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Surfactant protein-D predicts prognosis of interstitial lung disease induced by anticancer agents in advanced lung cancer: a case control study

Overview of attention for article published in BMC Cancer, May 2017
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Title
Surfactant protein-D predicts prognosis of interstitial lung disease induced by anticancer agents in advanced lung cancer: a case control study
Published in
BMC Cancer, May 2017
DOI 10.1186/s12885-017-3285-6
Pubmed ID
Authors

Kota Nakamura, Motoyasu Kato, Takehito Shukuya, Keita Mori, Yasuhito Sekimoto, Hiroaki Ihara, Ryota Kanemaru, Ryo Ko, Rina Shibayama, Ken Tajima, Ryo Koyama, Naoko Shimada, Osamu Nagashima, Fumiyuki Takahashi, Shinichi Sasaki, Kazuhisa Takahashi

Abstract

Interstitial lung diseases induced by anticancer agents (ILD-AA) are rare adverse effects of anticancer therapy. However, prognostic biomarkers for ILD-AA have not been identified in patients with advanced lung cancer. Our aim was to analyze the association between serum biomarkers sialylated carbohydrate antigen Krebs von den Lungen-6 (KL-6) and surfactant protein D (SP-D), and clinical characteristics in patients diagnosed with ILD-AA. Between April 2011 and March 2016, 1224 advanced lung cancer patients received cytotoxic agents and epidermal growth factor receptor tyrosine kinase inhibitors at Juntendo University Hospital and Juntendo University Urayasu Hospital. Of these patients, those diagnosed with ILD-AA were enrolled in this case control study. ΔKL-6 and ΔSP-D were defined as the difference between the levels at the onset of ILD-AA and their respective levels prior to development of ILD-AA. We evaluated KL-6 and SP-D at the onset of ILD-AA, ΔKL-6 and ΔSP-D, the risk factors for death related to ILD-AA, the chest high resolution computed tomography (HRCT) findings, and survival time in patients diagnosed with ILD-AA. Thirty-six patients diagnosed with ILD-AA were enrolled in this study. Among them, 14 patients died of ILD-AA. ΔSP-D in the patients who died was significantly higher than that in the patients who survived. However, ΔKL-6 did not differ significantly between the two groups. Moreover, ΔSP-D in patients who exhibited diffuse alveolar damage was significantly higher than that in the other patterns on HRCT. Receiver operating characteristic curve analysis was used to set the optimal cut off value for ΔSP-D at 398 ng/mL. Survival time for patients with high ΔSP-D (≥ 398 ng/mL) was significantly shorter than that for patients with low ΔSP-D. Multivariate analysis revealed that ΔSP-D was a significant prognostic factor of ILD-AA. This is the first research to evaluate high ΔSP-D (≥ 398 ng/mL) in patients with ILD-AA and to determine the risk factors for ILD-AA in advanced lung cancer patients. ΔSP-D might be a serum prognostic biomarker of ILD-AA. Clinicians should evaluate serum SP-D during chemotherapy and should carefully monitor the clinical course in patients with high ΔSP-D.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 20%
Professor 2 13%
Student > Bachelor 2 13%
Student > Master 2 13%
Student > Ph. D. Student 1 7%
Other 1 7%
Unknown 4 27%
Readers by discipline Count As %
Medicine and Dentistry 2 13%
Immunology and Microbiology 1 7%
Business, Management and Accounting 1 7%
Nursing and Health Professions 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Other 5 33%
Unknown 4 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 March 2018.
All research outputs
#14,015,608
of 15,894,908 outputs
Outputs from BMC Cancer
#4,685
of 5,901 outputs
Outputs of similar age
#242,200
of 279,842 outputs
Outputs of similar age from BMC Cancer
#1
of 2 outputs
Altmetric has tracked 15,894,908 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,901 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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