Evidence map›Paper›PMID 38523553›Full record

Trial reportCancer medicine2024

Nomogram for predicting pathological response to neoadjuvant treatment in patients with locally advanced gastric cancer: Data from a phase III clinical trial.

Han Shao, Nai Li, Yi-Hong Ling, Ji-Jin Wang, Yi Fang, Ming Jing, Zhi-Wei Zhou, Yu-Jing Zhang

Abstract readClinical Trial, Phase III
In one paragraph

Trial report in Cancer medicine, 2024. 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
–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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
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

8 authors.

Han ShaoState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
Nai LiState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
Yi-Hong LingState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
Ji-Jin WangState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
Yi FangState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
Ming JingState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
Zhi-Wei ZhouState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.ORCID 0000-0003-1338-1220
Yu-Jing ZhangState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.ORCID 0000-0001-7236-2375

Funding

Sun Yat-sen University Clinical Research 5010 Program grant2012013
6 · The paper itself

Abstract

purposeThis study aimed to establish a nomogram using routinely available clinicopathological parameters to predict the pathological response in patients with locally advanced gastric cancer (LAGC) undergoing neoadjuvant treatment. MATERIALS AND

methodsWe conducted this study based on the ongoing Neo-CRAG trial, a prospective study focused on preoperative treatment in patients with LAGC. A total of 221 patients who underwent surgery following neoadjuvant chemotherapy (nCT) or neoadjuvant chemoradiotherapy (nCRT) at Sun Yat-sen University Cancer Center between June 2013 and July 2022 were included in the analysis. We defined complete or near-complete pathological regression and ypN0 as good response (GR), and determined the prognostic value of GR by Kaplan-Meier survival analysis. Eventually, a nomogram for predicting GR was developed based on statistically identified predictors through multivariate logistic regression analysis and internally validated by the bootstrap method.

resultsGR was confirmed in 54 patients (54/221, 24.4%). Patients who achieved GR had a longer progression-free survival and overall survival. Then, five independent factors, including pretreatment tumor differentiation, clinical T stage, monocyte count, CA724 level, and the use of nCRT, were identified. Based on these predictors, the nomogram was established with an area under the curve (AUC) of 0.777 (95% CI, 0.705-0.850) and a bias-corrected AUC of 0.752.

conclusionA good pathological response after neoadjuvant treatment was associated with an improved prognosis in LAGC patients. The nomogram we established exhibits a high predictive capability for GR, offering potential value in devising personalized and precise treatment strategies for LAGC patients.

Indexed as

NomogramsStomach NeoplasmsHumansNeoadjuvant TherapyProspective Studieslocally advanced gastric cancerNeoadjuvant treatmentnomogrampathological response

Identifiers

PMID38523553
PMCPMC10961599

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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.