Prediction of Severe Acute Pancreatitis Using Classification and Regression Tree Analysis

Overview

Journal Dig Dis Sci

Specialty Gastroenterology

Date 2011 Aug 12

PMID 21833749

Citations 25

Authors

Wandong Hong

Lemei Dong

Qingke Huang

Wenzhi Wu

Jiansheng Wu

Yumin Wang

Affiliations

Soon will be listed here.

Abstract

Background: The available prognostic scoring systems for acute pancreatitis have limitations that restrict their clinical value.

Aims: To develop a decision model based on classification and regression tree (CART) analysis for the prediction of severe acute pancreatitis (SAP).

Methods: A total of 420 patients with acute pancreatitis were enrolled. Study participants were randomly assigned to the training sample and test sample in a 2:1 ratio. First, univariate analysis and logistic regression analysis were used to identify predictors associated with SAP in the training sample. Then, CART analysis was carried out to develop a simple tree model for the prediction of SAP. A receiver operating characteristic (ROC) curve was constructed in order to assess the performance of the model. The prediction model was then applied to the test sample.

Results: Four variables (systemic inflammatory response syndrome [SIRS], pleural effusion, serum calcium, and blood urea nitrogen [BUN]) were identified as important predictors of SAP by logistic regression analysis. A tree model (which consisted of pleural effusion, serum calcium, and BUN) that was developed by CART analysis was able to early identify among cohorts at high (79.03%) and low (7.80%) risk of developing SAP. The area under the ROC curve of the tree model was higher than that of the APACHE II score (0.84 vs. 0.68; P < 0.001). The predicted accuracy of the tree model was validated in the test sample with an area under the ROC curve of 0.86.

Conclusions: A decision tree model that consists of pleural effusion, serum calcium, and BUN may be useful for the prediction of SAP.

Citing Articles

Predictive value of machine learning for the severity of acute pancreatitis: A systematic review and meta-analysis.

Qian R, Zhuang J, Xie J, Cheng H, Ou H, Lu X Heliyon. 2024; 10(8):e29603.

PMID: 38655348 PMC: 11035062. DOI: 10.1016/j.heliyon.2024.e29603.

Severe Acute Pancreatitis Prediction: A Model Derived From a Prospective Registry Cohort.

Barrera Gutierrez J, Greenburg I, Shah J, Acharya P, Cui M, Vivian E Cureus. 2023; 15(10):e46809.

PMID: 37954725 PMC: 10636501. DOI: 10.7759/cureus.46809.

Decreased HDL-C Levels as a Predictor of Organ Failure in Acute Pancreatitis in the Emergency Department.

Venegas-Tamayo A, Pena-Veites O, Hernandez-Gonzalez M, Barrientos-Alvarado C Life (Basel). 2023; 13(7).

PMID: 37511976 PMC: 10381343. DOI: 10.3390/life13071602.

Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis.

Li B, Wu W, Liu A, Feng L, Li B, Mei Y J Inflamm Res. 2023; 16:2831-2843.

PMID: 37449283 PMC: 10337691. DOI: 10.2147/JIR.S416411.

Red Cell Distribution Width and Ratio of Red Cell Distribution Width-to-Total Serum Calcium as Predictors of Outcome of Acute Pancreatitis.

Gupta V, Narang S, Gill C, Selhi P, Gupta M Int J Appl Basic Med Res. 2023; 13(1):5-9.

PMID: 37266525 PMC: 10230523. DOI: 10.4103/ijabmr.ijabmr_286_22.

References

Heller S, Noordhoek E, Tenner S, Ramagopal V, Abramowitz M, Hughes M . Pleural effusion as a predictor of severity in acute pancreatitis. Pancreas. 1997; 15(3):222-5. DOI: 10.1097/00006676-199710000-00002. View

Vege S, Gardner T, Chari S, Munukuti P, Pearson R, Clain J . Low mortality and high morbidity in severe acute pancreatitis without organ failure: a case for revising the Atlanta classification to include "moderately severe acute pancreatitis". Am J Gastroenterol. 2009; 104(3):710-5. DOI: 10.1038/ajg.2008.77. View

Banks P, Freeman M . Practice guidelines in acute pancreatitis. Am J Gastroenterol. 2006; 101(10):2379-400. DOI: 10.1111/j.1572-0241.2006.00856.x. View

Mentula P, Kylanpaa M, Kemppainen E, Jansson S, Sarna S, Puolakkainen P . Early prediction of organ failure by combined markers in patients with acute pancreatitis. Br J Surg. 2004; 92(1):68-75. DOI: 10.1002/bjs.4786. View

