (0--12
months) and 6--8 ng/mL within the second year (12--24 months) after lung
transplantation, respectively. Initially, mycophenolate mofetil was
administered in a dose of 1000 mg/day divided into two doses. Prednisone
was intravenously administered at a dosage of 1 mg/kg/day from POD 1 to
POD 3, followed by oral administration at a dosage of 0.5 mg/kg/day
which gradually tapered down to a long-term maintenance dose ranging
between 5--10 mg/day.

\textbf{2.3 Data collection}

The pertinent parameters were collected through a retrospective chart
review of all patients, including demographic data (age, sex, height,
weight, comorbidities), laboratory data (alanine aminotransferase (ALT),
aspartate aminotransferase (AST), total bilirubin, serum creatinine,
urea, fasting blood glucose, hemoglobin, hematocrit), transplant-related
data (indication for transplant, transplant type, use of basiliximab and
use of extracorporeal membrane oxygenation (ECMO)), TAC
C\textsubscript{0}, Forced expiratory volume in 1 second (FEV1),
presence of donor-specific antibodies (DSA) and mortality were obtained.

The TAC C\textsubscript{0} values were determined using micro-particle
enzyme immunoassay (ARCHITECT i1000SR immunoassay analyzer, Abbott
U.S.). All TAC C\textsubscript{0} data within the 0--3 months, 3--12
months, and 12--24 months were included. The average TAC
C\textsubscript{0} were calculated for each patient within each
respective epoch. TAC IPV was calculated as the coefficient of variation
(CV) using the formula TAC IPV = (standard deviation/mean) \selectlanguage{ngerman}× 100\%, as
previously reported.\textsuperscript{19} A minimum of three measurements
per each post-transplant epoch were required to calculate IPV.
Respiratory function test was performed at four weeks
post-transplantation and then every 3 months thereafter, or based on
physicians' discretion.

\textbf{2.4 Genotyping}

The \emph{CYP3A5*3} (rs776746) genotype was determined using the Sanger
dideoxy DNA sequencing method. Genomic DNA was extracted from
EDTA-anticoagulated peripheral blood samples using a commercially
available DNA purification kit (EasyPure Blood Genomic DNA Kit,
Transgene Biotech, Beijing, China). Subsequently, genomic DNA samples
were amplified via polymerase chain reaction (PCR) and sequenced
utilizing the ABI 3730XL DNA Sequencer (ABI Co; Majorbio Biotechnology
Co.,Ltd., Beijing, China). The forward primer was
5'-CAGCATTTAGTCCTTGTGAG-3', and the reverse primer was 5'-
ACGACACACAGCAACCTTAG-3'. Data analysis was performed using Chromas
software (Technelysium, South Brisbane, Australia). Patients carrying
the \emph{*1} allele (\emph{CYP3A5*1/*1} or \emph{*1/*3} ) were
categorized as \emph{CYP3A5} expressers, while those with
the\emph{CYP3A5 *3/*3} genotype were classified as
\emph{CYP3A5}Non-expressers.

\textbf{2.5 Outcome definitions}

Our composite end-point outcomes consisted of the incidence of DSA,
chronic lung allograft dysfunction (CLAD), and mortality. Serum samples
were routinely collected post-transplantation to screen for the presence
of anti-human leukocyte antigen (HLA) antibodies. The presence of DSA
was determined by comparing the measured HLA types with donor HLA
typing. CLAD was defined as a 20\% decline from the best post-transplant
FEV1 according to the International Society of Heart and Lung Transplant
Guidelines.\textsuperscript{20} Additionally, we examined the
distribution characteristics of TAC exposure, represented by average
C\textsubscript{0} and IPV, across 3 distinct time periods (0--3 months,
3--12 months and 12--24 months).

