RT Journal Article
SR Electronic
T1 Identification and validation of a multivariable prediction model based on blood plasma and serum metabolomics for the distinction of chronic pancreatitis subjects from non-pancreas disease control subjects
JF Gut
JO Gut
FD BMJ Publishing Group Ltd and British Society of Gastroenterology
SP gutjnl-2020-320723
DO 10.1136/gutjnl-2020-320723
A1 M Gordian Adam
A1 Georg Beyer
A1 Nicole Christiansen
A1 Beate Kamlage
A1 Christian Pilarsky
A1 Marius Distler
A1 Tim Fahlbusch
A1 Ansgar Chromik
A1 Fritz Klein
A1 Marcus Bahra
A1 Waldemar Uhl
A1 Robert Grützmann
A1 Ujjwal M Mahajan
A1 Frank U Weiss
A1 Julia Mayerle
A1 Markus M Lerch
YR 2021
UL http://gut.bmj.com/content/early/2021/02/18/gutjnl-2020-320723.abstract
AB Objective Chronic pancreatitis (CP) is a fibroinflammatory syndrome leading to organ dysfunction, chronic pain, an increased risk for pancreatic cancer and considerable morbidity. Due to a lack of specific biomarkers, diagnosis is based on symptoms and specific but insensitive imaging features, preventing an early diagnosis and appropriate management.Design We conducted a type 3 study for multivariable prediction for individual prognosis according to the TRIPOD guidelines. A signature to distinguish CP from controls (n=160) was identified using gas chromatography-mass spectrometry and liquid chromatography‐tandem mass spectrometry on ethylenediaminetetraacetic acid (EDTA)-plasma and validated in independent cohorts.Results A Naive Bayes algorithm identified eight metabolites of six ontology classes. After algorithm training and computation of optimal cut-offs, classification according to the metabolic signature detected CP with an area under the curve (AUC) of 0.85 ((95% CI 0.79 to 0.91). External validation in two independent cohorts (total n=502) resulted in similar accuracy for detection of CP compared with non-pancreatic controls in EDTA-plasma (AUC 0.85 (95% CI 0.81 to 0.89)) and serum (AUC 0.87 (95% CI 0.81 to 0.95)).Conclusions This is the first study that identifies and independently validates a metabolomic signature in plasma and serum for the diagnosis of CP in large, prospective cohorts. The results could provide the basis for the development of the first routine laboratory test for CP.