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    Gut and Liver is an international journal of gastroenterology, focusing on the gastrointestinal tract, liver, biliary tree, pancreas, motility, and neurogastroenterology. Gut atnd Liver delivers up-to-date, authoritative papers on both clinical and research-based topics in gastroenterology. The Journal publishes original articles, case reports, brief communications, letters to the editor and invited review articles in the field of gastroenterology. The Journal is operated by internationally renowned editorial boards and designed to provide a global opportunity to promote academic developments in the field of gastroenterology and hepatology. +MORE

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Immune-Enhancing Treatment among Acute Necrotizing Pancreatitis Patients with Metabolic Abnormalities: A Post Hoc Analysis of a Randomized Clinical Trial

Xiaofei Huang1,2 , Wenjian Mao3 , Xingxing Hu1,2 , Fengxia Qin1,2,4 , Hui Zhao1,2 , Aiping Zhang1,2 , Xinyu Wang3 , Christian Stoppe5,6 , Dandan Zhou1,2 , Lu Ke3,7 , Haibin Ni1,2 , Chinese Acute Pancreatitis Clinical Trials Group (CAPCTG)

1Department of Emergency and Critical Care Medicine, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; 2Department of Emergency and Critical Care Medicine, Jiangsu Province Academy of Traditional Chinese Medicine, Nanjing, China; 3Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing, China; 4Department of Emergency and Critical Care Medicine, Nanjing Jiangning District Hospital of Traditional Chinese Medicine, Nanjing, China, 5Department of Anesthesiology, Intensive Care, Emergency and Pain Medicine, University Hospital Würzburg, Würzburg, Germany; 6Department of Cardiac Anesthesiology and Intensive Care Medicine, German Heart Center Charité Berlin, Berlin, Germany; 7National Institute of Healthcare Data Science, Nanjing University, Nanjing, China

Correspondence to: Haibin Ni
ORCID https://orcid.org/0000-0003-1726-7943
E-mail nhb_2002@126.com

Dandan Zhou
ORCID https://orcid.org/0000-0002-4041-5150
E-mail houdiane6@gmail.com

Xiaofei Huang and Wenjian Mao contributed equally to this work as first authors.

Received: August 15, 2023; Revised: October 8, 2023; Accepted: November 1, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Gut Liver.

Published online February 15, 2024

Copyright © Gut and Liver.

Background/Aims: Metabolic syndrome is common in patients with acute pancreatitis and its components have been reported to be associated with infectious complications. In this post hoc analysis, we aimed to evaluate whether metabolic abnormalities impact the effect of immune-enhancing thymosin alpha-1 (Tα1) therapy in acute necrotizing pancreatitis (ANP) patients.
Methods: All data were obtained from the database for a multicenter randomized clinical trial that evaluated the efficacy of Tα1 in ANP patients. Patients who discontinued the Tα1 treatment prematurely were excluded. The primary outcome was 90-day infected pancreatic necrosis (IPN) after randomization. Three post hoc subgroups were defined based on the presence of hyperglycemia, hypertriglyceridemia, or both at the time of randomization. In each subgroup, the correlation between Tα1 and 90-day IPN was assessed using the Cox proportional-hazards regression model. Multivariable propensity-score methods were used to control potential bias.
Results: Overall, 502 participants were included in this post hoc analysis (248 received Tα1 treatment and 254 received matching placebo treatment). Among them, 271 (54.0%) had hyperglycemia, 371 (73.9%) had hypertriglyceridemia and 229 (45.6%) had both. Tα1 therapy was associated with reduced incidence of IPN among patients with hyperglycemia (18.8% vs 29.7%: hazard ratio, 0.80; 95% confidence interval, 0.37 to 0.97; p=0.03), but not in the other subgroups. Additional multivariate regression models using three propensity-score methods yielded similar results.
Conclusions: Among ANP patients with hyperglycemia, immune-enhancing Tα1 treatment was associated with a reduced risk of IPN (ClinicalTrials.gov, Registry number: NCT02473406).

Keywords: Metabolic syndrome, Hyperglycemia, Acute necrotizing pancreatitis, Infection, Thymosin alpha1

Acute pancreatitis (AP) is one of the most common gastrointestinal diseases requiring emergency admission, and the prevalence is rising globally.1 Although mild for most patients, approximately 20% of them can develop severe AP, accompanied by complications such as extensive pancreatic necrosis, multiple organ failure, or/and infected pancreatic necrosis (IPN), commonly requiring intensive care unit admission.2 Among them, IPN is highly morbid and potentially lethal.3,4

Previous studies showed that metabolic syndrome was common in AP and its presence at the time of admission indicates an increased risk of moderately severe AP and severe AP.5,6 Hyperglycemia and hypertriglyceridemia are the most two common metabolic disorders in AP, and both of them may increase the risk of infection in AP.7-10 A possible explanation is that hyperglycemia can lead to functional damage to the innate immune system,11,12 and hypertriglyceridemia was also associated with immunosuppression.10 Moreover, hyperglycemia is thought to attenuate cytokine production, leukocyte recruitment, antibodies and complement effector, and pathogen recognition, leading to neutrophil, macrophage and natural killer cell dysfunction.12

In this regard, immune enhancement may have a role in treating AP patients with metabolic abnormalities. In the multicenter TRACE trial, immune-enhancing treatment with thymosin alpha-1 (Tα1) did not reduce the occurrence of IPN in predicted severe acute necrotizing pancreatitis (ANP) patients.13 However, patients with impaired immunity due to metabolic abnormalities may respond differently to the treatment.

This post hoc study aimed to assess whether metabolic abnormalities impact the responses to immune-enhancing Tα1 treatment in patients with ANP. The results of this study may pave the way for future trials.

1. Study design

This study is a post hoc analysis using data obtained from the TRACE trial. The TRACE trial is a multicenter, double-blind, randomized, placebo-controlled trial, and the protocol and trial results have been published recently.13,14 The original trial protocol complied with the ethical guidelines of the Declaration of Helsinki and was approved by the Ethics Committee of Jinling Hospital (ethical number: 2015NZKY-004-02) and by the local ethics committee of all the study centers. At each site, informed consent was obtained from the patients or their next of kin before randomization. This study adheres to the most recent STROBE statement,15 Supplemental Digital Content 1, and reports in accordance with the STROCSS guideline, Supplemental Digital Content 2.16

2. Study population

From March 18, 2017, to December 10, 2020, patients with ANP who were admitted within 7 days of the onset of abdominal pain were recruited. The inclusion criteria were: (1) AP diagnosed by the Revised Atlanta Classification criteria;3 (2) ≤7-day of AP onset; (3) age range between 18 and 70 years; (4) APACHE II ≥8; (5) Balthazar computed tomography score ≥5;17 and (6) obtained informed written consent. The exclusion criteria were: (1) AP during pregnancy; (2) with a diagnosis of chronic pancreatitis and/or malignancy-related AP; (3) receiving early intervention or surgery prior to hospitalization; (4) with a history of serious cardiovascular, respiratory, renal, or hepatic disease; or (5) with preexisting immune disorders. In the original trial, patients were randomly assigned to receive a subcutaneous injection of Tα1 1.6 mg every 12 hours for the first 7 days, followed by 1.6 mg once a day for the next 7 days, or a matching placebo (normal saline) during the same period. The trial drug (Tα1/placebo) was administered for a maximum of 14 days, or until the patient was discharged from the hospital or died, whichever came first. All TRACE trial participants were included in this post hoc analysis. Patients who discontinued Ta1 treatment prematurely and received less than 14 doses of Tα1 in the intervention group were excluded.

3. Data collection and definition

The baseline laboratory indexes reflecting blood glucose metabolism abnormalities or hyperglycemic state were retrospectively collected through electronic hospital records, including blood glucose, and glycosylated hemoglobin (HbA1c). Beyond these, all the data required in this analysis were obtained from the database of the TRACE trial.

