Cited by 7Lung Cancer Diagnosis and TreatmentLung Cancer Research StudiesOccupational and environmental lung diseases

Early Diagnosis of Lung Cancer: The Urgent Need of a Clinical Test

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Gasparri, Roberto, Guaglio, Alessandra, Spaggiari, Lorenzo·2022·Journal of Clinical Medicine

Abstract

Globally, lung cancer continues to be the leading cause of cancer death in men and women [...]

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Crossref · 10.3390/jcm11154398

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  • Without definitive tests, healthcare providers often depend on clinical judgment and broader testing approaches, sometimes resulting in diagnostic errors.

    “Without definitive tests, healthcare providers often depend on clinical judgment and broader testing approaches, sometimes resulting in diagnostic errors.”

    From Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors (2026) · cites this paper as [186]

    In the main text of “Early Diagnosis of Lung Cancer: The Urgent Need of a Clinical Test” (page not provided), the authors say adequate screening methods are lacking and describe false positives and overdiagnosis with low-dose CT. The paper does not say that providers often rely on clinical judgment or broader testing approaches, so that part of the attributed claim is unsupported. (LLM, conf=0.82)

    Experimental — accuracy not yet measured
  • There is a lack of appropriate or specific diagnostic tests for certain conditions or diseases, especially in their early stages.

    “First, there is a lack of appropriate or specific diagnostic tests for certain conditions or diseases, especially in their early stages [185,186,187].”

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References 16 · Cited by 7

Research works printed but not linked: 14

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  9. [12]Menyhárt O. Győrffy B. Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis Comput. Struct. Biotechnol. J. 2021 19 949 960 10.1016/j.csbj.2021.01.009 33613862 PMC7868685 · DOI
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  13. [17]Yu X.T. Zeng T. Integrative analysis of omics big data Methods Mol. Biol. 2018 1754 109 135 29536440
  14. [18]Lv J. Li J. Liu Y. Zhang H. Luo X. Ren M. Gao Y. Ma Y. Liang S. Yang Y. Artificial Intelligence-Aided Diagnosis Software to Identify Highly Suspicious Pulmonary Nodules Front. Oncol. 2022 11 749219 10.3389/fonc.2021.749219 35242696 PMC8886673 · DOI

Authors
Gasparri, R., Guaglio, A., & Spaggiari, L.
Affiliations
  • European Institute of Oncology (IT)
  • University of Milan (IT)
Corresponding author
Gasparri, Roberto
Venue
Journal of Clinical Medicine
Publisher
MDPI AG
Published
2022-07-28
Volume
11
Issue
15
Pages
4398
ISSN
2077-0383 (ISSN-L)
OpenAlex
W4288442929
Cited by
7
References
16
Citations by year
2026: 1 · 2024: 2 · 2023: 3 · 2022: 1
Type
journal article
Language
en
Open access
Locations
  • Journal of Clinical Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
  • Health Sciences › Medicine › Oncology › Lung Cancer Research Studies
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Occupational and environmental lung diseases
Keywords
lung cancer, early diagnosis, clinical diagnostic tests, cancer screening, cancer mortality

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