Evidence map›Paper›PMID 34873937›Full record

ArticleAnnals of Saudi medicine

Early and late recurrences in lymph node-negative gastric cancer: a retrospective cohort study.

Jian-Wei Sun, Dao-Li Liu, Jia-Xian Chen, Li-Zhen Lin, Lv-Ping Zhuang, Xian-Hai Hou

Abstract read
In one paragraph

Article in Annals of Saudi medicine. 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. Article
  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

6 authors.

Jian-Wei SunFrom the Department of Surgery, Qingyang's People's Hospital, Qingyan, China.
Dao-Li LiuFrom the Department of Gastrointestinal Surgery, Anqing First People's Hospital of Anhui Medical University, Anqing, China.
Jia-Xian ChenFrom the Department of Surgery, Qingyang's People's Hospital, Qingyan, China.
Li-Zhen LinFrom the Graduate School, Fujian Medical University, Fuzhou, China.
Lv-Ping ZhuangFrom the Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Xian-Hai HouFrom the Department of Surgery, Qingyang's People's Hospital, Qingyan, China.ORCID 0000-0002-1005-1958

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPredictors of recurrence in patients with lymph node-negative gastric cancer (GC) who have undergone curative resection have been widely investigated, but not the effects of predictors on timing of recurrence.

objectiveDetermine the factors associated with early and late recurrence in patients with node-negative GC.

designRetrospective cohort.

settingAcademic tertiary care center. PATIENTS AND

methodsThe study included patients with node-negative GC after curative resection between 2008 and 2018 at two institutions. Early and late recurrences were determined using a minimum

main outcome measuresRecurrence-free survival and factors associated with survival. SAMPLE SIZE: 606.

resultsAfter a median follow-up of 70 months, 50 (8.3%) patients experienced recurrent disease. The optimal length of RFS for distinguishing between early (n=26) and late recurrence (n=24) was 24 months (

conclusionsIndividualized therapeutic and follow-up strategies should be considered in future studies because of distinct patterns in predictors of early and late recurrence. LIMITATIONS: Retrospective design, small sample size. CONFLICT OF INTEREST: None.

Indexed as

Stomach NeoplasmsCohort StudiesHumansLymphatic MetastasisLymph NodesNeoplasm Recurrence, LocalRecurrenceRetrospective Studies

Identifiers

PMID34873937
PMCPMC8650598

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.