Evidence map›Paper›PMID 37099152›Full record

ArticleJournal of gastroenterology2023

Machine learning-based model for prediction and feature analysis of recurrence in pancreatic neuroendocrine tumors G1/G2.

Masatoshi Murakami, Nao Fujimori, Kohei Nakata, Masafumi Nakamura, Shinichi Hashimoto, Hiroshi Kurahara, Kazuyoshi Nishihara, Toshiya Abe, Shunpei Hashigo, Naotaka Kugiyama and 24 more

Abstract readMulticenter Study
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In one paragraph

Article in Journal of gastroenterology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

34 authors.

Masatoshi MurakamiDepartment of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-Ku, Fukuoka, 812-8582, Japan.
Nao FujimoriDepartment of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-Ku, Fukuoka, 812-8582, Japan. fujimori.nao.239@m.kyushu-u.ac.jp.ORCID 0000-0003-4286-8804
Kohei NakataDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Masafumi NakamuraDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Shinichi HashimotoDigestive and Lifestyle Diseases, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.
Hiroshi KuraharaDepartment of Digestive Surgery, Breast and Thyroid Surgery, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.
Kazuyoshi NishiharaDepartment of Surgery, Kitakyushu Municipal Medical Center, Kitakyushu, Japan.
Toshiya AbeDepartment of Surgery, Kitakyushu Municipal Medical Center, Kitakyushu, Japan.
Shunpei HashigoDepartment of Gastroenterology and Hepatology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Naotaka KugiyamaDepartment of Gastroenterology and Hepatology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Eisuke OzawaDepartment of Gastroenterology and Hepatology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan.
Kazuhisa OkamotoDepartment of Gastroenterology, Faculty of Medicine, Oita University, Oita, Japan.
Yusuke IshidaDepartment of Gastroenterology and Medicine, Faculty of Medicine, Fukuoka University, Fukuoka, Japan.
Keiichi OkanoDepartment of Gastroenterological Surgery, Faculty of Medicine, Kagawa University, Kita-gun, Japan.
Ryo TakakiDepartment of Gastroenterology, Urasoe General Hospital, Urasoe, Japan.
Yutaka ShimamatsuDivision of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Kurume, Japan.
Tetsuhide ItoNeuroendocrine Tumor Centre, Fukuoka Sanno Hospital, Fukuoka, Japan.
Masami MikiDepartment of Gastroenterology, National Hospital Organization Kyushu Cancer Center, Fukuoka, Japan.
Noriko OzaDepartment of Hepato-Biliary-Pancreatology, Saga-Ken Medical Centre Koseikan, Saga, Japan.
Daisuke YamaguchiDepartment of Gastroenterology, National Hospital Organization Ureshino Medical Center, Ureshino, Japan.
Hirofumi YamamotoDepartment of Surgery, Hamanomachi Hospital, Fukuoka, Japan.
Hironobu TakedomiDivision of Gastroenterology, Department of Internal Medicine, Faculty of Medicine, Saga University, Saga, Japan.
Ken KawabeDepartment of Gastroenterology, National Hospital Organization Kyushu Medical Center, Fukuoka, Japan.
Tetsuro AkashiDepartment of Internal Medicine, Saiseikai Fukuoka General Hospital, Fukuoka, Japan.
Koichi MiyaharaDepartment of Internal Medicine, Karatsu Red Cross Hospital, Karatsu, Japan.
Jiro OhuchidaDepartment of Surgery, Miyazaki Prefectural Miyazaki Hospital, Miyazaki, Japan.
Yasuhiro OguraDepartment of Surgery, Fukuoka Red Cross Hospital, Fukuoka, Japan.
Yohei NakashimaDepartment of Surgery, Japan Community Health Care Organization, Kyushu Hospital, Kitakyushu, Japan.
Toshiharu UekiDepartment of Gastroenterology, Fukuoka University Chikushi Hospital, Chikushino, Japan.
Kousei IshigamiDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Hironobu UmakoshiDepartment of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-Ku, Fukuoka, 812-8582, Japan.
Keijiro UedaDepartment of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-Ku, Fukuoka, 812-8582, Japan.
Takamasa OonoDepartment of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-Ku, Fukuoka, 812-8582, Japan.
Yoshihiro OgawaDepartment of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-Ku, Fukuoka, 812-8582, Japan.

Funding

Japan Society for the Promotion of Science JP22K08079Smoking Research Foundation GAKF800505
6 · The paper itself

Abstract

backgroundPancreatic neuroendocrine neoplasms (PanNENs) are a heterogeneous group of tumors. Although the prognosis of resected PanNENs is generally considered to be good, a relatively high recurrence rate has been reported. Given the scarcity of large-scale reports about PanNEN recurrence due to their rarity, we aimed to identify the predictors for recurrence in patients with resected PanNENs to improve prognosis.

methodsWe established a multicenter database of 573 patients with PanNENs, who underwent resection between January 1987 and July 2020 at 22 Japanese centers, mainly in the Kyushu region. We evaluated the clinical characteristics of 371 patients with localized non-functioning pancreatic neuroendocrine tumors (G1/G2). We also constructed a machine learning-based prediction model to analyze the important features to determine recurrence.

resultsFifty-two patients experienced recurrence (14.0%) during the follow-up period, with the median time of recurrence being 33.7 months. The random survival forest (RSF) model showed better predictive performance than the Cox proportional hazards regression model in terms of the Harrell's C-index (0.841 vs. 0.820). The Ki-67 index, residual tumor, WHO grade, tumor size, and lymph node metastasis were the top five predictors in the RSF model; tumor size above 20 mm was the watershed with increased recurrence probability, whereas the 5-year disease-free survival rate decreased linearly as the Ki-67 index increased.

conclusionsOur study revealed the characteristics of resected PanNENs in real-world clinical practice. Machine learning techniques can be powerful analytical tools that provide new insights into the relationship between the Ki-67 index or tumor size and recurrence.

Indexed as

Neuroendocrine TumorsPancreatic NeoplasmsHumansKi-67 AntigenPrognosisRetrospective StudiesKi-67 AntigenMachine learningPancreatic neuroendocrine tumorPrediction modelRandom survival forestRecurrence

Identifiers

PMID37099152

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