ReviewJournal of clinical medicine2024
Novel Strategies for Lung Cancer Interventional Diagnostics.
Review in Journal of clinical medicine, 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.
- Target Tissue Identification Based on Image Processing for Regulating Automatic Robotic Lung Biopsy Sampler: Onsite Phantom Validation.Sensors (Basel, Switzerland) · 2026Article
- Oncogenic Mutations and the Tumor Microenvironment: Drivers of Non-Small Cell Lung Cancer Progression.Cancers · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer is a major global health issue, with 2.21 million cases and 1.80 million deaths reported in 2020. It is the leading cause of cancer death worldwide. Most lung cancers have been linked to tobacco use, with changes in cigarette composition over the years contributing to shifts in cancer types and tumor locations within the lungs. Additionally, there is a growing incidence of lung cancer among never-smokers, particularly in East Asia, which is expected to increase the global burden of the disease. The classification of non-small cell lung cancer (NSCLC) into distinct subtypes is crucial for treatment efficacy and patient safety, especially as different subtypes respond differently to chemotherapy. For instance, certain chemotherapeutic agents are more effective for adenocarcinoma than for squamous carcinoma, which has led to the exclusion of squamous carcinoma from treatments like Bevacizumab due to safety concerns. This necessitates accurate histological diagnosis, which requires sufficient tissue samples from biopsies. However, acquiring adequate tissue is challenging due to the complex nature of lung tumors, patient comorbidities, and potential complications from biopsy procedures, such as bleeding, pneumothorax, and the purported risk of local recurrence. The need for improved diagnostic techniques has led to the development of advanced technologies like electromagnetic navigation bronchoscopy (ENB), radial endobronchial ultrasound (rEBUS), and robotic bronchoscopy. ENB and rEBUS have enhanced the accuracy and safety of lung biopsies, particularly for peripheral lesions, but both have limitations, such as the dependency on the presence of a bronchus sign. Robotic bronchoscopy, which builds on ENB, offers greater maneuverability and stability, improving diagnostic yields. Additionally, new imaging adjuncts, such as Cone Beam Computed Tomography (CBCT) and augmented fluoroscopy, further enhance the precision of these procedures by providing real-time, high-resolution imaging. These advancements are crucial as lung cancer is increasingly being detected at earlier stages due to screening programs, which require minimally invasive, accurate diagnostic methods to improve patient outcomes. This review aims to provide a comprehensive overview of the current challenges in lung cancer diagnostics and the innovative technological advancements in this rapidly evolving field, which represents an increasingly exciting career path for aspiring pulmonologists.
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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.