Evidence map›Paper›PMID 31663905›Full record

ArticleClinical and translational gastroenterology2019

Development and Validation of a Nomogram for Early Detection of Malignant Gallbladder Lesions.

Mingyu Chen, Jiasheng Cao, Yang Bai, Chenhao Tong, Jian Lin, Vishal Jindal, Leandro Cardoso Barchi, Silvio Nadalin, Sherry X Yang, Antonio Pesce and 7 more

Abstract readValidation Study
In one paragraph

Article in Clinical and translational gastroenterology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

17 authors.

Mingyu ChenDepartment of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University, Hangzhou, China.
Jiasheng CaoDepartment of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University, Hangzhou, China.
Yang BaiDepartment of General Surgery, Jinhua Municipal Central Hospital, Jinhua, China.
Chenhao TongDepartment of General Surgery, Shaoxing People's Hospital, Zhejiang University, Shaoxing, China.
Jian LinDepartment of General Surgery, Longyou People's Hospital, Quzhou, China.
Vishal JindalDepartment of Internal Medicine, St. Vincent Hospital, Worcester, Massachusetts, USA.
Leandro Cardoso BarchiDigestive Surgery Division, Department of Gastroenterology, University of Sao Paulo School of Medicine, São Paulo, Brazil.
Silvio NadalinDepartment of General, Visceral and Transplant Surgery, University Hospital Tuebingen, Tuebingen, Germany.
Sherry X YangNational Clinical Target Validation Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Antonio PesceDepartment of Medical and Surgical Sciences and Advanced Technologies "G.F. Ingrassia" Policlinico-Vittorio Emanuele Hospital, Unit of General Surgery, University of Catania, Catania, Italy.
Fabrizio PanaroDivision of Transplantation, Department of General Surgery, University of Montpellier-College of Medicine, Saint Eloi Hospital, Montpellier, France.
Arie AricheDepartment of Surgery, Hadassah Medical Center, Mount Scopus, Jerusalem, Israel.
Keita KaiDepartment of Pathology, Saga University Hospital, Saga, Japan.
Riccardo MemeoDepartment of Emergency and Organ Transplantation, General Surgery and Transplantation, University Aldo Moro of Bari, Bari, Italy.
Tanios Bekaii-SaabMedical Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Xiujun CaiDepartment of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University, Hangzhou, China.
Written on behalf of the AME Gallbladder Cancer Collaborative Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPreoperative decision-making for differentiating malignant from benign lesions in the gallbladder remains challenging. We aimed to create a diagnostic nomogram to identify gallbladder cancer (GBC), especially for incidental GBC (IGBC), before surgical resection.

methodsA total of 587 consecutive patients with pathologically confirmed gallbladder lesions from a hospital were randomly assigned to a training cohort (70%) and an internal validation cohort (30%), with 287 patients from other centers as an external validation cohort. Radiological features were developed by the least absolute shrinkage and selection operator logistic regression model. Significant radiological features and independent clinical factors, identified by multivariate analyses, were used to construct a nomogram.

resultsA diagnostic nomogram was established by age, CA19.9, and 6 radiological features. The values of area under the curve in the internal and external validation cohorts were up to 0.91 and 0.89, respectively. The calibration curves for probability of GBC showed optimal agreement between nomogram prediction and actual observation. Compared with previous methods, it demonstrated superior sensitivity (91.5%) and accuracy (85.1%) in the diagnosis of GBC. The accuracy using the nomogram was significantly higher in GBC groups compared with that by radiologists in the training cohort (P < 0.001) and similarly in each cohort. Notably, most of the IGBC, which were misdiagnosed as benign lesions, were successfully identified using this nomogram. DISCUSSION: A novel nomogram provides a powerful tool for detecting the presence of cancer in gallbladder masses, with an increase in accuracy and sensitivity. It demonstrates an unprecedented potential for IGBC identification.

Indexed as

NomogramsAdultAgedAged, 80 and overCA-19-9 AntigenCystectomyEarly Detection of CancerFemaleGallbladderGallbladder NeoplasmsHumansMaleMiddle AgedMultivariate AnalysisPreoperative PeriodRetrospective StudiesCA-19-9 Antigen

Identifiers

PMID31663905
PMCPMC6884352

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.