Evidence map›Paper›PMID 38316730›Full record

ArticleBrain imaging and behavior2024

Uncovering brain functional connectivity disruption patterns of lung cancer-related pain.

Xiaotong Wei, Yong Lai, Xiaosong Lan, Yong Tan, Jing Zhang, Jiang Liu, Jiao Chen, Chengfang Wang, Xiaoyu Zhou, Yu Tang and 2 more

Abstract read
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In one paragraph

Article in Brain imaging and behavior, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Xiaotong Wei *Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Yong Lai *Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Xiaosong LanDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Yong TanDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Jing ZhangDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Jiang LiuDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Jiao ChenDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Chengfang WangDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Xiaoyu ZhouDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Yu TangDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China.
Daihong LiuDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China. liudaihong121@163.com.
Jiuquan ZhangDepartment of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Hanyu Road No. 181, Shapingba District, Chongqing, 400030, China. zhangjq_radiol@foxmail.com.

Funding

National Natural Science Foundation of China 82371937Natural Science Foundation of Chongqing CSTB2022NSCQ-MSX0396Natural Science Foundation of Chongqing cstc2021jcyj-msxmX0313Natural Science Foundation of Chongqing cstc2021jcyj-msxmX0319
6 · The paper itself

Abstract

Pain is a pervasive symptom in lung cancer patients during the onset of the disease. This study aims to investigate the connectivity disruption patterns of the whole-brain functional network in lung cancer patients with cancer pain (CP+). We constructed individual whole-brain, region of interest (ROI)-level functional connectivity (FC) networks for 50 CP+ patients, 34 lung cancer patients without pain-related complaints (CP-), and 31 matched healthy controls (HC). Then, a ROI-based FC analysis was used to determine the disruptions of FC among the three groups. The relationships between aberrant FCs and clinical parameters were also characterized. The ROI-based FC analysis demonstrated that hypo-connectivity was present both in CP+ and CP- patients compared to HC, which were particularly clustered in the somatomotor and ventral attention, frontoparietal control, and default mode modules. Notably, compared to CP- patients, CP+ patients had hyper-connectivity in several brain regions mainly distributed in the somatomotor and visual modules, suggesting these abnormal FC patterns may be significant for cancer pain. Moreover, CP+ patients also showed increased intramodular and intermodular connectivity strength of the functional network, which could be replicated in cancer stage IV and lung adenocarcinoma. Finally, abnormal FCs within the prefrontal cortex and somatomotor cortex were positively correlated with pain intensity and pain duration, respectively. These findings suggested that lung cancer patients with cancer pain had disrupted connectivity in the intrinsic brain functional network, which may be the underlying neuroimaging mechanisms.

Indexed as

BrainCancer PainLung NeoplasmsMagnetic Resonance ImagingNeural PathwaysAdultAgedBrain MappingConnectomeFemaleHumansMaleMiddle AgedNerve NetCancer painFunctional connectivityFunctional moduleResting-state fMRI

Identifiers

PMID38316730

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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.