Evidence map›Paper›PMID 38150034›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2023

Exploring the dynamics of perioperative symptom networks in colorectal cancer patients: a cross-lagged panel network analysis.

Bin Shang, Zekun Bian, Caifeng Luo, Fei Lv, Jing Wu, Shuhong Lv, Qing Wei

Abstract read
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In one paragraph

Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
4.4field-weighted citation impact, top 5% of its field
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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Mechanisms of simplified sitting Badunjin effects on symptom burden: a network-based cross-lagged analysis in advanced cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Trial
  4. Article
  5. Reconsidering the interpretation of network analysis in symptom research.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  6. Dynamic Network Analysis of Symptom Profiles and Their Expected Impact on Patients with Colorectal Cancer Receiving Postoperative Adjuvant Chemotherapy.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Symptom network in patients with colorectal cancer during the perioperative period.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  12. Article
  13. Symptom dynamics through multiphase treatment in acute myeloid leukemia: a cross-lagged panel network analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  14. Observational
  15. Core symptoms in patients with colorectal cancer receiving chemotherapy: a network analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  16. Symptom clusters and network analysis of patients with intermediate and advanced liver cancer treated with targeted immunotherapy.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Article
  17. 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

7 authors at 2 institutions in 1 country.

Bin Shang *School of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang City, Jiangsu Province, China.
Zekun Bian *School of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang City, Jiangsu Province, China.
Caifeng LuoSchool of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang City, Jiangsu Province, China. lcf0105@163.com.
Fei LvDepartment of Nursing, Jiangsu University Jingjiang College, Zhenjiang, China.
Jing WuSchool of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang City, Jiangsu Province, China.
Shuhong LvGastrointestinal Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
Qing WeiGastrointestinal Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
Jiangsu University · CNAffiliated Hospital of Jiangsu University · CN

Funding

Qinglan Project of Jiangsu Province of China Su Teacher's Letter (2023) No. 51
6 · The paper itself

Abstract

backgroundColorectal cancer incidence is on the rise, necessitating precise symptom management. However, causal relationships among symptoms have been challenging to establish due to reliance on cross-sectional data. Cross-lagged panel network (CLPN) analysis offers a solution, leveraging longitudinal data for insight.

objectiveWe employed CLPN analysis to construct symptom networks in colorectal cancer patients at three perioperative time points, aiming to identify predictive relationships and intervention opportunities.

methodsWe evaluated the prevalence and severity of symptoms throughout the perioperative period, encompassing T1 the first day of admission, T2 2-3 days postoperatively, and T3 discharge, utilizing the M. D. Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI). To identify crucial nodes in the network and explore predictive and interactive effects among symptoms, CLPNs were constructed from longitudinal data in R.

resultsThe analysis revealed a stable network, with disturbed sleep exhibiting the highest out-EI (outgoing expected influence) during T1. Distress had a sustained impact throughout the perioperative. Disturbed sleep at T1 predicted T2 bloating, fatigue, distress, and pain. T1 distress predicted T2 sadness severity. T2 distress primarily predicted T3 fatigue, disturbed sleep, changes in taste, and bloating. T2 shortness of breath predicted T3 changes in taste and loss of appetite. Furthermore, biochemical markers like RBC and ALB had notable influence on symptom clusters during T1→T2 and T2→T3, respectively.

conclusionPrioritizing disturbed sleep during T1 and addressing distress throughout the perioperative phase is recommended. Effective symptom management not only breaks the chain of symptom progression, enhancing healthcare impact, but also eases patient symptom burdens.

Indexed as

Colorectal NeoplasmsAppetiteCross-Sectional StudiesDyspneaFatigueHumansSleepColorectal cancerCross-lagged panel networkLongitudinal studyNetwork analysisPerioperative periodSymptoms network

Identifiers

PMID38150034
OpenAlexW4390271667

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.