Evidence map›Paper›PMID 36143086›Full record

ArticleJournal of clinical medicine2022

Development and Multicenter Validation of a Novel Immune-Inflammation-Based Nomogram to Predict Survival in Western Resectable Gastric and Gastroesophageal Junction Adenocarcinoma (GEA): The NOMOGAST.

Massimiliano Salati, Nicola De Ruvo, Mariano Cesare Giglio, Lorena Sorrentino, Giuseppe Esposito, Sara Fenocchi, Giovanni Cucciarrè, Francesco Serra, Elena Giulia Rossi, Giovanni Vittimberga and 11 more

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 49% of its field
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

3 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
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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

21 authors at 4 institutions in 1 country.

Massimiliano SalatiDivision of Oncology, Department of Oncology and Hematology, University Hospital of Modena, 41125 Modena, Italy.
Nicola De RuvoGeneral, Oncological and Emergency Surgery Unit, University Hospital of Modena, 41125 Modena, Italy.
Mariano Cesare GiglioDivision of Hepato-Bilio-Pancreatic, Minimally Invasive and Robotic Surgery, Federico II University Hospital, 80131 Naples, Italy.
Lorena SorrentinoGeneral, Oncological and Emergency Surgery Unit, University Hospital of Modena, 41125 Modena, Italy.ORCID 0000-0001-8551-9394
Giuseppe EspositoGeneral, Oncological and Emergency Surgery Unit, University Hospital of Modena, 41125 Modena, Italy.
Sara FenocchiGeneral, Oncological and Emergency Surgery Unit, University Hospital of Modena, 41125 Modena, Italy.
Giovanni CucciarrèGeneral, Oncological and Emergency Surgery Unit, University Hospital of Modena, 41125 Modena, Italy.
Francesco SerraGeneral, Oncological and Emergency Surgery Unit, University Hospital of Modena, 41125 Modena, Italy.ORCID 0000-0002-2701-4387
Elena Giulia RossiGeneral, Oncological and Emergency Surgery Unit, University Hospital of Modena, 41125 Modena, Italy.
Giovanni VittimbergaGeneral Surgery and Advanced Oncological Therapy Unit, AUSL Romagna Forlì Hospital, 47100 Forlì, Italy.
Giorgia RadiGeneral Surgery and Advanced Oncological Therapy Unit, AUSL Romagna Forlì Hospital, 47100 Forlì, Italy.
Leonardo SolainiGeneral Surgery and Advanced Oncological Therapy Unit, AUSL Romagna Forlì Hospital, 47100 Forlì, Italy.
Paolo MorgagniGeneral Surgery and Advanced Oncological Therapy Unit, AUSL Romagna Forlì Hospital, 47100 Forlì, Italy.
Giulia GrizziDivision of Oncology, Department of Oncology, ASST di Cremona, Hospital of Cremona, 26100 Cremona, Italy.
Margherita RattiDivision of Oncology, Department of Oncology, ASST di Cremona, Hospital of Cremona, 26100 Cremona, Italy.
Fabio GelsominoDivision of Oncology, Department of Oncology and Hematology, University Hospital of Modena, 41125 Modena, Italy.
Andrea SpallanzaniDivision of Oncology, Department of Oncology and Hematology, University Hospital of Modena, 41125 Modena, Italy.ORCID 0000-0001-6955-7139
Michele GhidiniMedical Oncology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy.ORCID 0000-0001-5435-1218
Giorgio ErcolaniGeneral Surgery and Advanced Oncological Therapy Unit, AUSL Romagna Forlì Hospital, 47100 Forlì, Italy.
Massimo DominiciDivision of Oncology, Department of Oncology and Hematology, University Hospital of Modena, 41125 Modena, Italy.
Roberta GelminiGeneral, Oncological and Emergency Surgery Unit, University Hospital of Modena, 41125 Modena, Italy.ORCID 0000-0002-8471-710X
University of Modena and Reggio Emilia · ITIstituti Ospitalieri di Cremona · ITFederico II University Hospital · ITFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background. More than 50% of operable GEA relapse after curative-intent resection. We aimed at externally validating a nomogram to enable a more accurate estimate of individualized risk in resected GEA. Methods. Medical records of a training cohort (TC) and a validation cohort (VC) of patients undergoing radical surgery for c/uT2-T4 and/or node-positive GEA were retrieved, and potentially interesting variables were collected. Cox proportional hazards in univariate and multivariate regressions were used to assess the effects of the prognostic factors on OS. A graphical nomogram was constructed using R software’s package Regression Modeling Strategies (ver. 5.0-1). The performance of the prognostic model was evaluated and validated. Results. The TC and VC consisted of 185 and 151 patients. ECOG:PS > 0 (p < 0.001), angioinvasion (p < 0.001), log (Neutrophil/Lymphocyte ratio) (p < 0.001), and nodal status (p = 0.016) were independent prognostic values in the TC. They were used for the construction of a nomogram estimating 3- and 5-year OS. The discriminatory ability of the model was evaluated with the c-Harrell index. A 3-tier scoring system was developed through a linear predictor grouped by 25 and 75 percentiles, strengthening the model’s good discrimination (p < 0.001). A calibration plot demonstrated a concordance between the predicted and actual survival in the TC and VC. A decision curve analysis was plotted that depicted the nomogram’s clinical utility. Conclusions. We externally validated a prognostic nomogram to predict OS in a joint independent cohort of resectable GEA; the NOMOGAST could represent a valuable tool in assisting decision-making. This tool incorporates readily available and inexpensive patient and disease characteristics as well as immune-inflammatory determinants. It is accurate, generalizable, and clinically effectivex.

Indexed as

gastric cancernomogramprognosis

Identifiers

PMID36143086
PMCPMC9500991
OpenAlexW4296295839

What OpenQuestion holds

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LicenceCC BY
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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.