\textbf{2.7 Statistical analysis}

Data was processed using Statistical Package for Social Science (SPSS)
19.0. Continuous variables were expressed as mean ± standard deviation
(SD) or median (interquartile range, IQR). Categorical variables were
presented as count (percentage). The differences between groups were
assessed using Student's t-test for normally distributed continuous
variables, and Mann-Whitney U tests for non-normally distributed
continuous variables, as appropriate. Predefined outcomes stratified by
average TAC C\textsubscript{0}, IPV or \emph{CYP3A5} genotype were
analyzed by Kaplan-Meier analysis and compared using the Log-rank test.
Time from transplant to DSA, CLAD or death was modeled using Cox
proportional hazards regression. Potential risk factors included age at
transplant, sex, body mass index (BMI), comorbidities (hypertension,
hyperlipidemia and diabetes), transplant-related data and TAC exposure.
The variables with a \emph{P} value \textless{} 0.2 in the univariate
analysis were included in the multivariate analysis, which employed a
forward likelihood ratio-test approach for constructing final Cox
survival models. \emph{P} \textless{} 0.05 was considered of statistical
significance.

\textbf{3 Results}

\textbf{3.1 Clinical characteristics of patients}

A total of 241 patients underwent lung transplantation and participated
in \emph{CYP3A5} genotyping between August 2016 and August 2022. From
this study population, 5 patients were excluded for using cyclosporine,
1 patient was excluded due to missing data and 1 patient did not survive
the first month post-transplantation, resulting in a final analysis
cohort of 234 patients. The baseline characteristics are presented in
Table 1. The median (IQR) age was 60 (51--65) years old, with males
accounting for 81.2\% of the participants. The most prevalent pulmonary
diagnosis was interstitial lung disease (ILD; 66.2\%), followed by
chronic obstructive pulmonary disease (COPD; 12.0\%), pulmonary
hypertension (PH; 9.8\%), bronchiectasis (3.8\%) and other indications
including bronchiolitis obliterans, pneumoconiosis, hypersensitivity
pneumonitis and cystic fibrosis (8.1\%). The prevalence rates of
diabetes mellitus, hypertension and hyperlipidemia before surgery were
27.8\%, 19.7\% and 18.8\%, respectively. Fifty percent of the patients
(\emph{n} = 117) were \emph{CYP3A5} expressers, while the remaining 50\%
(\emph{n} = 117) were \emph{CYP3A5} non-expressers.

\textbf{3.2 TAC exposure after lung transplantation}

The average TAC C\textsubscript{0} was 8.8 (IQR, 8.1--9.9) ng/mL, 8.5
(IQR, 7.7--9.8) ng/mL, and 7.8 ± 1.5 ng/mL for the epochs 0--3 months,
3--12 months and 12--24 months, respectively; whereas the corresponding
TAC IPV were 36.7\% (IQR, 30.2\%--44.3\%), 30.6\% (IQR, 23.5\%--39.0\%),
and 28.2\% (IQR, 21.8\%--35.0\%) over the same corresponding period
(Figure 1). Both parameters exhibited a descending trend over time.

The number of TAC C\textsubscript{0} measurements for the periods 0--3
months, 3--12 months and 12--24 months were 18 (IQR, 14--21), 30
(IQR,12--29), and 13 (IQR,7--21), respectively (Figure 1). Patients
received more extensive monitoring in the early post-transplantation
periods, especially in the first year.

Given that CYP3A5 is the primary enzyme responsible for TAC metabolism,
we sought to investigate its potential impact on TAC exposure; the
results are summarized in Table S1. Notably, significant difference was
observed only during the 0--3 months period between \emph{CYP3A5}
expressers and non-expressers (\emph{P} = 0.011 for TAC
C\textsubscript{0}, \emph{P} = 0.003 for TAC IPV).

\textbf{3.3 Correlation of TAC exposure across different time periods}

The trend-lines for TAC C\textsubscript{0} and IPV are depicted in
Figure 2, illustrating significant fluctuations in TAC concentration and
consistently high IPV values across all time periods. Furthermore, the
change trends of these parameters at different time points exhibit
similarity. TAC C\textsubscript{0} and IPV showed significant
correlation between 3--12 months and 12--24 months (TAC
C\textsubscript{0}: \emph{r} = 0.541, \emph{P} \textless{} 0.001; TAC
IPV: \emph{r} = 0.231, \emph{P} = 0.002), so we used the data during
3--12 months for all further analyses (\emph{n} = 224). The distribution
of the TAC C\textsubscript{0} and IPV during this time period are shown
in Figure S1. In the outcome analysis, TAC C\textsubscript{0} were
categorized into two groups: High C\textsubscript{0} (TAC
C\textsubscript{0} \textgreater{}= 8 ng/mL) and Low C\textsubscript{0}
(TAC C\textsubscript{0} \textless{} 8 ng/mL), while TAC IPV values were
classified as High IPV (TAC IPV \textgreater{}= 30\%) and Low IPV (TAC
IPV \textless{} 30\%) (Supplementary Figure 1).