Regarding the diagnostic criteria of metabolic abnormalities, patients who had preexisting diabetes mellitus had baseline blood glucose >11.0 mmol/L (199 mg/dL) (highest value on the day of randomization) or had HbA1c ≥6.5% measured during the index admission, were defined as hyperglycemia.18,19 Hypertriglyceridemia was defined as baseline serum triglycerides >1.7 mmol/L (150 mg/dL) (highest value on the day of randomization).20 Severe hypertriglyceridemia was defined as baseline serum triglycerides >5.65 mmol/L (500 mg/dL).21 Hypertriglyceridemia-induced AP was defined as serum peak triglyceride levels of 11.3 mmol/L (1,000 mg/dL) or 5.65–11.3 mmol/L (500–1,000 mg/dL) and the absence of other causes of AP.22 The definitions of other etiologies have been described in the recent guidelines.23-25

4. Study outcomes

The incidence of IPN within 90 days of randomization was the primary outcome of this study. IPN was diagnosed based on one or more of the following criteria: on computed tomography, there were gas bubbles within pancreatic and/or peripancreatic necrosis; a positive culture was obtained from pancreatic and/or peripancreatic necrosis via fine-needle aspiration, drainage, or necrosectomy.3 The secondary clinical outcomes included new onset organ failure, new requirements of invasive interventions, and length of stay (in intensive care unit and hospital) during the index hospitalization, and 90-day mortality. Secondary laboratory outcomes included C-reactive protein, lymphocyte count, and monocyte human leukocyte antigen-DR, on day-7 and day-14 after randomization. The Revised Atlanta Classification guideline was used to define organ failure.3

5. Statistical analysis

According to their normality, continuous data are presented as means and standard deviations or medians and interquartile ranges. The Shapiro-Wilk test was used to determine the data's normality. The Mann-Whitney U test or the Student t-test was used to analyze the continuous variables. The Fisher exact test or chi-square test was used to compare categorical data between two groups, which were expressed as frequencies and percentages (%).

The three post hoc subgroups were differentiated based on the presence or absence of hyperglycemia, hypertriglyceridemia, or a combination of both at baseline (at the time of randomization). The subgroup×treatment interaction effect was examined by the Cox proportional-hazards regression (CPHR) model that controlled for Tα1 treatment and subgroup main effects. The role of Tα1 in reducing 90-day IPN in the subgroup was then assessed using the Kaplan-Meier method and compared using the log-rank test. The multivariate CPHR model was utilized to comparatively analyze the differences (variations) in the primary outcome with potential bias (p<0.2 between two groups) as well as three a priori variables (age, sex, and etiology) as covariates. Finally, we included the following factors: age, sex, etiology of AP and APACHE II score at randomization. The hazard ratios (HRs) and their 95% confidence intervals (CIs) were derived. Propensity-score techniques were utilized to reduce the confounding effects to account for the administration of Tα1 in a nonrandomized manner. Using the same covariates (age, sex, etiology of AP and APACHE II score at admission) as the Cox regression model, the multivariate logistic regression model was utilized to estimate the individual propensities for receipt of Tα1 treatment. The multivariate CPHR analyses were carried out using three propensity-score methods: propensity-score matching (PSM), inverse probability weighting (IPTW), and adding the propensity score as an extra covariate. In the PSM analysis, the matched control sample was generated using the nearest-neighbor method. The weights calculated from the propensity score were used for the IPTW weighting of the multivariate CPHR. The baseline characteristic balances between the Tα1 and placebo group after PSM and IPTW were re-assessed by the standard mean difference (Supplementary Fig. 1).

Unless otherwise stated, statistical tests were two-sided, with p<0.05 deemed significant. The SPSS 26.0 (IBM Corp., Armonk, NY, USA) and R 4.1.1 (R Foundation for Statistical Computing, Vienna, Austria) tools were employed for executing all of the statistical analyses.

1. Baseline characteristics

Overall, 508 participants were randomized in the original TRACE trial. After six patients in the intervention group were excluded due to premature discontinuation of Tα1 treatment, 502 patients participated in this study (248 received Tα1 treatment and 254 received the matching placebo). Among the study subjects, 271 (54.2%) had hyperglycemia, 371 (73.9%) had hypertriglyceridemia, and 229 (45.6%) had combined hyperglycemia and hypertriglyceridemia (Table 1). Among the 271 hyperglycemia patients, 90 (33.2%) patients had a previous history of diabetes, 95 (35.1%) had HbA1c≥6.5%, 234 (86.3%) had blood glucose >11.0 mmol/L on the day of randomization and 123 (45.4%) of the patients were diagnosed by blood glucose alone.

Table 1. Baseline Characteristics of the Study Subjects

CharacteristicTotal (n=502)Tα1 group (n=248)Placebo group (n=254)p-value
Age, yr43.0 (35.0–53.0)43.0 (34.3–52.8)44.0 (35.0–54.0)0.48
Sex0.66
Female187 (37.3)90 (36.3)97 (38.2)
Male315 (62.7)158 (63.7)157 (61.8)
Body mass index, kg/m226.3 (24.0–28.4)26.2 (24.0–28.2)26.5 (24.2–29.0)0.45
APACHE II score10.0 (8.0–13.0)10.0 (8.0–13.0)10.0 (8.0–13.0)0.98
SOFA score4.0 (2.0–6.0)4.0 (2.0–6.0)4.0 (2.0–6.0)0.80
Etiologies0.99
Alcoholic31 (6.2)16 (6.5)15 (5.9)
Biliary199 (39.6)99 (39.9)100 (39.4)
Idiopathic24 (4.8)12 (4.8)12 (4.7)
Hypertriglyceridemia248 (49.4)121 (48.8)127 (50.0)
The extent of pancreatic necrosis0.28
≤50%439 (62.2)216 (64.9)223 (59.4)
>50%63 (12.5)32 (12.9)31 (12.2)
The interval between onset and randomization, day4.0 (2.4–6.0)4.0 (2.0–6.0)4.0 (2.7–6.0)0.92
Laboratory indexes
C-reactive protein, g/L164.7 (99.0–236.3)168.9 (94.1–236.5)160.6 (105.5–236.4)0.93
Lymphocyte count, ×109/L0.9 (0.6–1.2)0.9 (0.6–1.2)0.9 (0.7–1.2)0.31
Metabolic abnormalities
Hyperglycemia271 (54.0)133 (53.6)138 (54.3)1.00
Hypertriglyceridemia371 (73.9)184 (74.2)187 (73.6)1.00
Severe hypertriglyceridemia178 (35.5)85 (34.3)93 (36.6)1.00
Combined hyperglycemia and hypertriglyceridemia229 (45.6)116 (46.8)113 (44.5)1.00

Data are presented as median (interquartile range) or number (%).

Tα1, thymosin alpha 1; APACHE II, Acute Physiology and Chronic Health Evaluation II, which ranges from 0 to 71, with higher scores indicating more severe disease; SOFA, Sequential Organ Failure Assessment, the score for which ranges from 0 to 24; a higher scores indicates more severe organ failure.

p>0.05 for the comparison between the groups for all characteristics.



2. Results of subgroup analysis

On trial day 90 after randomization, 55 (22.2%) patients who received Tα1 developed IPN, while 65 (25.6%) patients who received placebo did so (Supplementary Fig. 2). The interaction between baseline metabolic abnormalities and the efficacy of treatment was examined further by analyzing four subgroups: patients with hyperglycemia, with hypertriglyceridemia, with both, or with severe hypertriglyceridemia. The impact of hyperglycemia on the efficacy of Tα1 treatment was the most significant (p for interaction=0.03) (Fig. 1).

Figure 1.Subgroup analysis of the risk of 90-day infected pancreatic necrosis. A risk difference of less than 1 indicates better results for the thymosin alpha-1 (Tα1) group.
HR, hazard ratio; CI, confidence interval.

