Evidence map›Paper›PMID 32476803›Full record

Observational studyWorld journal of gastroenterology2020

Nomogram for predicting pathological complete response to neoadjuvant chemotherapy in patients with advanced gastric cancer.

Yong-He Chen, Jian Xiao, Xi-Jie Chen, Hua-She Wang, Dan Liu, Jun Xiang, Jun-Sheng Peng

Open access · hybridAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in World journal of gastroenterology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.4field-weighted citation impact, top 16% 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

21 citing papers in PubMed, 29 citations in OpenAlex.

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  12. Predictive factors for histological response to neoadjuvant therapy in gastric adenocarcinomas.Arquivos brasileiros de cirurgia digestiva : ABCD = Brazilian archives of digestive surgery · 2025
    Article
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  15. Digital histopathological images of biopsy predict response to neoadjuvant chemotherapy for locally advanced gastric cancer.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2023
    Observational
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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

7 authors at 3 institutions in 1 country.

Yong-He ChenDepartment of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China.
Jian XiaoDepartment of Medical Oncology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China.
Xi-Jie ChenDepartment of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China.
Hua-She WangDepartment of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China.
Dan LiuDepartment of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510655, Guangdong Province, China.
Jun XiangDepartment of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China.
Jun-Sheng PengDepartment of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China.
Sun Yat-sen University · CNSixth Affiliated Hospital of Sun Yat-sen University · CNGuangzhou University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurvival benefit of neoadjuvant chemotherapy (NAC) for advanced gastric cancer (AGC) is a debatable issue. Studies have shown that the survival benefit of NAC is dependent on the pathological response to chemotherapy drugs. For those who achieve pathological complete response (pCR), NAC significantly prolonged prolapsed-free survival and overall survival. For those with poor response, NAC yielded no survival benefit, only toxicity and increased risk for tumor progression during chemotherapy, which may hinder surgical resection. Thus, predicting pCR to NAC is of great clinical significance and can help achieve individualized treatment in AGC patients.

aimTo establish a nomogram for predicting pCR to NAC for AGC patients.

methodsTwo-hundred and eight patients diagnosed with AGC who received NAC followed by resection surgery from March 2012 to July 2019 were enrolled in this study. Their clinical data were retrospectively analyzed by logistic regression analysis to determine the possible predictors for pCR. Based on these predictors, a nomogram model was developed and internally validated using the bootstrap method.

resultspCR was confirmed in 27 patients (27/208, 13.0%). Multivariate logistic regression analysis showed that higher carcinoembryonic antigen level, lymphocyte ratio, lower monocyte count and tumor differentiation grade were associated with higher pCR. Concordance statistic of the established nomogram was 0.767.

conclusionA nomogram predicting pCR to NAC was established. Since this nomogram exhibited satisfactory predictive power despite utilizing easily available pretreatment parameters, it can be inferred that this nomogram is practical for the development of personalized treatment strategy for AGC patients.

Indexed as

GastrectomyNeoadjuvant TherapyNomogramsAntineoplastic Combined Chemotherapy ProtocolsCarcinoembryonic AntigenDisease-Free SurvivalDisease ProgressionFemaleFollow-Up StudiesHumansLeukocyte CountMaleMiddle AgedNeoplasm StagingStomachStomach NeoplasmsCarcinoembryonic AntigenAdvanced gastric cancerNeoadjuvant chemotherapyNomogramPathological complete response

Identifiers

PMID32476803
PMCPMC7243641
OpenAlexW3028472054

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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.