\textbf{3.4 Occurrence and risk factors for clinical outcomes}

\textbf{3.4.1 DSA}

Of the 224 patients in this study, 18 (8\%) experienced DSA and the
median time for DSA incidence was 1088 days (IQR, 592--1677 days).
Kaplan-Meier analysis revealed that DSA incidence was 12.5\% and 5.6\%
in the Low and High C\textsubscript{0} group, respectively (\emph{P} =
0.025) (Figure 4A). Additionally, the High IPV group also demonstrated a
higher frequency of DSA compared to the Low IPV group, although this
difference did not reach statistical significance (11.1\% versus 4.7\%,
\emph{P} = 0.056) (Figure 4D). From the Cox proportional hazard model,
Low C\textsubscript{0} was independently associated with increased risk
for DSA (HR 2.820, 95\% CI 1.093--7.276,\emph{P} = 0.032) (Table 2).

\textbf{3.4.2 CLAD}

The overall incidence of CLAD in the study population following lung
transplantation was 19.6\%, with a median time to CLAD onset of 952 days
(IQR, 533--1480 days). TAC exposure was not associated with CLAD
incidence both in Kaplan-Meier analysis and Cox proportional hazard
model (Figure 4B and 4E, Table 2).

\textbf{3.4.3 Survival}

The survival rate of the study population was 79.5\% and the median
survival time was 1107 days (IQR, 622--1681 days). Kaplan-Meier analysis
showed a statistically significant difference in survival rates between
the High C\textsubscript{0} and Low C\textsubscript{0} group (\emph{P} =
0.025), as well as between the High IPV and Low IPV group (\emph{P} =
0.007) (Figure 4C and 4F). According to the Cox proportional hazard
model, Low C\textsubscript{0} (HR 2.220, 95\% CI 1.162--4.243, \emph{P}
= 0.016) and High IPV (HR 2.100, 95\% CI 1.120--3.937, \emph{P} = 0.021)
was associated with increased risk of mortality (Table 2).

\textbf{3.5 Impact of combined TAC exposure on clinical outcomes}

Since both TAC C\textsubscript{0} and IPV showed significance in outcome
analysis, we combined these 2 parameters together and further stratified
the study population into 3 groups: High C\textsubscript{0}/Low IPV
group, High C\textsubscript{0}/High IPV \& Low C\textsubscript{0}/Low
IPV group and Low C\textsubscript{0}/High IPV group (Figure 4). Notably,
patients from High C\textsubscript{0}/Low IPV group exhibited
statistically significant lower incidence of DSA (Figure 5A, Log
rank\emph{P} = 0.01) and superior survival rate compared with Low
C\textsubscript{0}/High IPV group (Figure 5C, Log rank \emph{P} =
0.001).

Table 3 shows the results of the Cox regression analysis of DSA and
survival according to TAC C\textsubscript{0}/IPV status. After adjusting
for age, sex, BMI, and factors with a \emph{P} value \textless{} 0.2 in
univariate analysis, the adjusted HR of Low C\textsubscript{0}/High IPV
for DSA was 4.534 (1.326--15.507) (\emph{P} = 0.016), while for survival
it was 4.205 (1.739--10.168) (\emph{P} = 0.001), surpassing the
predictive power of TAC C\textsubscript{0} or IPV alone.