3. Primary outcome and secondary outcomes

Among the 271 patients with hyperglycemia, 133 received Tα1 and 138 received placebo. The baseline characteristics of the study subjects are shown in Supplementary Table 1. Overall, 24 patients (18.0%) developed IPN in the Tα1 group, significantly lower than the placebo group (n=41, 29.7%) (HR, 0.57; 95% CI, 0.34 to 0.94; p=0.03). Among patients with hypertriglyceridemia or with combined hypertriglyceridemia and hyperglycemia, the use of Tα1 did not lead to a difference in the incidence of IPN (Fig. 1).

The cumulative incidence of IPN within 90 days of randomization is shown in Fig. 2. Among ANP patients with hyperglycemia, the likelihood of developing IPN was significantly lower in the Tα1 group compared to the placebo groups (log-rank p=0.024). The results for those without hyperglycemia are shown in Supplementary Fig. 3. The results of multivariate Cox regression analysis for 90-day IPN in hyperglycemia patients confirmed that Tα1 was an independent protective factor for the reduction of IPN after adjustment for age, sex, etiology, and APACHE II score at randomization (HR, 0.59; 95% CI, 0.35 to 0.99; p=0.047) (Table 2).

Figure 2.The Kaplan-Meier curves for the cumulative incidence of infected pancreatic necrosis from randomization to day 90 in patients with hyperglycemia.
Tα1, thymosin alpha-1.

Table 2. Multivariate Cox Regression Analysis for 90-Day Infected Pancreatic Necrosis Based on the Cox Proportional-Hazards Model in Patients with Hyperglycemia

ParameterHR (95% CI)p-value
Age1.01 (0.99–1.03)0.25
Male sex1.44 (0.82–2.55)0.21
Etiology
BiliaryReference
Hyperlipidemic0.74 (0.40–1.35)0.32
Alcohol1.65 (0.58–4.71)0.35
Others0.26 (0.03–1.92)0.18
APACHE II score1.05 (1.01–1.09)0.01
Treatment
PlaceboReference
Tα10.59 (0.35–0.99)0.047

HR, hazard ratio; CI, confidence interval; APACHE II, Acute Physiology and Chronic Health Evaluation II, the score for which ranges from 0 to 71; a high score indicates more severe disease; Tα1, thymosin alpha-1.



For sensitivity analysis, three propensity-score methods were used. Overall, there was also significant association between Tα1 treatment and the reduced primary endpoint (HR 0.59, 95% CI 0.41 to 0.85 for the IPTW method; HR 0.58, 95% CI 0.35 to 0.99 for the PSM method; HR 0.55, 95% CI 0.33 to 0.93 for the method adjusted for propensity score) in each propensity-score method (Table 3). The baseline data of the two groups before and after PSM and IPTW are shown in Supplementary Table 2 and Supplementary Fig. 1.

Table 3. Associations between Early Tα1 Treatment and the End Point of 90-Day IPN in the Crude Analysis, Multivariable Analysis, and Propensity-Score Analyses

Analysis90-Day IPN, HR (95% CI)
No. of events/no. of patients at risk (%)
Tα124/133 (18.0)
Placebo41/138 (29.7)
Crude analysis0.57 (0.34–0.94)
Multivariable analysis*0.59 (0.35–0.99)
Propensity-score analyses
With inverse probability weighting0.59 (0.41–0.85)
With matching0.58 (0.35–0.99)
Adjusted for propensity score§0.55 (0.33–0.93)

Tα1, thymosin alpha-1; IPN, infected pancreatic necrosis; HR, hazard ratio; CI, confidence interval.

*The primary analysis with a hazard ratio from the multivariable Cox proportional-hazards model, with additional adjustment for age, sex, etiology and APACHE II score at randomization. The analysis included all 271 patients; The hazard ratio from the multivariable Cox proportional-hazards model with the same covariates with inverse probability weighting according to the propensity score. The analysis included all the patients with their respective weight; Shown is the hazard ratio from a multivariable Cox proportional-hazards model with the same covariates among the matched patients according to the propensity score. The analysis included 248 patients (124 who received Tα1 and 124 who received placebo); §The hazard ratio from a multivariable Cox proportional-hazards model with the same covariates, with additional adjustment for the propensity score. The analysis included all the 271 patients.



Regarding the secondary outcomes, no significant difference was observed between patients who received Tα1 or placebo among the 271 patients with hyperglycemia (Table 4). There was also no difference in C-reactive protein level or the lymphocyte count at day 7 or day 14 after randomization or the monocyte human leukocyte antigen-DR level at enrolment, day 7, or day 14 after randomization (Supplementary Table 3).

Table 4. Secondary Clinical Outcomes in Patients with Hyperglycemia

Secondary clinical outcomeTα1 group (n=133)Placebo group (n=138)p-value
New onset organ failure
Respiratory3 (2.3)7 (5.1)0.22
Renal8 (6.0)3 (2.2)0.13
Cyclic6 (4.5)11 (8.0)0.24
Invasive interventions18 (13.5)22 (15.9)0.58
Length of hospital stay, day15 (11–24)17.5 (9–25.3)0.70
Length of ICU stay, day9 (5–16.5)10 (5.8–19)0.37
90-Day mortality11 (8.3)16 (11.6)0.36

Data are presented as number (%) or median (interquartile range).

Tα1, thymosin alpha-1; ICU, intensive care unit.


In this post hoc analysis, we found that metabolic abnormalities are common in predicted severe ANP patients. The subgroup analysis suggested that predicted severe ANP patients with hyperglycemia may benefit from immune-enhancing Tα1 treatment by reducing the incidence of IPN.

Metabolic syndrome, defined by the presence of a cluster of metabolic abnormalities that includes hyperglycemia, central obesity, hypertriglyceridemia, hypertension, and low high-density lipoprotein cholesterol level, has been identified as a common clinical finding and is associated with increased mortality and morbidity in AP.5 A previous study revealed that more than 60% of AP patients had at least one major metabolic comorbidity, which was similar to our findings (53.9% hyperglycemia and 73.9% hypertriglyceridemia).26 Among the components of metabolic syndrome, hyperglycemia and hypertriglyceridemia are the two most common metabolic abnormalities, which have frequently been reported to be associated with worse prognosis in AP.8,9,27 Furthermore, both hyperglycemia and hypertriglyceridemia have been linked to impaired immune function,10,12 potentially increasing the incidence of infection. However, in our study, only patients with hyperglycemia responded differently to the Tα1 therapy.

The pharmacological characteristics of Tα1 may explain these findings: hyperglycemia is thought to impair a wide range of functions in neutrophils, macrophages and natural killer cells, including impaired migration, decreased membrane fluidity, reduced phagocytosis and intracellular killing capacity, and altered chemotaxis, resulting in increased susceptibility towards infections and increased severity of infections.11,28-30 The specific mechanism of hyperglycemia's effect on the innate immune response is still unknown, but it may involve activating protein kinase C or altering the tertiary structure of complement via direct glycosylation.28 Tα1, which is thought to affect dendritic cells and T helper cells, stimulates innate immunity, including neutrophils, natural killer cells, and macrophages.31 Given these well-known pharmacological effects, we hypothesized that Tα1 could reduce the occurrence of IPN by repairing the innate immune damage caused by hyperglycemia. To clarify this, a future prospective study is required.

On the other hand, we did not observe different treatment responses in patients with hypertriglyceridemia or combined disorders. Current evidence suggests that increased fatty acid levels can cause inflammation and elevated cytokines, worsening kidney, lung, and shock injury, eventually leading to multi-system organ failure and increased mortality.32 Though hypertriglyceridemia was reported to affect the circulating neutrophil subpopulation,10 whether it is associated with immune dysfunction was poorly studied. Moreover, another possible explanation may be simply that the sample size of patients with hypertriglyceridemia was underpowered.

