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Cited by 935

The DOI matches its Crossref record; 133 of the 133 references it cites were found in a registry or an index.

Progress and prospects of early detection in lung cancer

Open access
Blandin Knight, Sean, Crosbie, Phil A., Balata, Haval, Chudziak, Jakub, Hussell, Tracy, Dive, Caroline·2017·Open Biology

Abstract

Lung cancer is the leading cause of cancer-related death in the world. It is broadly divided into small cell (SCLC, approx. 15% cases) and non-small cell lung cancer (NSCLC, approx. 85% cases). The main histological subtypes of NSCLC are adenocarcinoma and squamous cell carcinoma, with the presence of specific DNA mutations allowing further molecular stratification. If identified at an early stage, surgical resection of NSCLC offers a favourable prognosis, with published case series reporting 5-year survival rates of up to 70% for small, localized tumours (stage I). However, most patients (approx. 75%) have advanced disease at the time of diagnosis (stage III/IV) and despite significant developments in the oncological management of late stage lung cancer over recent years, survival remains poor. In 2014, the UK Office for National Statistics reported that patients diagnosed with distant metastatic disease (stage IV) had a 1-year survival rate of just 15–19% compared with 81–85% for stage I.

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Metadata

Authors
Blandin Knight, S., Crosbie, P. A., Balata, H., Chudziak, J., Hussell, T., & Dive, C.
Venue
Open Biology
Published
2017-09
Volume
7
Issue
9
ISSN
2046-2441 (ISSN-L)
OpenAlex
W2752625590
Cited by
935
References
133
FWCI
43.33
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Progress and prospects of early detection in lung cancer. https://app.cochat.ai/papers/10.1098/rsob.170070
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Blandin Knight, S., Crosbie, P. A., Balata, H., Chudziak, J., Hussell, T., & Dive, C. (2017). Progress and prospects of early detection in lung cancer. Open Biology. https://doi.org/10.1098/rsob.170070

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.