ArticleOncoTargets and therapy2024
Prognostic Factors and Construction of Nomogram Prediction Model of Lung Cancer Patients Using Clinical and Blood Laboratory Parameters.
Article in OncoTargets and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Optimizing Surgery Strategies in Stage IB Lung Squamous Cell Carcinoma: Insights from Interpretable Machine Learning.Thoracic cancer · 2026Article
- Prognostic Value of Routine Hematological Markers and ECOG Performance in Predicting Overall Survival in Lung Cancer-A Retrospective Cohort Study and Literature Review.Journal of clinical medicine · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This work aimed to explore the prognostic risk factors of lung cancer (LC) patients and establish a line chart prediction model. Methods: A total of 322 LC patients were taken as the study subjects. They were randomly divided into a training set (n = 202) and a validation set (n = 120). Basic information and laboratory indicators were collected, and the progression-free survival (PFS) and overall survival (OS) were followed up. Single-factor and cyclooxygenase (COX) multivariate analyses were performed on the training set to construct a Nomogram prediction model, which was validated with 120 patients in the validation set, and Harrell's consistency was analyzed. Results: Single-factor analysis revealed significant differences in PFS ( Conclusion: Male gender, treatment response of PD, and SCCA > 1.6 are independent risk factors affecting the survival of LC patients. The PFS line chart model demonstrates good concordance.
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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.