Attempts have been made in boosting the immune system in patients with diabetes, including liposomal glutathione,33 mechanistic target of rapamycin inhibitor,34 and microbiological and immunological enteral nutrition.35 But none of them targeted the innate immune system directly. Recently, a network enrichment analysis revealed that Tα1 also regulates cellular metabolic processes, implying that Tα1 treatment may have new translational implications in pathological conditions such as diabetes.36 Furthermore, a previous experimental study found that co-administration of Tα1 protects against streptozotocin-induced pancreatic damage and diabetes, and that part of the protection may be achieved by increasing pancreatic antioxidative capability.37 Given these known pieces of evidence, our findings offer a promising direction for further investigation and point to the potential of immune-enhancing Tα1 therapy in the treatment of diabetes.

This subgroup analysis has several strengths: (1) the subgroup variables (HbA1c and blood glucose) were measured at the baseline, and the definitions of hyperglycemia were from previously published studies;18,19 (2) the comparison was undertaken within a single RCT conducted at several sites, which increases the generalizability of the received findings; (3) the use of three different propensity-score methods, reflecting the robustness of these findings; (4) the findings have a plausible pharmacologic explanation.

Some limitations need to be also acknowledged. (1) the retrospective nature of this post hoc analysis may bring in some inevitable bias; (2) there is a lack of other laboratory parameters reflecting the amelioration of immune suppression after Tα1 treatment; (3) hypertriglyceridemia-induced AP accounts for approximately 50% of the study subjects and alcohol-induced AP only 6%, which differs significantly from cohorts reported in Western countries.38,39 Possible explanations may include changes in dietary habits in China over the last few decades,40 genetic factors,41,42 and different alcohol drinking habits; and (4) the definition of hyperglycemia used in this study is a composite one, and approximately 50% of hyperglycemia patients were diagnosed solely based on random blood glucose levels, which can be impacted by patients' fasting status, the use of dextrose fluid, and glycemic control treatments. However, we can not control for these potential confounders since the original trial did not collect the corresponding data.

In conclusion, Tα1 treatment was associated with reduced IPN incidence in ANP patients with hyperglycemia. To confirm our findings, a future randomized trial with sufficient power is required.

We acknowledge the contribution of the members of the TRACE trial study group: Lu Ke, Jing Zhou, Wenjian Mao, Wendi Jiang, He Zhang, Jiajia Lin, Mengjie Lu, Yan Chen, Baiqiang Li, Zhihui Tong, Yuxiu Liu, Weiqin Li, Jinling Hospital. Tao Chen, Liverpool University. Fang Shao, Nanjing Medical University. Nonghua Lv, Yin Zhu, Liang Xia, Wenhua He, Zhenping Chen, The First Affiliated Hospital of Nanchang University. Xinting Pan, Qingyun Zhu, Youdong Wan, The Affiliated Hospital of Qingdao University. Hong Mei, Kang Li, Miao Chen, The Affiliated Hospital of Zunyi Medical University. Chengjian He, Hongyi Yao, Zigui Zhu, Nanhua Hospital. Weili Gu, Affiliated Hospital 2 of Nantong University. Weihua Lu, Jingyi Wu, Feng Zhou, The First Affiliated Hospital of Wannan Medical College. Shumin Tu, Long Fu, Bing Xue, Shangqiu First People's Hospital. Haibin Ni, Xiaofei Huang, Dandan Zhou, Jiangsu Provincial Hospital of Integrated Chinese and Western Medicine. Guoxiu Zhang, Lening Ren, Dahuan Li, The First Affiliated Hospital and College of Clinical Medicine of Henan University of Science and Technology. Xiangyang Zhao, Wei Zhao, Xiaomei Chen, Qilu Hospital of Shandong University. Junli Sun, Keke Xin, Luoyang Central Hospital. Weiwei Chen, Qingcheng Xu, Clinical Medical College of Yangzhou University. Jingchun Song, Qingbo Zeng, 94th Hospital of PLA. Min Shao, Dongsheng Zhao, The First Affiliated Hospital of Anhui Medical University. Jianfeng Tu, Hongguo Yang, Zhejiang Provincial People's Hospital.

Study concept and design: X.H., D.Z., L.K., H.N. Data acquisition: W.M., X.H., F.Q., H.Z., A.Z., X.W. Data analysis and interpretation: W.M. Drafting of the manuscript: X.H., W.M., L.K. Critical revision of the manuscript for important intellectual content: C.S., L.K., H.N. Statistical analysis: W.M. Administrative, technical, or material support; study supervision: D.Z., L.K., H.N. Approval of final manuscript: all authors.

Deidentified individual participant data are available indefinitely in the electronic database. Data can be accessed through capctg.medbit.cn with the approval of the authors. Request for data can be made to the corresponding author (ctgchina@medbit.cn) and will be discussed during a meeting of the Chinese Acute Pancreatitis Clinical Trials Group (CAPCTG).

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Article

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Gut and Liver

Published online February 15, 2024

Copyright © Gut and Liver.

Immune-Enhancing Treatment among Acute Necrotizing Pancreatitis Patients with Metabolic Abnormalities: A Post Hoc Analysis of a Randomized Clinical Trial

Xiaofei Huang1,2 , Wenjian Mao3 , Xingxing Hu1,2 , Fengxia Qin1,2,4 , Hui Zhao1,2 , Aiping Zhang1,2 , Xinyu Wang3 , Christian Stoppe5,6 , Dandan Zhou1,2 , Lu Ke3,7 , Haibin Ni1,2 , Chinese Acute Pancreatitis Clinical Trials Group (CAPCTG)

1Department of Emergency and Critical Care Medicine, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; 2Department of Emergency and Critical Care Medicine, Jiangsu Province Academy of Traditional Chinese Medicine, Nanjing, China; 3Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing, China; 4Department of Emergency and Critical Care Medicine, Nanjing Jiangning District Hospital of Traditional Chinese Medicine, Nanjing, China, 5Department of Anesthesiology, Intensive Care, Emergency and Pain Medicine, University Hospital Würzburg, Würzburg, Germany; 6Department of Cardiac Anesthesiology and Intensive Care Medicine, German Heart Center Charité Berlin, Berlin, Germany; 7National Institute of Healthcare Data Science, Nanjing University, Nanjing, China

Correspondence to:Haibin Ni
ORCID https://orcid.org/0000-0003-1726-7943
E-mail nhb_2002@126.com

Dandan Zhou
ORCID https://orcid.org/0000-0002-4041-5150
E-mail houdiane6@gmail.com

Xiaofei Huang and Wenjian Mao contributed equally to this work as first authors.

Received: August 15, 2023; Revised: October 8, 2023; Accepted: November 1, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background/Aims: Metabolic syndrome is common in patients with acute pancreatitis and its components have been reported to be associated with infectious complications. In this post hoc analysis, we aimed to evaluate whether metabolic abnormalities impact the effect of immune-enhancing thymosin alpha-1 (Tα1) therapy in acute necrotizing pancreatitis (ANP) patients.
Methods: All data were obtained from the database for a multicenter randomized clinical trial that evaluated the efficacy of Tα1 in ANP patients. Patients who discontinued the Tα1 treatment prematurely were excluded. The primary outcome was 90-day infected pancreatic necrosis (IPN) after randomization. Three post hoc subgroups were defined based on the presence of hyperglycemia, hypertriglyceridemia, or both at the time of randomization. In each subgroup, the correlation between Tα1 and 90-day IPN was assessed using the Cox proportional-hazards regression model. Multivariable propensity-score methods were used to control potential bias.
Results: Overall, 502 participants were included in this post hoc analysis (248 received Tα1 treatment and 254 received matching placebo treatment). Among them, 271 (54.0%) had hyperglycemia, 371 (73.9%) had hypertriglyceridemia and 229 (45.6%) had both. Tα1 therapy was associated with reduced incidence of IPN among patients with hyperglycemia (18.8% vs 29.7%: hazard ratio, 0.80; 95% confidence interval, 0.37 to 0.97; p=0.03), but not in the other subgroups. Additional multivariate regression models using three propensity-score methods yielded similar results.
Conclusions: Among ANP patients with hyperglycemia, immune-enhancing Tα1 treatment was associated with a reduced risk of IPN (ClinicalTrials.gov, Registry number: NCT02473406).

