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Sci Transl Med. 2019 Jul 17;11(501). pii: eaav4772. doi: 10.1126/scitranslmed.aav4772.

A multimodality test to guide the management of patients with a pancreatic cyst.

Author information

1
Ludwig Center and Howard Hughes Medical Institute at the Sidney Kimmel Cancer Center, Johns Hopkins University, Baltimore, MD 21287, USA.
2
Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University, Baltimore, MD 21287, USA.
3
Department of Biomedical Engineering, Johns Hopkins Medical Institutions, Johns Hopkins University, Baltimore, MD 21287, USA.
4
Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21287, USA.
5
Department of Pathology, Johns Hopkins University, Baltimore, MD 21287, USA.
6
Department of Oncology, Johns Hopkins University, Baltimore, MD 21287, USA.
7
Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
8
Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
9
Department of Gastroenterology, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
10
Department of Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
11
Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
12
Department of Histopathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
13
Department of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
14
Department of Medicine, University of Pittsburgh, Pittsburgh PA 15213, USA.
15
Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
16
ARC-Net Research Centre, University and Hospital Trust of Verona, Verona 37134, Italy.
17
Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona 37134, Italy.
18
General and Pancreatic Surgery, Pancreas Institute, University and Hospital Trust of Verona, Verona 37134, Italy.
19
Department of Pathology, Ospedale Sacro Cuore-Don Calabria, Negrar 37024, Italy.
20
Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, South Korea.
21
Hepatobiliary and Pancreas Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, South Korea.
22
Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, South Korea.
23
Department of Histopathology, St. Vincent's University Hospital, Dublin D04 T6F4, Ireland.
24
Department of Surgery, St. Vincent's University Hospital, Dublin D04 T6F4, Ireland.
25
Division of Pancreatic Surgery, Department of Surgery, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy.
26
Department of Pathology, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy.
27
Department of Surgery, Centro Hepatobiliopancreático e Transplantação, Hospital Curry Cabral, Lisbon 1050-099, Portugal.
28
Department of Surgery, University of Colorado, Aurora, CO 80045, USA.
29
Department of Medicine, Stanford University Medical Center, Palo Alto, CA 94304, USA.
30
Department of Hepatobiliary and Pancreatic Surgery, Pathology and Cancer Genomics, National Cancer Center Hospital and National Cancer Center Research Institute, Tokyo 104-0045, Japan.
31
Department of Gastroenterology, Aichi Cancer Center Hospital, Nagoya 464-8681, Japan.
32
Department of Gastroenterology and Hepatology, Amsterdam Medical Center, Amsterdam 1017 ZX, Netherlands.
33
Department of Surgery, Johns Hopkins University, Baltimore, MD 21287, USA.
34
Department of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA.
35
Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University, Baltimore, MD 21287, USA. bertvog@gmail.com amlennon@jhmi.edu cwolfga2@jhmi.edu rhruban@jhmi.edu ctomasetti@jhu.edu karchin@jhu.edu.
36
Department of Biostatistics and Bioinformatics, Johns Hopkins University, Baltimore, MD 21287, USA.
37
Ludwig Center and Howard Hughes Medical Institute at the Sidney Kimmel Cancer Center, Johns Hopkins University, Baltimore, MD 21287, USA. bertvog@gmail.com amlennon@jhmi.edu cwolfga2@jhmi.edu rhruban@jhmi.edu ctomasetti@jhu.edu karchin@jhu.edu.
38
Department of Radiology, Johns Hopkins University, Baltimore, MD 21287, USA.

Abstract

Pancreatic cysts are common and often pose a management dilemma, because some cysts are precancerous, whereas others have little risk of developing into invasive cancers. We used supervised machine learning techniques to develop a comprehensive test, CompCyst, to guide the management of patients with pancreatic cysts. The test is based on selected clinical features, imaging characteristics, and cyst fluid genetic and biochemical markers. Using data from 436 patients with pancreatic cysts, we trained CompCyst to classify patients as those who required surgery, those who should be routinely monitored, and those who did not require further surveillance. We then tested CompCyst in an independent cohort of 426 patients, with histopathology used as the gold standard. We found that clinical management informed by the CompCyst test was more accurate than the management dictated by conventional clinical and imaging criteria alone. Application of the CompCyst test would have spared surgery in more than half of the patients who underwent unnecessary resection of their cysts. CompCyst therefore has the potential to reduce the patient morbidity and economic costs associated with current standard-of-care pancreatic cyst management practices.

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