ArticleWorld journal of surgical oncology2025
Primary tumor resection: a new hope or an old illusion for patients with metastatic non-small cell lung neuroendocrine tumors?
Article in World journal of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
objectivesThis study aimed to investigate the impact of primary tumor resection (PTR) on survival outcomes for patients with metastatic non-small cell neuroendocrine tumors (mNSCLC-NETs), develop a predictive model to identify which patients may benefit from surgery in terms of survival.
methodsWe extracted information on mNSCLC-NET patients from the SEER database. Propensity score matching was used to eliminate bias between surgery and non-surgery groups. The effect of PTR on prognosis was assessed via Kaplan‒Meier analysis with the log-rank test and the Cox proportional hazards model. Feature selection was performed via the Boruta algorithm. Model building utilized fivefold cross-validation and applied five machine learning algorithms. The optimal model was selected and used to construct a visual network nomogram.
resultsAmong the 1,776 eligible patients, 12.61% underwent surgery. After PSM, the surgery group showed significantly longer median overall survival (mOS) (26 months vs. 11 months) compared to the non-surgery group. Among the five machine learning models, logistic regression had the highest AUC of 0.760 on the validation set. Therefore, we used a logistic regression model to construct a nomogram. This tool identified beneficiary and non-beneficiary groups, with the former having a longer mOS (30 months vs. 10 months).
conclusionsOverall, PTR in mNSCLC-NETs could prolong patients survival, and the web-based nomogram can predict patients who may benefit from surgery. This tool may aid clinicians in patient counseling and personalized decision-making.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.