Keywords: Metabolic syndrome, Hyperglycemia, Acute necrotizing pancreatitis, Infection, Thymosin alpha1

INTRODUCTION

Acute pancreatitis (AP) is one of the most common gastrointestinal diseases requiring emergency admission, and the prevalence is rising globally.1 Although mild for most patients, approximately 20% of them can develop severe AP, accompanied by complications such as extensive pancreatic necrosis, multiple organ failure, or/and infected pancreatic necrosis (IPN), commonly requiring intensive care unit admission.2 Among them, IPN is highly morbid and potentially lethal.3,4

Previous studies showed that metabolic syndrome was common in AP and its presence at the time of admission indicates an increased risk of moderately severe AP and severe AP.5,6 Hyperglycemia and hypertriglyceridemia are the most two common metabolic disorders in AP, and both of them may increase the risk of infection in AP.7-10 A possible explanation is that hyperglycemia can lead to functional damage to the innate immune system,11,12 and hypertriglyceridemia was also associated with immunosuppression.10 Moreover, hyperglycemia is thought to attenuate cytokine production, leukocyte recruitment, antibodies and complement effector, and pathogen recognition, leading to neutrophil, macrophage and natural killer cell dysfunction.12

In this regard, immune enhancement may have a role in treating AP patients with metabolic abnormalities. In the multicenter TRACE trial, immune-enhancing treatment with thymosin alpha-1 (Tα1) did not reduce the occurrence of IPN in predicted severe acute necrotizing pancreatitis (ANP) patients.13 However, patients with impaired immunity due to metabolic abnormalities may respond differently to the treatment.

This post hoc study aimed to assess whether metabolic abnormalities impact the responses to immune-enhancing Tα1 treatment in patients with ANP. The results of this study may pave the way for future trials.

MATERIALS AND METHODS

1. Study design

This study is a post hoc analysis using data obtained from the TRACE trial. The TRACE trial is a multicenter, double-blind, randomized, placebo-controlled trial, and the protocol and trial results have been published recently.13,14 The original trial protocol complied with the ethical guidelines of the Declaration of Helsinki and was approved by the Ethics Committee of Jinling Hospital (ethical number: 2015NZKY-004-02) and by the local ethics committee of all the study centers. At each site, informed consent was obtained from the patients or their next of kin before randomization. This study adheres to the most recent STROBE statement,15 Supplemental Digital Content 1, and reports in accordance with the STROCSS guideline, Supplemental Digital Content 2.16

2. Study population

From March 18, 2017, to December 10, 2020, patients with ANP who were admitted within 7 days of the onset of abdominal pain were recruited. The inclusion criteria were: (1) AP diagnosed by the Revised Atlanta Classification criteria;3 (2) ≤7-day of AP onset; (3) age range between 18 and 70 years; (4) APACHE II ≥8; (5) Balthazar computed tomography score ≥5;17 and (6) obtained informed written consent. The exclusion criteria were: (1) AP during pregnancy; (2) with a diagnosis of chronic pancreatitis and/or malignancy-related AP; (3) receiving early intervention or surgery prior to hospitalization; (4) with a history of serious cardiovascular, respiratory, renal, or hepatic disease; or (5) with preexisting immune disorders. In the original trial, patients were randomly assigned to receive a subcutaneous injection of Tα1 1.6 mg every 12 hours for the first 7 days, followed by 1.6 mg once a day for the next 7 days, or a matching placebo (normal saline) during the same period. The trial drug (Tα1/placebo) was administered for a maximum of 14 days, or until the patient was discharged from the hospital or died, whichever came first. All TRACE trial participants were included in this post hoc analysis. Patients who discontinued Ta1 treatment prematurely and received less than 14 doses of Tα1 in the intervention group were excluded.

3. Data collection and definition

The baseline laboratory indexes reflecting blood glucose metabolism abnormalities or hyperglycemic state were retrospectively collected through electronic hospital records, including blood glucose, and glycosylated hemoglobin (HbA1c). Beyond these, all the data required in this analysis were obtained from the database of the TRACE trial.

Regarding the diagnostic criteria of metabolic abnormalities, patients who had preexisting diabetes mellitus had baseline blood glucose >11.0 mmol/L (199 mg/dL) (highest value on the day of randomization) or had HbA1c ≥6.5% measured during the index admission, were defined as hyperglycemia.18,19 Hypertriglyceridemia was defined as baseline serum triglycerides >1.7 mmol/L (150 mg/dL) (highest value on the day of randomization).20 Severe hypertriglyceridemia was defined as baseline serum triglycerides >5.65 mmol/L (500 mg/dL).21 Hypertriglyceridemia-induced AP was defined as serum peak triglyceride levels of 11.3 mmol/L (1,000 mg/dL) or 5.65–11.3 mmol/L (500–1,000 mg/dL) and the absence of other causes of AP.22 The definitions of other etiologies have been described in the recent guidelines.23-25

4. Study outcomes

The incidence of IPN within 90 days of randomization was the primary outcome of this study. IPN was diagnosed based on one or more of the following criteria: on computed tomography, there were gas bubbles within pancreatic and/or peripancreatic necrosis; a positive culture was obtained from pancreatic and/or peripancreatic necrosis via fine-needle aspiration, drainage, or necrosectomy.3 The secondary clinical outcomes included new onset organ failure, new requirements of invasive interventions, and length of stay (in intensive care unit and hospital) during the index hospitalization, and 90-day mortality. Secondary laboratory outcomes included C-reactive protein, lymphocyte count, and monocyte human leukocyte antigen-DR, on day-7 and day-14 after randomization. The Revised Atlanta Classification guideline was used to define organ failure.3

5. Statistical analysis

According to their normality, continuous data are presented as means and standard deviations or medians and interquartile ranges. The Shapiro-Wilk test was used to determine the data's normality. The Mann-Whitney U test or the Student t-test was used to analyze the continuous variables. The Fisher exact test or chi-square test was used to compare categorical data between two groups, which were expressed as frequencies and percentages (%).

The three post hoc subgroups were differentiated based on the presence or absence of hyperglycemia, hypertriglyceridemia, or a combination of both at baseline (at the time of randomization). The subgroup×treatment interaction effect was examined by the Cox proportional-hazards regression (CPHR) model that controlled for Tα1 treatment and subgroup main effects. The role of Tα1 in reducing 90-day IPN in the subgroup was then assessed using the Kaplan-Meier method and compared using the log-rank test. The multivariate CPHR model was utilized to comparatively analyze the differences (variations) in the primary outcome with potential bias (p<0.2 between two groups) as well as three a priori variables (age, sex, and etiology) as covariates. Finally, we included the following factors: age, sex, etiology of AP and APACHE II score at randomization. The hazard ratios (HRs) and their 95% confidence intervals (CIs) were derived. Propensity-score techniques were utilized to reduce the confounding effects to account for the administration of Tα1 in a nonrandomized manner. Using the same covariates (age, sex, etiology of AP and APACHE II score at admission) as the Cox regression model, the multivariate logistic regression model was utilized to estimate the individual propensities for receipt of Tα1 treatment. The multivariate CPHR analyses were carried out using three propensity-score methods: propensity-score matching (PSM), inverse probability weighting (IPTW), and adding the propensity score as an extra covariate. In the PSM analysis, the matched control sample was generated using the nearest-neighbor method. The weights calculated from the propensity score were used for the IPTW weighting of the multivariate CPHR. The baseline characteristic balances between the Tα1 and placebo group after PSM and IPTW were re-assessed by the standard mean difference (Supplementary Fig. 1).

