Evidence map›Paper›PMID 40191622›Full record

ArticleJournal of pain research2025

Latent Profile Analysis of Pain Catastrophizing in Post-Operative Lung Cancer Patients.

Xinyan Wu, Tao Xu, Ping Cai, Siwen Shen, Mengchen Ji, Qing Liu, Xiaobo Wang, Mingqi Zhang, Shiming Wang, Danfeng Gu

Abstract read
In one paragraph

Article in Journal of pain research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Pain catastrophizing, pain acceptance, and pain intensity among patients with cancer in Oman and Lebanon: a comparative cross-sectional study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  2. Article
  3. Article
  4. Exploring the relationship between postoperative psychological resilience and symptom burden in esophageal cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Xinyan WuAffiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.ORCID 0009-0002-9836-5536
Tao XuJiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.
Ping CaiAffiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.
Siwen ShenAffiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.
Mengchen JiAffiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.
Qing LiuHuadong Sanatorium, Wuxi, Jiangsu, 214122, People's Republic of China.
Xiaobo WangJiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.ORCID 0009-0004-6138-4973
Mingqi ZhangJiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.
Shiming Wang *Wuxi Branch of Zhongda Hospital Southeast University, Wuxi, Jiangsu, 214122, People's Republic of China.
Danfeng Gu *Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with lung cancer often experience high levels of pain and recurrent pain episodes after thoracoscopic surgery, compromising their adherence to rehabilitation exercises and quality of life. Pain catastrophizing is defined as an exaggerated and negative mindset towards actual or anticipated pain and is one of the significant factors influencing pain. To date, prior investigations on pain catastrophizing have predominantly employed variable-centered approaches, focusing on broader population levels while neglecting individual specificity. Latent profile analysis represents an individual-centered data analysis method that can accurately identify distinct phenotypic subgroups and deeply analyze the characteristics of each subgroup. This enables clinicians to identify high-risk patients early and provide precision interventions to reduce pain catastrophizing and ultimately alleviate postoperative pain burden. Stratification-guided interventions play a crucial role in treating patients with pain catastrophizing, aligning with the principles of precision medicine. Methods: 409 patients were included in this cross-sectional study. Latent profile analysis (LPA) was employed to discern distinct classes of pain catastrophizing among these patients. Chi-square tests, ANOVA, and multinomial logistic regression were conducted to analyze the factors influencing the different pain catastrophizing profiles among patients following thoracoscopic lung cancer surgery. Results: Three distinct latent classes of pain catastrophizing were identified, Class1, labeled "Mild Pain Catastrophizing-Rumination Type"(26.2% of participants), Class2, referred to as "Moderate Pain Catastrophizing-Ruminative Exaggerative Type"(33.2%), Class3, designated as "Severe Pain Catastrophizing-Ruminative Helpless Exaggerative Type"(40.6%). Unordered multinomial logistic regression analysis indicated that factors influencing mild pain catastrophizing included fatigue, perception of social support, marital status, primary caregiver, tumor location, and clinical stage. In contrast, factors influencing moderate pain catastrophizing included fatigue, perception of social support, marital status, education level, primary caregiver, and clinical stage ( Conclusion: Three distinct patterns of pain catastrophizing were identified in patients following lung cancer surgery, each exhibiting unique classification characteristics. Healthcare professionals should promptly identify individuals at high risk for pain catastrophizing and develop targeted interventions that address physiological, psychological, and social factors.

Indexed as

latent profile analysispain catastrophizingthoracic surgeryvideo-assisted

Identifiers

PMID40191622
PMCPMC11971992

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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.