ArticleFrontiers in oncology2024
Three-year follow-up study reveals improved survival rate in NSCLC patients underwent guideline-concordant diagnosis and treatment.
Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Metabolic reprogramming and lung cancer focused on roles, mechanism, and clinical prospects of circRNAs: a narrative review.Frontiers in oncology · 2026Review
- The Saudi Thoracic Society Evidence-based guidelines for the diagnosis and management of chronic obstructive pulmonary disease.Annals of thoracic medicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: No studies in China have assessed the guideline-concordance level of the first-course of non-small cell lung cancer (NSCLC) diagnosis and treatment and its relationship with survival. This study comprehensively assesses the current status of guideline-concordant diagnosis (GCD) and guideline-concordant treatment (GCT) of NSCLC in China and explores its impact on survival. Methods: First course diagnosis and treatment data for NSCLC patients in Liaoning, China in 2017 and 2018 (n=1828) were used and classified by whether they underwent GCD and GCT according to Chinese Society of Clinical Oncology (CSCO) guidelines. Pearson's chi-squared test was used to determine unadjusted associations between categorical variables of interest. Logistic models were constructed to identify variables associated with GCD and GCT. Kaplan-Meier analysis and log-rank tests were used to estimate and compare 3-year survival rates. Multivariate Cox proportional risk models were constructed to assess the risk of cancer mortality associated with guideline-concordant diagnosis and treatment. Results: Of the 1828 patients we studied, 48.1% underwent GCD, and 70.1% underwent GCT. The proportions of patients who underwent both GCD and GCT, GCD alone, GCT alone and neither GCD nor GCT were 36.7%, 11.4%, 33.5% and 18.4%, respectively. Patients in advanced stage and non-oncology hospitals were significantly less likely to undergo GCD and GCT. Compared with those who underwent neither GCD nor GCT, patients who underwent both GCD and GCT, GCD alone and GCT alone had 35.2%, 26.7% and 35.7% higher 3-year survival rates; the adjusted lung cancer mortality risk significantly decreased by 29% (adjusted hazard ratio[aHR], 0.71; 95% CI, 0.53-0.95), 29% (aHR, 0.71; 95% CI, 0.50-1.00) and 32% (aHR, 0.68; 95% CI, 0.51-0.90). Conclusion: The 3-year risk of death is expected to be reduced by 29% if patients with NSCLC undergo both GCD and GCT. There is a need to establish an oncology diagnosis and treatment data management platform in China to monitor, evaluate, and promote the use of clinical practice guidelines in healthcare settings.
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.