Evidence map›Paper›PMID 35936739›Full record

ArticleFrontiers in oncology2022

Electrical Impedance Analysis for Lung Cancer: A Prospective, Multicenter, Blind Validation Study.

Dawei Yang, Chuanjia Gu, Ye Gu, Xiaodong Zhang, Di Ge, Yong Zhang, Ningfang Wang, Xiaoxuan Zheng, Hao Wang, Li Yang and 6 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
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

16 authors.

Dawei YangDepartment of Pulmonary Medicine and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Chuanjia GuDepartment of Respiratory Endoscopy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Ye GuDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China.
Xiaodong ZhangDepartment of Pulmonary Medicine, Nantong Tumor Hospital, Nantong, China.
Di GeDepartment of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Yong ZhangDepartment of Pulmonary Medicine and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Ningfang WangDepartment of Pulmonary Medicine and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Xiaoxuan ZhengDepartment of Respiratory Endoscopy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Hao WangDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China.
Li YangDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China.
Saihua ChenDepartment of Pulmonary Medicine, Nantong Tumor Hospital, Nantong, China.
Pengfei XieDepartment of Pulmonary Medicine, Nantong Tumor Hospital, Nantong, China.
Deng ChenKey Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai, China.
Jinming YuKey Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai, China.
Jiayuan SunDepartment of Respiratory Endoscopy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Chunxue BaiDepartment of Pulmonary Medicine and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypothesis: Patients with cancer have different impedances or conductances than patients with benign normal tissue; thus, we can apply electrical impedance analysis (EIA) to identify patients with cancer. Method: To evaluate EIA's efficacy and safety profile in diagnosing pulmonary lesions, we conducted a prospective, multicenter study among patients with pulmonary lesions recruited from 4 clinical centers (Zhongshan Hospital Ethics Committee, Approval No. 2015-16R and 2017-035(3). They underwent EIA to obtain an Algorithm Composite Score or 'Prolung Index,' PI. The classification threshold of 29 was first tested in an analytical validation set of 144 patients and independently validated in a clinical validation set of 418 patients. The subject's final diagnosis depended on histology and a 2-year follow-up. Results: In total, 418 patients completed the entire protocol for clinical validation, with 186 true positives, 145 true negatives, 52 false positives, and 35 false negatives. The sensitivity, specificity, and diagnostic yield were 84% (95% CI 79.3%-89.0%), 74% (95% CI 67.4%-79.8%), and 79% (95%CI 75.3%-83.1%), respectively, and did not differ according to age, sex, smoking history, body mass index, or lesion types. The sensitivity of small lesions was comparable to that of large lesions ( Conclusion: Electrical impedance analysis is a safe and efficient tool for risk stratification of pulmonary lesions, especially for patients with a suspicious lung lesion.

Indexed as

diagnosiselectrical impedancelung cancerprospectivepulmonary nodules

Identifiers

PMID35936739
PMCPMC9348894

What Socratic holds

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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 Socratic graph.