ReviewBiological research for nursing2023
The Cancer Genomic Integration Model for Symptom Science (CGIMSS): A Biopsychosocial Framework.
Review in Biological research for nursing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07481903 (Effect of Acupuncture on Psychoneurological Symptom Cluster in Breast Cancer Survivors), which is not on this map. Cited by 3 papers.
What it found
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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.
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.
Effect of Acupuncture on Psychoneurological Symptom Cluster in Breast Cancer Survivors
Who cites it
3 citing papers in PubMed.
- Genetic insights into the timing of metastasis: a secondary analysis of the Count Me In metastatic breast cancer cohort.Frontiers in cell and developmental biology · 2026Article
- Research Priorities of the Oncology Nursing Society: 2024-2027.Oncology nursing forum · 2024Article
- Psychoneurological symptom cluster trajectories in individuals treated for early-stage breast cancer.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Current nursing research has characterized symptom clusters and trajectories in individuals with breast cancer. The existing literature describes the relationship between symptoms and biological variables and the potential moderating effects of individual and social factors. The genomic profiling of breast cancer has also been an area of much recent research. Emerging evidence indicates that incorporating cancer genomics into symptom science research can aid in the prognostication of symptoms and elucidate targets for symptom management interventions. The aim of this paper is to outline a model to integrate cancer genomics into symptom science research, illustrated using breast cancer and psychoneurological (PN) symptoms as an example. We present a review of the current literature surrounding breast cancer genomics (specifically cancer genomic instability) and the biological underpinnings of the PN symptom cluster. Advances in both of these areas indicate that inflammation may serve as the bridge between cancer genomics and the PN symptom cluster. We also outline how the integration of cancer genomics into symptom science research synergizes with current research of individual and social factors in relation to symptoms. This model aims to provide a framework to guide future biopsychosocial symptom science research that can elucidate new predictive methods and new targets for intervention.
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Registered trials
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.