The prognostic role of cytokines in assessing the course of acute pancreatitis: a systematic review and meta-analysis

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Abstract

Acute pancreatitis (AP) is an inflammatory disease of the pancreas that can lead to potentially severe complications. Despite the availability of clinical scoring systems to predict disease severity, there remains a need for more accurate and rapid tools for early prognostication.

A systematic assessment of the significance of serum interleukin levels for predicting disease severity in patients with acute pancreatitis was performed.

This study was conducted according to the PRISMA guidelines. A systematic literature search (2013–2024) was performed using PubMed and Google Scholar. Data on the diagnostic accuracy of interleukins, specifically the area under the ROC curve (AUC), sensitivity, and specificity, were extracted and analyzed. The quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Meta-regression and sensitivity analyses were also performed.

The meta-analysis included 11 studies of interleukin-6 (n = 1377) and 5 studies of interleukin-8 (n = 535). The pooled area under the ROC curve (AUC) for interleukin-6 was 0.84 by the random-effects model with high heterogeneity (I2 = 92%), for interleukin-8 — the pooled AUC was 0.843 (I2 = 80.76%). The area under the hierarchical summary ROC curve was 0.697 for interleukin-6 (sensitivity — 80.9%, specificity — 54.5%) and 0.595 for interleukin-8 (sensitivity — 87.7%, specificity — 39.6%), which indicates a moderate summary accuracy of both markers. A subgroup analysis of interleukin-6 using thresholds of ≥100 pg/mL demonstrated an AUC of 0.852 and a hierarchical summary ROC AUC of 0.621. For interleukin-8, a cut-off value of <39.55 pg/mL the pooled AUC was 0.726 (I2 = 80%), while a cut-off of ≥39.55 pg/mL resulted in an AUC of 0.949 (95% CI 0.904–0.995), I2 = 69.5%. These findings indicate that higher IL-8 thresholds yielded not only more accurate (AUC = 0.95) but also more homogeneous results (I2 reduced from 80% to 69.5%).

The dynamics of interleukin-22 levels demonstrated the highest prognostic accuracy among secondary cytokines (AUC = 0.857, sensitivity — 83%, specificity — 85%). Despite signs of publication bias, the results were robust in the sensitivity analysis.

Interleukin-6 is the most informative biomarker for the early prediction of severe acute pancreatitis. Interleukin-8 complements the severity assessment by reflecting neutrophil activation, whereas interleukins-10 and -22 indicate the balance of the inflammatory response and hold potential as therapeutic targets. The use of a cytokine profile in conjunction with clinical scoring systems may improve the accuracy of risk stratification and patient outcomes.

About the authors

Liudmila K. Orbelian

Kuban State Medical University

Author for correspondence.
Email: orbelyan@mail.ru
ORCID iD: 0000-0003-1428-393X
SPIN-code: 8123-4311

MD

Russian Federation, Krasnodar

Vladimir M. Durleshter

Kuban State Medical University; Regional Clinical Hospital No. 2, Krasnodar

Email: durleshter59@mail.ru
ORCID iD: 0000-0002-7420-0553
SPIN-code: 6229-6933

MD, Dr. Sci. (Medicine), Professor

Russian Federation, Krasnodar; Krasnodar

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Supplementary files

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2. Fig. 1. PRISMA flow diagram of study selection.

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3. Fig. 2. Risk of bias assessment.

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4. Fig. 3. Distribution of risk of bias and applicability across domains.

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5. Fig. 4. Forest plot showing the areas under the ROC curves in studies of interleukin-6.

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6. Fig. 5. Hierarchical summary ROC (HSROC) curve illustrating the role of interleukin-6 in predicting severe acute pancreatitis. AUC, area under the ROC curve; TPR, true positive rate; FPR, false positive rate.

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7. Fig. 6. Hierarchical summary ROC (HSROC) curve illustrating the role of interleukin-6 in predicting severe acute pancreatitis for studies with a cutoff value ≥100 pg/mL. AUC, area under the ROC curve; TPR, true positive rate; FPR, false positive rate.

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8. Fig. 7. Forest plot showing the areas under the ROC curves in studies of interleukin-8.

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9. Fig. 8. Hierarchical summary ROC (HSROC) curve illustrating the role of interleukin-8 in predicting severe acute pancreatitis. AUC, area under the ROC curve; TPR, true positive rate; FPR, false positive rate.

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10. Fig. 9. Hierarchical summary ROC (HSROC) curve illustrating the role of interleukin-8 in predicting severe acute pancreatitis for studies with a cutoff value ≥39.55 pg/mL. AUC, area under the ROC curve; TPR, true positive rate; FPR, false positive rate.

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