Unless otherwise stated, statistical tests were two-sided, with p<0.05 deemed significant. The SPSS 26.0 (IBM Corp., Armonk, NY, USA) and R 4.1.1 (R Foundation for Statistical Computing, Vienna, Austria) tools were employed for executing all of the statistical analyses.

RESULTS

1. Baseline characteristics

Overall, 508 participants were randomized in the original TRACE trial. After six patients in the intervention group were excluded due to premature discontinuation of Tα1 treatment, 502 patients participated in this study (248 received Tα1 treatment and 254 received the matching placebo). Among the study subjects, 271 (54.2%) had hyperglycemia, 371 (73.9%) had hypertriglyceridemia, and 229 (45.6%) had combined hyperglycemia and hypertriglyceridemia (Table 1). Among the 271 hyperglycemia patients, 90 (33.2%) patients had a previous history of diabetes, 95 (35.1%) had HbA1c≥6.5%, 234 (86.3%) had blood glucose >11.0 mmol/L on the day of randomization and 123 (45.4%) of the patients were diagnosed by blood glucose alone.

Table 1 . Baseline Characteristics of the Study Subjects.

CharacteristicTotal (n=502)Tα1 group (n=248)Placebo group (n=254)p-value
Age, yr43.0 (35.0–53.0)43.0 (34.3–52.8)44.0 (35.0–54.0)0.48
Sex0.66
Female187 (37.3)90 (36.3)97 (38.2)
Male315 (62.7)158 (63.7)157 (61.8)
Body mass index, kg/m226.3 (24.0–28.4)26.2 (24.0–28.2)26.5 (24.2–29.0)0.45
APACHE II score10.0 (8.0–13.0)10.0 (8.0–13.0)10.0 (8.0–13.0)0.98
SOFA score4.0 (2.0–6.0)4.0 (2.0–6.0)4.0 (2.0–6.0)0.80
Etiologies0.99
Alcoholic31 (6.2)16 (6.5)15 (5.9)
Biliary199 (39.6)99 (39.9)100 (39.4)
Idiopathic24 (4.8)12 (4.8)12 (4.7)
Hypertriglyceridemia248 (49.4)121 (48.8)127 (50.0)
The extent of pancreatic necrosis0.28
≤50%439 (62.2)216 (64.9)223 (59.4)
>50%63 (12.5)32 (12.9)31 (12.2)
The interval between onset and randomization, day4.0 (2.4–6.0)4.0 (2.0–6.0)4.0 (2.7–6.0)0.92
Laboratory indexes
C-reactive protein, g/L164.7 (99.0–236.3)168.9 (94.1–236.5)160.6 (105.5–236.4)0.93
Lymphocyte count, ×109/L0.9 (0.6–1.2)0.9 (0.6–1.2)0.9 (0.7–1.2)0.31
Metabolic abnormalities
Hyperglycemia271 (54.0)133 (53.6)138 (54.3)1.00
Hypertriglyceridemia371 (73.9)184 (74.2)187 (73.6)1.00
Severe hypertriglyceridemia178 (35.5)85 (34.3)93 (36.6)1.00
Combined hyperglycemia and hypertriglyceridemia229 (45.6)116 (46.8)113 (44.5)1.00

Data are presented as median (interquartile range) or number (%)..

Tα1, thymosin alpha 1; APACHE II, Acute Physiology and Chronic Health Evaluation II, which ranges from 0 to 71, with higher scores indicating more severe disease; SOFA, Sequential Organ Failure Assessment, the score for which ranges from 0 to 24; a higher scores indicates more severe organ failure..

p>0.05 for the comparison between the groups for all characteristics..



2. Results of subgroup analysis

On trial day 90 after randomization, 55 (22.2%) patients who received Tα1 developed IPN, while 65 (25.6%) patients who received placebo did so (Supplementary Fig. 2). The interaction between baseline metabolic abnormalities and the efficacy of treatment was examined further by analyzing four subgroups: patients with hyperglycemia, with hypertriglyceridemia, with both, or with severe hypertriglyceridemia. The impact of hyperglycemia on the efficacy of Tα1 treatment was the most significant (p for interaction=0.03) (Fig. 1).

Figure 1. Subgroup analysis of the risk of 90-day infected pancreatic necrosis. A risk difference of less than 1 indicates better results for the thymosin alpha-1 (Tα1) group.
HR, hazard ratio; CI, confidence interval.

3. Primary outcome and secondary outcomes

Among the 271 patients with hyperglycemia, 133 received Tα1 and 138 received placebo. The baseline characteristics of the study subjects are shown in Supplementary Table 1. Overall, 24 patients (18.0%) developed IPN in the Tα1 group, significantly lower than the placebo group (n=41, 29.7%) (HR, 0.57; 95% CI, 0.34 to 0.94; p=0.03). Among patients with hypertriglyceridemia or with combined hypertriglyceridemia and hyperglycemia, the use of Tα1 did not lead to a difference in the incidence of IPN (Fig. 1).

The cumulative incidence of IPN within 90 days of randomization is shown in Fig. 2. Among ANP patients with hyperglycemia, the likelihood of developing IPN was significantly lower in the Tα1 group compared to the placebo groups (log-rank p=0.024). The results for those without hyperglycemia are shown in Supplementary Fig. 3. The results of multivariate Cox regression analysis for 90-day IPN in hyperglycemia patients confirmed that Tα1 was an independent protective factor for the reduction of IPN after adjustment for age, sex, etiology, and APACHE II score at randomization (HR, 0.59; 95% CI, 0.35 to 0.99; p=0.047) (Table 2).

Figure 2. The Kaplan-Meier curves for the cumulative incidence of infected pancreatic necrosis from randomization to day 90 in patients with hyperglycemia.
Tα1, thymosin alpha-1.

Table 2 . Multivariate Cox Regression Analysis for 90-Day Infected Pancreatic Necrosis Based on the Cox Proportional-Hazards Model in Patients with Hyperglycemia.

ParameterHR (95% CI)p-value
Age1.01 (0.99–1.03)0.25
Male sex1.44 (0.82–2.55)0.21
Etiology
BiliaryReference
Hyperlipidemic0.74 (0.40–1.35)0.32
Alcohol1.65 (0.58–4.71)0.35
Others0.26 (0.03–1.92)0.18
APACHE II score1.05 (1.01–1.09)0.01
Treatment
PlaceboReference
Tα10.59 (0.35–0.99)0.047

HR, hazard ratio; CI, confidence interval; APACHE II, Acute Physiology and Chronic Health Evaluation II, the score for which ranges from 0 to 71; a high score indicates more severe disease; Tα1, thymosin alpha-1..



For sensitivity analysis, three propensity-score methods were used. Overall, there was also significant association between Tα1 treatment and the reduced primary endpoint (HR 0.59, 95% CI 0.41 to 0.85 for the IPTW method; HR 0.58, 95% CI 0.35 to 0.99 for the PSM method; HR 0.55, 95% CI 0.33 to 0.93 for the method adjusted for propensity score) in each propensity-score method (Table 3). The baseline data of the two groups before and after PSM and IPTW are shown in Supplementary Table 2 and Supplementary Fig. 1.

Table 3 . Associations between Early Tα1 Treatment and the End Point of 90-Day IPN in the Crude Analysis, Multivariable Analysis, and Propensity-Score Analyses.

Analysis90-Day IPN, HR (95% CI)
No. of events/no. of patients at risk (%)
Tα124/133 (18.0)
Placebo41/138 (29.7)
Crude analysis0.57 (0.34–0.94)
Multivariable analysis*0.59 (0.35–0.99)
Propensity-score analyses
With inverse probability weighting0.59 (0.41–0.85)
With matching0.58 (0.35–0.99)
Adjusted for propensity score§0.55 (0.33–0.93)

Tα1, thymosin alpha-1; IPN, infected pancreatic necrosis; HR, hazard ratio; CI, confidence interval..

