Evidence map›Paper›PMID 40529780›Full record

ArticleJournal of thoracic disease2025

Development and validation of a prognostic model for overall survival in pN0 esophageal cancer patients after neoadjuvant chemotherapy: a SEER database-based study.

Pengjie Yang, Ting Yang, Tianlai Liu, Mengfei Sun, Jingjing Zhang, Berend J van der Wilk, Dehui Zhao, Benben Zhu

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Pengjie Yang *Department of Thoracic Surgery, Peking University Cancer Hospital (Inner Mongolia Campus)/Affiliated Cancer Hospital of Inner Mongolia Medical University, Hohhot, China.
Ting Yang *College of Pharmacy, Inner Mongolia Medical University, Hohhot, China.
Tianlai Liu *Endoscopy Center, Inner Mongolia Hospital of Peking University Cancer Hospital (Affiliated Cancer Hospital of Inner Mongolia Medical University), Hohhot, China.
Mengfei SunCollege of Pharmacy, Inner Mongolia Medical University, Hohhot, China.
Jingjing ZhangCollege of Pharmacy, Inner Mongolia Medical University, Hohhot, China.
Berend J van der WilkDepartment of Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Dehui ZhaoDepartment of Thoracic Surgery, Peking University Cancer Hospital (Inner Mongolia Campus)/Affiliated Cancer Hospital of Inner Mongolia Medical University, Hohhot, China.
Benben ZhuDepartment of Pharmacy, Peking University Cancer Hospital (Inner Mongolia Campus)/Affiliated Cancer Hospital of Inner Mongolia Medical University, Hohhot, China.ORCID https://orcid.org/0009-0005-7499-4604

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Esophageal cancer (EC) is a common malignancy globally, with neoadjuvant chemotherapy plus surgery being the standard treatment. Clinically, accurate prognosis for pN0 patients after neoadjuvant therapy remains challenging, as the traditional tumor-node-metastasis (TNM) staging system may understate the impact of lymph node dissection extent and individual clinical variables on survival. However, the impact of lymph node dissection extent on survival in patients with pN0 status following neoadjuvant therapy remains unclear. This study aimed to clarify this relationship and develop a predictive model for overall survival (OS). Methods: Using the Surveillance, Epidemiology, and End Results (SEER) database, we identified 1,393 patients with pN0 after neoadjuvant chemotherapy followed by surgery between 2007 and 2021. Baseline clinical factors (age, sex, race, tumor location, T/M stage, lymph node count, etc.) were extracted, and OS was defined as the time from diagnosis to death or last follow-up (minimum 1-month follow-up). Patients were randomly divided into a training set and validation set at a 7:3 ratio by histology [squamous cell carcinoma/adenocarcinoma (SCC/AC)]. Restricted cubic spline regression and multivariate Cox regression were used to identify lymph node dissection thresholds and independent prognostic factors. A nomogram was constructed and validated via concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results: The study cohort had a median age of 63 years, with 82.1% male and 80.4% AC. For SCC, ≥13 lymph nodes dissected was associated with improved OS [hazard ratio (HR) =0.60, 95% confidence interval (CI): 0.43-0.85], and for AC, ≥15 lymph nodes (HR =0.71, 95% CI: 0.60-0.85). Independent predictors included sex, lymph node count (SCC), and sex, age, M stage, lymph node count (AC). The nomogram achieved C-indices of 0.593 (training) and 0.677 (validation) for SCC, and 0.599 (training) and 0.634 (validation) for AC, outperforming TNM staging in 1-, 3-, 5-year OS prediction (SCC validation AUCs: 0.773, 0.678, 0.651; AC: 0.696, 0.664, 0.640). Conclusions: The findings suggest that dissecting an adequate number of lymph nodes is associated with improved survival in patients with pN0 EC. Most probably, this is due to more adequate staging of the pN-status of patients and avoidance of understaging. The nomogram provides more precise survival prediction than TNM staging, aiding personalized prognosis and treatment planning. Clinicians should prioritize achieving these lymph node dissection thresholds to optimize staging accuracy, though external validation in diverse populations is warranted.

Indexed as

Esophageal cancer (EC)neoadjuvant chemotherapypN0 statusprognostic model

Identifiers

PMID40529780
PMCPMC12170118

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.