Evidence map›Paper›PMID 36620591›Full record

ArticleFrontiers in oncology2022

The significance of time interval between perioperative SOX/XELOX chemotherapy and clinical decision model in gastric cancer.

Jun-Bing Chen, Zi-Ning Liu, Yin-Kui Wang, Fei Shan, Shuang-Xi Li, Yong-Ning Jia, Kan Xue, Ru-Lin Miao, Zhe-Min Li, Zhou-Qiao Wu and 4 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Jun-Bing ChenKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Zi-Ning LiuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Yin-Kui WangKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Fei ShanKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Shuang-Xi LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Yong-Ning JiaKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Kan XueKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Ru-Lin MiaoKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Zhe-Min LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Zhou-Qiao WuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Xiang-Ji YingKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Yan ZhangKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Zi-Yu LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.
Jia-Fu JiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: To investigate the influences of time interval between multimodality therapies on survival for locally advanced gastric cancer (LAGC) patients, 627 patients were included in a retrospective study, and 350 who received neoadjuvant chemotherapy (NACT) based on SOX (S-1 plus Oxaliplatin)/XELOX (Capecitabine plus Oxaliplatin) treatment, radical surgery, and adjuvant chemotherapy (AC) from 2005.01 to 2018.06 were eligible for analyses. Methods: Three factors were used to assess influences, including time interval from NACT accomplishment to AC initiation (PECTI), time to surgery after NACT accomplishment (TTS), and time to adjuvant chemotherapy after surgery (TAC). Results: Concerning PECTIs, 99 (28.29%) experienced it within 9 weeks, 188 (53.71%) within 9-13 weeks, 63 (18.00%) over 13 weeks. Patients' 5-year overall survival (OS) significantly decreased as trichotomous PECTI increased (78.6% Discussion: In control of PECTI, TTS could be extended appropriately, and shortened TAC might make a remedy, and delayed TAC might be allowed when TTS was shortened.

Indexed as

adjuvant chemotherapydecision analysisgastric cancerneoadjuvant chemotherapynomogramsperioperative period

Identifiers

PMID36620591
PMCPMC9816861

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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.