*The primary analysis with a hazard ratio from the multivariable Cox proportional-hazards model, with additional adjustment for age, sex, etiology and APACHE II score at randomization. The analysis included all 271 patients; The hazard ratio from the multivariable Cox proportional-hazards model with the same covariates with inverse probability weighting according to the propensity score. The analysis included all the patients with their respective weight; Shown is the hazard ratio from a multivariable Cox proportional-hazards model with the same covariates among the matched patients according to the propensity score. The analysis included 248 patients (124 who received Tα1 and 124 who received placebo); §The hazard ratio from a multivariable Cox proportional-hazards model with the same covariates, with additional adjustment for the propensity score. The analysis included all the 271 patients..



Regarding the secondary outcomes, no significant difference was observed between patients who received Tα1 or placebo among the 271 patients with hyperglycemia (Table 4). There was also no difference in C-reactive protein level or the lymphocyte count at day 7 or day 14 after randomization or the monocyte human leukocyte antigen-DR level at enrolment, day 7, or day 14 after randomization (Supplementary Table 3).

Table 4 . Secondary Clinical Outcomes in Patients with Hyperglycemia.

Secondary clinical outcomeTα1 group (n=133)Placebo group (n=138)p-value
New onset organ failure
Respiratory3 (2.3)7 (5.1)0.22
Renal8 (6.0)3 (2.2)0.13
Cyclic6 (4.5)11 (8.0)0.24
Invasive interventions18 (13.5)22 (15.9)0.58
Length of hospital stay, day15 (11–24)17.5 (9–25.3)0.70
Length of ICU stay, day9 (5–16.5)10 (5.8–19)0.37
90-Day mortality11 (8.3)16 (11.6)0.36

Data are presented as number (%) or median (interquartile range)..

Tα1, thymosin alpha-1; ICU, intensive care unit..


DISCUSSION

In this post hoc analysis, we found that metabolic abnormalities are common in predicted severe ANP patients. The subgroup analysis suggested that predicted severe ANP patients with hyperglycemia may benefit from immune-enhancing Tα1 treatment by reducing the incidence of IPN.

Metabolic syndrome, defined by the presence of a cluster of metabolic abnormalities that includes hyperglycemia, central obesity, hypertriglyceridemia, hypertension, and low high-density lipoprotein cholesterol level, has been identified as a common clinical finding and is associated with increased mortality and morbidity in AP.5 A previous study revealed that more than 60% of AP patients had at least one major metabolic comorbidity, which was similar to our findings (53.9% hyperglycemia and 73.9% hypertriglyceridemia).26 Among the components of metabolic syndrome, hyperglycemia and hypertriglyceridemia are the two most common metabolic abnormalities, which have frequently been reported to be associated with worse prognosis in AP.8,9,27 Furthermore, both hyperglycemia and hypertriglyceridemia have been linked to impaired immune function,10,12 potentially increasing the incidence of infection. However, in our study, only patients with hyperglycemia responded differently to the Tα1 therapy.

The pharmacological characteristics of Tα1 may explain these findings: hyperglycemia is thought to impair a wide range of functions in neutrophils, macrophages and natural killer cells, including impaired migration, decreased membrane fluidity, reduced phagocytosis and intracellular killing capacity, and altered chemotaxis, resulting in increased susceptibility towards infections and increased severity of infections.11,28-30 The specific mechanism of hyperglycemia's effect on the innate immune response is still unknown, but it may involve activating protein kinase C or altering the tertiary structure of complement via direct glycosylation.28 Tα1, which is thought to affect dendritic cells and T helper cells, stimulates innate immunity, including neutrophils, natural killer cells, and macrophages.31 Given these well-known pharmacological effects, we hypothesized that Tα1 could reduce the occurrence of IPN by repairing the innate immune damage caused by hyperglycemia. To clarify this, a future prospective study is required.

On the other hand, we did not observe different treatment responses in patients with hypertriglyceridemia or combined disorders. Current evidence suggests that increased fatty acid levels can cause inflammation and elevated cytokines, worsening kidney, lung, and shock injury, eventually leading to multi-system organ failure and increased mortality.32 Though hypertriglyceridemia was reported to affect the circulating neutrophil subpopulation,10 whether it is associated with immune dysfunction was poorly studied. Moreover, another possible explanation may be simply that the sample size of patients with hypertriglyceridemia was underpowered.

Attempts have been made in boosting the immune system in patients with diabetes, including liposomal glutathione,33 mechanistic target of rapamycin inhibitor,34 and microbiological and immunological enteral nutrition.35 But none of them targeted the innate immune system directly. Recently, a network enrichment analysis revealed that Tα1 also regulates cellular metabolic processes, implying that Tα1 treatment may have new translational implications in pathological conditions such as diabetes.36 Furthermore, a previous experimental study found that co-administration of Tα1 protects against streptozotocin-induced pancreatic damage and diabetes, and that part of the protection may be achieved by increasing pancreatic antioxidative capability.37 Given these known pieces of evidence, our findings offer a promising direction for further investigation and point to the potential of immune-enhancing Tα1 therapy in the treatment of diabetes.

This subgroup analysis has several strengths: (1) the subgroup variables (HbA1c and blood glucose) were measured at the baseline, and the definitions of hyperglycemia were from previously published studies;18,19 (2) the comparison was undertaken within a single RCT conducted at several sites, which increases the generalizability of the received findings; (3) the use of three different propensity-score methods, reflecting the robustness of these findings; (4) the findings have a plausible pharmacologic explanation.

Some limitations need to be also acknowledged. (1) the retrospective nature of this post hoc analysis may bring in some inevitable bias; (2) there is a lack of other laboratory parameters reflecting the amelioration of immune suppression after Tα1 treatment; (3) hypertriglyceridemia-induced AP accounts for approximately 50% of the study subjects and alcohol-induced AP only 6%, which differs significantly from cohorts reported in Western countries.38,39 Possible explanations may include changes in dietary habits in China over the last few decades,40 genetic factors,41,42 and different alcohol drinking habits; and (4) the definition of hyperglycemia used in this study is a composite one, and approximately 50% of hyperglycemia patients were diagnosed solely based on random blood glucose levels, which can be impacted by patients' fasting status, the use of dextrose fluid, and glycemic control treatments. However, we can not control for these potential confounders since the original trial did not collect the corresponding data.

In conclusion, Tα1 treatment was associated with reduced IPN incidence in ANP patients with hyperglycemia. To confirm our findings, a future randomized trial with sufficient power is required.

ACKNOWLEDGEMENTS

We acknowledge the contribution of the members of the TRACE trial study group: Lu Ke, Jing Zhou, Wenjian Mao, Wendi Jiang, He Zhang, Jiajia Lin, Mengjie Lu, Yan Chen, Baiqiang Li, Zhihui Tong, Yuxiu Liu, Weiqin Li, Jinling Hospital. Tao Chen, Liverpool University. Fang Shao, Nanjing Medical University. Nonghua Lv, Yin Zhu, Liang Xia, Wenhua He, Zhenping Chen, The First Affiliated Hospital of Nanchang University. Xinting Pan, Qingyun Zhu, Youdong Wan, The Affiliated Hospital of Qingdao University. Hong Mei, Kang Li, Miao Chen, The Affiliated Hospital of Zunyi Medical University. Chengjian He, Hongyi Yao, Zigui Zhu, Nanhua Hospital. Weili Gu, Affiliated Hospital 2 of Nantong University. Weihua Lu, Jingyi Wu, Feng Zhou, The First Affiliated Hospital of Wannan Medical College. Shumin Tu, Long Fu, Bing Xue, Shangqiu First People's Hospital. Haibin Ni, Xiaofei Huang, Dandan Zhou, Jiangsu Provincial Hospital of Integrated Chinese and Western Medicine. Guoxiu Zhang, Lening Ren, Dahuan Li, The First Affiliated Hospital and College of Clinical Medicine of Henan University of Science and Technology. Xiangyang Zhao, Wei Zhao, Xiaomei Chen, Qilu Hospital of Shandong University. Junli Sun, Keke Xin, Luoyang Central Hospital. Weiwei Chen, Qingcheng Xu, Clinical Medical College of Yangzhou University. Jingchun Song, Qingbo Zeng, 94th Hospital of PLA. Min Shao, Dongsheng Zhao, The First Affiliated Hospital of Anhui Medical University. Jianfeng Tu, Hongguo Yang, Zhejiang Provincial People's Hospital.

