Evidence map›Paper›PMID 29728140›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2018

Solid component proportion is an important predictor of tumor invasiveness in clinical stage T

Meng Li, Ning Wu, Li Zhang, Wei Sun, Ying Liu, Lv Lv, Jiansong Ren, Dongmei Lin

Abstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Meng LiDepartment of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ning WuDepartment of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. cjr.wuning@vip.163.com.
Li ZhangDepartment of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wei SunDepartment of Pathology, Beijing Cancer Hospital, Beijing, China.
Ying LiuPET-CT Center, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Lv LvDepartment of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jiansong RenNational Office for Cancer Prevention and Control, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Dongmei LinDepartment of Pathology, Beijing Cancer Hospital, Beijing, China.

Funding

National key R&D Program of China 2017YFC1308700National Natural Science Foundation of China 81601494PUMC Youth Fund 2017320017PUMC Youth Fund 3332016030
6 · The paper itself

Abstract

backgroundPreoperative tumor invasiveness in clinical stage T

methodsA total of 375 surgically resected cT

resultsWe found that the GGOc proportion was positively correlated with lepidic growth pattern percentage (r = 0.67, P <  0.01), while the Sc proportion was negatively correlated with it (r = - 0.74, P <  0.01). Multivariate analysis showed that tumor size and Sc proportion were identified as independent predictors for tumor invasiveness. The area under the ROC curve (AUC) of Sc proportion was 0.875, which was higher than that of tumor size (0.750) (P <  0.001), and had no significant difference with that of combination of these two factors (0.884) (P = 0.28).

conclusionsThe GGOc/Sc proportion measured using 3D computer-quantified CT number analysis reflects the lepidic growth pattern percentage in tumors, and the Sc proportion may be an important factor for the prediction of tumor invasiveness in cT

Indexed as

AdenocarcinomaAdenocarcinoma of LungAdultAgedAged, 80 and overFemaleHumansImaging, Three-DimensionalLung NeoplasmsMaleMiddle AgedNeoplasm InvasivenessNeoplasm StagingRetrospective StudiesROC CurveTomography, X-Ray ComputedComputer tomographyCT number analysisLung adenocarcinomaNeoplasm invasivenessPositron-emission tomography

Identifiers

PMID29728140
PMCPMC5935978

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Registered trials

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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.