Evidence map›Paper›PMID 39885043›Full record

ArticleAnnals of surgical oncology2025

Positive Lymph Node Status Before and After Neoadjuvant Chemoradiotherapy Improves Prediction of Disease-Free Survival in Esophageal Squamous Cell Carcinoma Patients.

Xu Huang, Zitao Jian, Runze You, Hao Yin, Dongxian Jiang, Wenyi Xu, Zhiyun Duan, Heng Jiao, Shuyi Yang, Qingle Wang and 8 more

Abstract read
PubMed Publisher
In one paragraph

Article in Annals of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. European journal of nuclear medicine and molecular imaging · 2026
    Article
  3. Article
  4. 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

18 authors.

Xu Huang *Departments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Zitao Jian *Departments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Runze You *Departments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Hao YinDepartments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Dongxian JiangCancer Center, Zhongshan Hospital, Fudan University, Shanghai, China.
Wenyi XuDepartments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Zhiyun DuanDepartments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Heng JiaoDepartments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Shuyi YangCancer Center, Zhongshan Hospital, Fudan University, Shanghai, China.
Qingle WangCancer Center, Zhongshan Hospital, Fudan University, Shanghai, China.
Zhaochong ZengCancer Center, Zhongshan Hospital, Fudan University, Shanghai, China.
Hong FanDepartments of Thoracic, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
Hongbo XuDepartment of Cardiothoracic Surgery, Lu'an Affiliated Hospital of Anhui Medical University, Anhui, China.
Jun YinDepartments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Yingyong HouCancer Center, Zhongshan Hospital, Fudan University, Shanghai, China.
Han TangDepartments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China. tang.han@zs-hospital.sh.cn.
Lijie TanDepartments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China. tan.lijie@zs-hospital.sh.cn.
Miao LinDepartments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China. lin.miao@zs-hospital.sh.cn.

Funding

National Natural Science Foundation of China 81902396Zhongshan Hospital 2020ZSLC5Zhongshan Hospital 2021ZSYQ27
6 · The paper itself

Abstract

backgroundThis study proposes a modified lymph node (LN) staging category (BALN) on the basis of the number of positive LNs before (prepN) and after (ypN) neoadjuvant chemoradiotherapy (nCRT) to improve prognostic stratification in esophageal squamous cell carcinoma (ESCC). PATIENTS AND

methodsA total of 381 patients with ESCC who underwent nCRT at three medical centers were retrospectively enrolled. The ypN categories were scored according to the eighth edition of the American Joint Committee of Cancer (AJCC) staging manual. LNs with regression changes or vital tumor cells were used for interpretation of the prepN stage, reflecting the estimated number of originally involved LNs. BALN category was organized on the basis of the sum of the number of positive LNs in prepN and ypN categories.

resultsBALN category revealed clearer survival classification and prognostic value of disease-free survival (DFS) in patients with ESCC (p < 0.0001). Multivariate cox proportional risk model identified BALN stage as a significant risk factor of DFS of patients with ESCC (p < 0.001). The results of 5-year time-area under the curve (AUC) demonstrated better predictive ability of the BALN category than the ypN category (AUC 0.755 versus 0.707, p = 0.004). The rypTNM system based on BALN category exhibited comparable survival discrimination and better predictive performance than ypTNM system (AUC 0.799 versus 0.756, p = 0.020).

conclusionsThe BALN stage and the revised ypTNM system showed preferable prognosis outcomes to the ypN stage and the ypTNM system, respectively. Evaluating LN status before and after nCRT could allow for more accurate esophageal cancer staging.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsCarcinoma, Squamous CellChemoradiotherapyChemoradiotherapy, AdjuvantEsophageal NeoplasmsLymph NodesNeoadjuvant TherapyAdultAgedDisease-Free SurvivalEsophageal Squamous Cell CarcinomaFemaleFollow-Up StudiesHumansLymphatic MetastasisMaleBALN stageEsophageal cancerLymph node statusNeoadjuvant therapyPrognosis

Identifiers

PMID39885043

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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.