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

AUTHOR CONTRIBUTIONS

Study concept and design: X.H., D.Z., L.K., H.N. Data acquisition: W.M., X.H., F.Q., H.Z., A.Z., X.W. Data analysis and interpretation: W.M. Drafting of the manuscript: X.H., W.M., L.K. Critical revision of the manuscript for important intellectual content: C.S., L.K., H.N. Statistical analysis: W.M. Administrative, technical, or material support; study supervision: D.Z., L.K., H.N. Approval of final manuscript: all authors.

SUPPLEMENTARY MATERIALS

Supplementary materials can be accessed at https://doi.org/10.5009/gnl230326.

DATA AVAILABILITY STATEMENT

Deidentified individual participant data are available indefinitely in the electronic database. Data can be accessed through capctg.medbit.cn with the approval of the authors. Request for data can be made to the corresponding author (ctgchina@medbit.cn) and will be discussed during a meeting of the Chinese Acute Pancreatitis Clinical Trials Group (CAPCTG).

Fig 1.

Figure 1.Subgroup analysis of the risk of 90-day infected pancreatic necrosis. A risk difference of less than 1 indicates better results for the thymosin alpha-1 (Tα1) group.
HR, hazard ratio; CI, confidence interval.
Gut and Liver 2024; :

Fig 2.

Figure 2.The Kaplan-Meier curves for the cumulative incidence of infected pancreatic necrosis from randomization to day 90 in patients with hyperglycemia.
Tα1, thymosin alpha-1.
Gut and Liver 2024; :

Table 1 Baseline Characteristics of the Study Subjects

CharacteristicTotal (n=502)Tα1 group (n=248)Placebo group (n=254)p-value
Age, yr43.0 (35.0–53.0)43.0 (34.3–52.8)44.0 (35.0–54.0)0.48
Sex0.66
Female187 (37.3)90 (36.3)97 (38.2)
Male315 (62.7)158 (63.7)157 (61.8)
Body mass index, kg/m226.3 (24.0–28.4)26.2 (24.0–28.2)26.5 (24.2–29.0)0.45
APACHE II score10.0 (8.0–13.0)10.0 (8.0–13.0)10.0 (8.0–13.0)0.98
SOFA score4.0 (2.0–6.0)4.0 (2.0–6.0)4.0 (2.0–6.0)0.80
Etiologies0.99
Alcoholic31 (6.2)16 (6.5)15 (5.9)
Biliary199 (39.6)99 (39.9)100 (39.4)
Idiopathic24 (4.8)12 (4.8)12 (4.7)
Hypertriglyceridemia248 (49.4)121 (48.8)127 (50.0)
The extent of pancreatic necrosis0.28
≤50%439 (62.2)216 (64.9)223 (59.4)
>50%63 (12.5)32 (12.9)31 (12.2)
The interval between onset and randomization, day4.0 (2.4–6.0)4.0 (2.0–6.0)4.0 (2.7–6.0)0.92
Laboratory indexes
C-reactive protein, g/L164.7 (99.0–236.3)168.9 (94.1–236.5)160.6 (105.5–236.4)0.93
Lymphocyte count, ×109/L0.9 (0.6–1.2)0.9 (0.6–1.2)0.9 (0.7–1.2)0.31
Metabolic abnormalities
Hyperglycemia271 (54.0)133 (53.6)138 (54.3)1.00
Hypertriglyceridemia371 (73.9)184 (74.2)187 (73.6)1.00
Severe hypertriglyceridemia178 (35.5)85 (34.3)93 (36.6)1.00
Combined hyperglycemia and hypertriglyceridemia229 (45.6)116 (46.8)113 (44.5)1.00

Data are presented as median (interquartile range) or number (%).

Tα1, thymosin alpha 1; APACHE II, Acute Physiology and Chronic Health Evaluation II, which ranges from 0 to 71, with higher scores indicating more severe disease; SOFA, Sequential Organ Failure Assessment, the score for which ranges from 0 to 24; a higher scores indicates more severe organ failure.

p>0.05 for the comparison between the groups for all characteristics.


Table 2 Multivariate Cox Regression Analysis for 90-Day Infected Pancreatic Necrosis Based on the Cox Proportional-Hazards Model in Patients with Hyperglycemia

ParameterHR (95% CI)p-value
Age1.01 (0.99–1.03)0.25
Male sex1.44 (0.82–2.55)0.21
Etiology
BiliaryReference
Hyperlipidemic0.74 (0.40–1.35)0.32
Alcohol1.65 (0.58–4.71)0.35
Others0.26 (0.03–1.92)0.18
APACHE II score1.05 (1.01–1.09)0.01
Treatment
PlaceboReference
Tα10.59 (0.35–0.99)0.047

HR, hazard ratio; CI, confidence interval; APACHE II, Acute Physiology and Chronic Health Evaluation II, the score for which ranges from 0 to 71; a high score indicates more severe disease; Tα1, thymosin alpha-1.


Table 3 Associations between Early Tα1 Treatment and the End Point of 90-Day IPN in the Crude Analysis, Multivariable Analysis, and Propensity-Score Analyses

Analysis90-Day IPN, HR (95% CI)
No. of events/no. of patients at risk (%)
Tα124/133 (18.0)
Placebo41/138 (29.7)
Crude analysis0.57 (0.34–0.94)
Multivariable analysis*0.59 (0.35–0.99)
Propensity-score analyses
With inverse probability weighting0.59 (0.41–0.85)
With matching0.58 (0.35–0.99)
Adjusted for propensity score§0.55 (0.33–0.93)

Tα1, thymosin alpha-1; IPN, infected pancreatic necrosis; HR, hazard ratio; CI, confidence interval.

*The primary analysis with a hazard ratio from the multivariable Cox proportional-hazards model, with additional adjustment for age, sex, etiology and APACHE II score at randomization. The analysis included all 271 patients; The hazard ratio from the multivariable Cox proportional-hazards model with the same covariates with inverse probability weighting according to the propensity score. The analysis included all the patients with their respective weight; Shown is the hazard ratio from a multivariable Cox proportional-hazards model with the same covariates among the matched patients according to the propensity score. The analysis included 248 patients (124 who received Tα1 and 124 who received placebo); §The hazard ratio from a multivariable Cox proportional-hazards model with the same covariates, with additional adjustment for the propensity score. The analysis included all the 271 patients.


Table 4 Secondary Clinical Outcomes in Patients with Hyperglycemia

Secondary clinical outcomeTα1 group (n=133)Placebo group (n=138)p-value
New onset organ failure
Respiratory3 (2.3)7 (5.1)0.22
Renal8 (6.0)3 (2.2)0.13
Cyclic6 (4.5)11 (8.0)0.24
Invasive interventions18 (13.5)22 (15.9)0.58
Length of hospital stay, day15 (11–24)17.5 (9–25.3)0.70
Length of ICU stay, day9 (5–16.5)10 (5.8–19)0.37
90-Day mortality11 (8.3)16 (11.6)0.36

Data are presented as number (%) or median (interquartile range).

Tα1, thymosin alpha-1; ICU, intensive care unit.


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Vol.18 No.4
July, 2024

pISSN 1976-2283
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