Evidence map›Paper›PMID 35664642›Full record

ArticleComputational and mathematical methods in medicine2022

Clinical Value of PLR, MLR, and NWR in Neoadjuvant Chemotherapy for Locally Advanced Gastric Cancer.

Baojun He, Jieli Wu

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Baojun HeDepartment of Clinical Laboratory Medicine, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning 121001, China.ORCID https://orcid.org/0000-0002-3572-9892
Jieli WuDepartment of Oncology Medicine, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning 121001, China.
Jinzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The clinical value of platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-white blood cell ratio (NWR) in predicting the prognosis of patients with locally advanced gastric cancer after neoadjuvant chemotherapy (NACT) was studied. Methods: A total of 131 patients with locally advanced gastric cancer treated with neoadjuvant chemotherapy in our hospital from May 2015 to June 2018 were selected as the study subjects, and all were treated with neoadjuvant chemotherapy. The relationship between the values of PLR, MLR, and NWR and the efficacy of neoadjuvant chemotherapy and clinical staging was analyzed; all patients were followed up for 3 years. Patients were divided into death group and survival group according to the survival of patients. The predictive value of PLR, MLR, and NWR values for patients' prognosis was analyzed, and the survival rates of patients with different PLR, MLR, and NWR values were compared. Results: The effective rate of neoadjuvant chemotherapy in patients with locally advanced gastric cancer was 62.60% (82/131), and the PLR, MLR, and NWR values in the effective group were lower than those in the ineffective group ( Conclusions: PLR, MLR, and NWR values are correlated with clinical stage, and the combined detection has value in evaluating the clinical efficacy of neoadjuvant chemotherapy and predicting the prognosis of patients with locally advanced gastric cancer.

Indexed as

Neoadjuvant TherapyStomach NeoplasmsHumansLymphocytesMonocytesNeutrophilsPrognosisRetrospective Studies

Identifiers

PMID35664642
PMCPMC9162812
OpenAlexW4281686025

What OpenQuestion holds

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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.