Evidence map›Paper›PMID 38222966›Full record

ArticleAsia-Pacific journal of oncology nursing2024

Symptom clusters in breast cancer survivors with and without type 2 diabetes over the cancer trajectory.

Susan Storey, Xiao Luo, Jie Ren, Kun Huang, Diane Von Ah

Abstract read
In one paragraph

Article in Asia-Pacific journal of oncology nursing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Qigong in the care of breast cancer survivors with diabetes.Asia-Pacific journal of oncology nursing · 2024
    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

5 authors.

Susan StoreyIndiana University School of Nursing, Indianapolis, IN, USA.
Xiao LuoDepartment of Management Science and Information Systems, School of Business, Oklahoma State University, OK, USA.
Jie RenDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine Indianapolis, IN, USA.
Kun HuangDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine; Regenstrief Institute, Indianapolis, IN, USA.
Diane Von AhCollege of Nursing, Cancer Research, Center for Healthy Aging, Self-Management and Complex Care, The Ohio State University, Columbus, OH, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to investigate symptoms and symptom clusters in breast cancer survivors (BCS) with and without type 2 diabetes across three crucial periods during the cancer trajectory (0-6 months, 12-18 months, and 24-30 months) post-initial chemotherapy. Methods: Eight common symptoms in both BCS and individuals with diabetes were identified through natural language processing of electronic health records from January 2007 to December 2018. Exploratory factor analysis was employed to discern symptom clusters, evaluating their stability, consistency, and clinical relevance. Results: Among the 4601 BCS in the study, 20% ( Conclusions: Healthcare providers must be attentive to BCS with diabetes throughout the cancer trajectory, considering intensified and/or unique profiles of symptoms and symptom clusters. Interdisciplinary cancer survivorship models are essential for effective diabetes management in BCS. Implementing a comprehensive diabetes management program throughout the cancer trajectory could alleviate symptoms and symptom clusters, ultimately enhancing health outcomes and potentially reducing healthcare resource utilization.

Indexed as

Breast cancer survivorsCancer trajectoryElectronic health recordNatural language processingSymptom clustersType 2 diabetes

Identifiers

PMID38222966
PMCPMC10784674

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.