Gonzalvez-Gasch A, Garcia de Casasola G, Barba Martin R, Herreros B, Guijarro C . A simple prognostic score for risk assessment in patients with acute pancreatitis. Eur J Intern Med. 2009; 20(3):e43-8. DOI: 10.1016/j.ejim.2008.09.014. View

Petrov M, Shanbhag S, Chakraborty M, Phillips A, Windsor J . Organ failure and infection of pancreatic necrosis as determinants of mortality in patients with acute pancreatitis. Gastroenterology. 2010; 139(3):813-20. DOI: 10.1053/j.gastro.2010.06.010. View

Mortele K, Wiesner W, Intriere L, Shankar S, Zou K, Kalantari B . A modified CT severity index for evaluating acute pancreatitis: improved correlation with patient outcome. AJR Am J Roentgenol. 2004; 183(5):1261-5. DOI: 10.2214/ajr.183.5.1831261. View

Augustin S, Muntaner L, Altamirano J, Gonzalez A, Saperas E, Dot J . Predicting early mortality after acute variceal hemorrhage based on classification and regression tree analysis. Clin Gastroenterol Hepatol. 2009; 7(12):1347-54. DOI: 10.1016/j.cgh.2009.08.011. View

Spitzer A, Barcia A, Schell M, Barber A, Norman J, Grendell J . Applying Ockham's razor to pancreatitis prognostication: a four-variable predictive model. Ann Surg. 2006; 243(3):380-8. PMC: 1448950. DOI: 10.1097/01.sla.0000202213.22389.36. View

10.

Bradley 3rd E . A clinically based classification system for acute pancreatitis. Summary of the International Symposium on Acute Pancreatitis, Atlanta, Ga, September 11 through 13, 1992. Arch Surg. 1993; 128(5):586-90. DOI: 10.1001/archsurg.1993.01420170122019. View

11.

DeLong E, Delong D, Clarke-Pearson D . Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988; 44(3):837-45. View

12.

De Waele J, Delrue L, Hoste E, De Vos M, Duyck P, Colardyn F . Extrapancreatic inflammation on abdominal computed tomography as an early predictor of disease severity in acute pancreatitis: evaluation of a new scoring system. Pancreas. 2007; 34(2):185-90. DOI: 10.1097/mpa.0b013e31802d4136. View

13.

Wu B, Johannes R, Sun X, Tabak Y, Conwell D, Banks P . The early prediction of mortality in acute pancreatitis: a large population-based study. Gut. 2008; 57(12):1698-703. DOI: 10.1136/gut.2008.152702. View

14.

Ueda T, Takeyama Y, Yasuda T, Matsumura N, Sawa H, Nakajima T . Simple scoring system for the prediction of the prognosis of severe acute pancreatitis. Surgery. 2006; 141(1):51-8. DOI: 10.1016/j.surg.2006.05.008. View

15.

Brown A, James-Stevenson T, Dyson T, Grunkenmeier D . The panc 3 score: a rapid and accurate test for predicting severity on presentation in acute pancreatitis. J Clin Gastroenterol. 2007; 41(9):855-8. DOI: 10.1097/01.mcg.0000248005.73075.e4. View

16.

Kurosaki M, Matsunaga K, Hirayama I, Tanaka T, Sato M, Yasui Y . A predictive model of response to peginterferon ribavirin in chronic hepatitis C using classification and regression tree analysis. Hepatol Res. 2010; 40(4):251-60. DOI: 10.1111/j.1872-034X.2009.00607.x. View

17.

Hong W, Zhu Q, Huang Z, Chen X, Jiang Z, Xu S . Predictors of esophageal varices in patients with HBV-related cirrhosis: a retrospective study. BMC Gastroenterol. 2009; 9:11. PMC: 2661092. DOI: 10.1186/1471-230X-9-11. View

18.

Harrison D, DAmico G, Singer M . The Pancreatitis Outcome Prediction (POP) Score: a new prognostic index for patients with severe acute pancreatitis. Crit Care Med. 2007; 35(7):1703-8. DOI: 10.1097/01.CCM.0000269031.13283.C8. View

19.

Rajaratnam S, Martin I . Admission serum glucose level: an accurate predictor of outcome in gallstone pancreatitis. Pancreas. 2006; 33(1):27-30. DOI: 10.1097/01.mpa.0000222315.36490.9b. View

20.

Petrov M, Windsor J . Classification of the severity of acute pancreatitis: how many categories make sense?. Am J Gastroenterol. 2009; 105(1):74-6. DOI: 10.1038/ajg.2009.597. View