\textbf{4 Discussion}

Our findings have revealed that a combination of Low C\textsubscript{0}
and High IPV of TAC, assessed between 3 and 12 months after
transplantation, was associated with an increased risk of donor-specific
antibodies (DSA), as well as mortality among lung transplant recipients.
Furthermore, we observed that the \emph{CYP3A5} genotype influenced TAC
C\textsubscript{0} and IPV during the early post-transplantation period;
however, no correlation was found with clinical outcomes (Supplementary
Figure 2).

We concluded that patients with an average C\textsubscript{0} below 8
ng/mL during 3--12 months are at higher risk for DSA and mortality.
Previous studies investigating the correlation between
C\textsubscript{0} and graft outcomes in lung transplantation have
yielded inconsistent findings. Ryu et al. reported an increased risk of
mortality with a C\textsubscript{0} below 10 ng/ mL within one month
post-transplantation, \textsuperscript{15} while Gallagher found a
negative association between mean TAC C\textsubscript{0} (median (IQR):
9.8 (8.56--10.75) ng/mL) between 6--12 months and
CLAD.\textsuperscript{7} Darley et al. reported a significantly higher
proportion of rejection biopsies (85.7\% versus 31.9\%) with
C\textsubscript{0} fell below their target range of 12--15 ng/mL within
the first three months after transplantation.\textsuperscript{21} The
discrepancies in lower limits of TAC C\textsubscript{0} may be
attributed to variations in target ranges employed across different
studies. In our center, where a substantial number of elderly patients
undergo transplantation and face high risk of infection resulting in
mortality, we have observed a significant association between
C\textsubscript{0} \textless{} 8 ng/mL and inferior outcomes, thereby
suggesting this lower limit remains acceptable. Meanwhile, higher TAC
concentration has been linked to increased drug toxicity such as acute
kidney injury, chronic kidney disease and post-transplant diabetes
mellitus; \textsuperscript{22, 23} however, limited studies exist to
assess the upper limit of TAC C\textsubscript{0} in lung transplant
recipients, thus further investigations are warranted.

In addition to routine C\textsubscript{0} monitoring, TAC IPV has
emerged as a novel marker for identifying transplant recipients at risk
for suboptimal clinical outcomes.\textsuperscript{24} Various
methodologies have been proposed to assess IPV, including coefficient of
variation (CV), standard deviation (SD) and time in therapeutic range
(TTR).\textsuperscript{25} In our study, we employed the most prevalent
parameter in solid organ transplantation, CV, and observed that patients
with CV \textgreater{}= 30\% during 3--12 months was associated with
increased risk of mortality. Meanwhile, current studies on evaluating
TAC IPV in lung transplantation used different methodologies, and
conclusions remains controversial.

Gallagher conducted a retrospective analysis of 110 lung transplant
recipients, using SD to characterize IPV. Their findings suggest that
TAC SD calculated during 6--12 months independently predicted the time
to development of CLAD and mortality. With each unit increase in SD,
there was a corresponding 46\% and 27\% increase in the risk of CLAD and
death, respectively. \textsuperscript{7} Ensor et al. conducted a
retrospective study involving 292 patients and reported that a 10\%
increase in TTR was significantly associated with reduced risk of acute
cellular rejection (ACR), CLAD and mortality at 1
year.\textsuperscript{9} In contrast, Kao et al analyzing TTR in 157
lung transplant patients during the first 6 months, did not find any
correlation between TTR and ACR. \textsuperscript{8}These studies
differed in their target ranges; Ensor and his colleagues employed a
narrower range of 12--15 ng/mL for 0--6 months followed by 10--12 ng/mL
for 6--12 months, while Kao used a range of 10--15 ng/mL throughout the
first year. Due to TAC's high variability, maintaining a strict
therapeutic range can be challenging; therefore, adopting a more liberal
range may allow more time within the therapeutic range without adverse
effect on ACR, leading to negative outcomes.

