Evidence map›Paper›PMID 40831611›Full record

ArticleAsia-Pacific journal of oncology nursing2025

Development and validation of an early warning model for postoperative reflux in patients with esophageal cancer.

Xueying Sun, Lirong Wei, Yuqing Zhao, Qian Bai, Na Cao, Sihan Liu, Huixia Li

Abstract read
In one paragraph

Article in Asia-Pacific journal of oncology nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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.

Xueying SunEsophageal Oncology Department, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Lirong WeiEsophageal Oncology Department, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Yuqing ZhaoEsophageal Oncology Department, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Qian BaiEsophageal Oncology Department, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Na CaoEsophageal Oncology Department, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Sihan LiuEsophageal Oncology Department, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Huixia LiEsophageal Oncology Department, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop and validate a predictive model for assessing the risk of postoperative reflux in patients with esophageal cancer. Methods: A total of 278 postoperative patients with esophageal cancer admitted between January and December 2022 were enrolled as the modeling cohort. An independent cohort of 120 patients admitted between January and April 2023 was used for external validation. Logistic regression analysis was performed to construct the risk prediction model. Model performance was evaluated in terms of discrimination, calibration, and goodness-of-fit. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC), calibration was examined using calibration plots generated by 1000 bootstrap resamples, and the Hosmer-Lemeshow goodness-of-fit test was applied ( Results: The incidence of postoperative reflux in the modeling cohort was 36.3%. The AUC was 0.813 (95% CI: 0.762-0.864) in the modeling cohort and 0.820 (95% CI: 0.747-0.894) in the validation cohort, indicating good discriminative ability. The Hosmer-Lemeshow test showed Conclusions: The developed early warning model demonstrates acceptable predictive performance for identifying postoperative reflux risk in patients with esophageal cancer. It may assist clinicians in early risk assessment and individualized intervention, although further external validation is warranted prior to clinical implementation.

Indexed as

Early warning modelEsophageal cancerLogistic regressionPostoperative refluxRisk prediction

Identifiers

PMID40831611
PMCPMC12358671

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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.