Evidence map›Paper›PMID 40529733›Full record

ArticleJournal of thoracic disease2025

Enhancing survival in locally advanced esophageal cancer: a comparative analysis of neoadjuvant immunotherapy versus conventional neoadjuvant therapies using the SEER database.

Qinyong Tian, Jingping Lin, Liudan Hu, Yimin Lin, Dingzhu Chen, Rongqiang Shen, Yi Zhang, Jinxin Xu, Lihua Chen

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. 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.

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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

9 authors.

Qinyong Tian *Department of Cardiothoracic Surgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China.
Jingping Lin *The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Liudan Hu *Department of Gastroenterology, Zhangzhou Traditional Chinese Medicine Hospital, Zhangzhou, China.
Yimin LinDepartment of Cardiothoracic Surgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China.
Dingzhu ChenDepartment of Cardiothoracic Surgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China.
Rongqiang ShenDepartment of Cardiothoracic Surgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China.
Yi ZhangDepartment of Cardiothoracic Surgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China.
Jinxin XuDepartment of Thoracic Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Lihua ChenDepartment of Medical Oncology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Neoadjuvant immune checkpoint inhibitors (ICIs) for locally advanced esophageal cancer have drawn significant research interest. We used the Surveillance, Epidemiology, and End Results (SEER) database to explore survival benefits of neoadjuvant immunotherapy (NAI) in this group. Methods: A comprehensive analysis was conducted utilizing the SEER database to assess the efficacy of NAI in conjunction with surgery compared to traditional neoadjuvant therapy. The study encompassed clinical and pathological characteristics as well as survival statistics of patients diagnosed with locally advanced resectable esophageal cancer between 2004 and 2014, and from 2019 to 2020. Patient data were categorized into NAI group and conventional neoadjuvant therapy (CNAT) group. Overall survival (OS) and cancer-specific survival (CSS) were evaluated using Kaplan-Meier analysis, Cox regression models, propensity score matching (PSM), and inverse probability of treatment weighting (IPTW). Results: A total of 3,708 eligible patients were included in this study, among whom 944 received NAI and 2,764 received CNAT. Kaplan-Meier curves demonstrated a significant improvement in OS and CSS in the NAI group compared to CNAT group (P<0.05). Further Cox regression analysis revealed sex, age, tumor size, grade, SEER summary stage, and treatment modality as independent prognostic factors (P<0.05). Specifically, female and receipt of NAI were associated with better prognosis, while age over 65 years, tumor size exceeding 60 mm, grade III-IV, and "regional" summary stage were considered as risk factors. Subsequent subgroup analyses and interaction assessments revealed that, compared to "unmarried and others" patients and those with tumor sizes ≤60 mm, "married" patients and those with tumor sizes >60 mm experienced significantly greater survival benefits from NAI (interaction P values <0.05). The external validation cohort included 157 patients with locally advanced esophageal squamous cell carcinoma, of which 108 received neoadjuvant chemoimmunotherapy (nICT) group and 49 received neoadjuvant chemotherapy (nCT group). Univariate and multivariate Cox regression analyses identified treatment group [hazard ratio (HR): 0.466, 95% confidence interval (CI): 0.225-0.962, P=0.04] as an independent predictor of OS. Conclusions: The combination of NAI with surgical intervention significantly improved survival outcomes in patients with locally advanced esophageal cancer. These findings support the integration of immunotherapeutic agents into neoadjuvant treatment, offering promising directions for future clinical strategies and research in the management of esophageal cancer.

Indexed as

cancer-specific survival (CSS)Esophageal cancer (EC)neoadjuvant immunotherapy (NAI)overall survival (OS)Surveillance, Epidemiology, and End Results database (SEER database)

Identifiers

PMID40529733
PMCPMC12170019

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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.