The majority of studies evaluating the impact of TAC exposure on
clinical outcomes have primary focused on the stable period, typically
defined as at least 3 months post-transplantation. During the early
post-transplant phase, patients experience clinical instability and
necessitate frequent dose adjustments of TAC. This results in highly
variable concentrations, which can introduce biases in statistical
analysis and complicate result interpretation. Nonetheless, efforts have
been made to investigate this phenomenon. Gallagher et al. found no
association between TAC SD within 0--6 months and CLAD or mortality.
Similarly, Evens et al. reported that high TAC variability within 0-3
months did not correlate with an increased acute rejection score at 12
months. In our study, we also observed no correlation between TAC IPV
during 0--3 months and DSA, CLAD, or mortality (data not shown).
Furthermore, there is limited literature exploring long-term TAC
exposure beyond 12 months after lung transplantation. Our data suggest
TAC exposure during 3--12 months predicted the developing trend of
exposure in the second year, which aligns with previous
study.\textsuperscript{7}

The average C\textsubscript{0} effectively reflects the levels over
specific time periods, while IPV captures fluctuations between high and
low levels, similar to accuracy and precision in analytical science.
Hence, a combination of C\textsubscript{0} and IPV may provide a more
comprehensive characterization of TAC exposure. Stefanovi\selectlanguage{polish}ć \selectlanguage{english}et al
enrolled 104 Caucasian kidney transplant patients, and found patients
with high IPV/low C\textsubscript{0}/D during 6--12 months had
significantly reduced graft survival compared to the other
combinations.\textsuperscript{16} Park et al further validated this
conclusion in a larger cohort with 1080 kidney transplant recipients, by
reporting higher incidences of death censored graft loss (DCGL),
biopsy-proven allograft rejection (BPAR) and overall graft loss in the
high IPV/low C/D group. \textsuperscript{17} Our study was the first
study in lung transplantation to investigate the combinational effect of
TAC C\textsubscript{0} and IPV, and we also observed a stronger
predictive power of Low C\textsubscript{0}/High IPV combination than TAC
C\textsubscript{0} or IPV alone.

The impact of \emph{CYP3A5} polymorphism on TAC metabolism has been
extensively studied; however, the definitive association
between\emph{CYP3A5} genotype and TAC IPV remains to be
established.\textsuperscript{26} Seiber et al reported each additional
loss-of-function allele (\emph{CYP3A5*3} , \emph{*6} and *7) reduced TAC
CV by 1.82\% in the first six months following kidney transplantation in
European Americans. \textsuperscript{18} On the other hand, studies
conducted between 6 and 12 months suggested no significant influence
of\emph{CYP3A5} genotype on TAC IPV. \textsuperscript{27, 28} Similarly,
we only observed a higher IPV in \emph{CYP3A5} expressers within the
first three months. Other factors such as noncompliance, drug-drug or
drug-food interactions may play a more prominent role in determining IPV
during the stable phase after transplantation.

There are several limitations in our study. Firstly, the study design
was single-center, retrospective and observational. Secondly, the sample
size is relatively small compared to previous research in kidney
transplantation. Thirdly, we did not exclude inpatient data in our
study. Lung transplant recipients usually face higher risk of infection
compared to other solid organ transplantation and have a high likelihood
of hospital readmission, particularly within the first year. To maintain
an adequate sample size, we included all measurements in our study.

In conclusion, the present study suggested using a combination of Low
C\textsubscript{0} (\textless{} 8 ng/mL) and High IPV
(\textgreater{}=30\%) of TAC calculated during 3--12 months after lung
transplantation may help predict adverse clinical outcomes. Monitoring
TAC C\textsubscript{0} and IPV in routine clinical practice is a
convenient tool that may assist in identifying patients at high risk for
inferior long-term outcomes.

\textbf{Acknowledgements}

We thank Prof. Wenhui Chen and her team from Department of Lung
Transplantation in China-Japan Friendship Hospital for their assistance
in conducting the study.

\textbf{Conflicts of interests}

There are no competing interests to declare.

\textbf{Funding}

The study was financed with National High Level Hospital Clinical
Research Funding (2022-NHLHCRF-PY-15), National Natural Science
Foundation Project (82273523), National High Level Hospital Clinical
Research Funding (2022-NHLHCRF-LX-03), National Key Research and
Development Program of China (2020YFC2005504), CAMS Innovation Fund for
Medical Science (2021-I2M-1-049) and Capital's Funds for Health
Improvement and Research (CFH 2020-1-2031).

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