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Personalized Nursing Care for Patients with Cancer in the Precision-Medicine Era

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health-Related Quality of Life and Well-Being".

Deadline for manuscript submissions: 15 December 2024 | Viewed by 3839

Special Issue Editors

Nursing Department, Health Sciences Center, The Federal University of Espírito Santo (UFES), Vitória 29075-910, ES, Brazil
Interests: personalized nursing; cancer symptom clusters; symptom management; sickness behavior; biomarkers; cancer epidemiology; oncology nursing
Department of Pediatrics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto 05508-060, SP, Brazil
Interests: immunology; inflammation; immunohistochemistry; cell culture; flow cytometry; western blot immunofluorescence; ELISA; gene expression; molecular; biology

Special Issue Information

Dear Colleagues,

The foundation of precision medicine lies in the recognition that different groups of individuals have specific genomic characteristics, which must be implicated in different and personalized treatments. The precision medicine era promises to offer, based on the identification of a patient’s genetic characteristics, the precise medicine, in the exact dose and at the right time, thus making it more efficient and reducing the costs of medical care. In order to meet the new demands for care, it is necessary that the omics sciences be integrated into nursing and clinical practice, especially in patient care. In this context, the emergent knowledge of structural genomics has been improved techniques that enabled the advancement of research related to functional genomics, which together comprise the “omics” sciences including transcriptomics, proteomics, the epigenomics and metabolomics. Such approaches aim to understand changes in the functioning of the genome at different stages of development and under different environmental conditions, in order to provide a better understanding of cancer development at a molecular level. It stands out that successful implementation of personalized nursing and clinical care in the precision medicine era requires interprofessional collaboration, community outreach efforts, and coordination of care. Recent approaches to personalized nursing care have shown a vast field of analysis to understand the connections between different systems (e.g., immune, endocrine, nervous system) and biobehavioral changes in patients in different contexts, particularly in the field of oncology. The integration of these complex connections of biological systems has become increasingly important and emergent for patient-centered oncology care.

Topics of interest include, but are not limited to:

  • Methodological studies concerning quantitative or qualitative approaches as well as experimental studies correlating the various clinical conditions or genotype information with phenotypes and clinical parameters of cancer patients.
  • Innovative research in the field of diagnostic assessments and nursing interventions for personalized oncology nursing care.
  • Studies focused on each individual’s personal risk for disease and the effectiveness of treatments based on individuals’ unique combination of genomics (or other omics science) and environmental risk factors.
  • New analytical strategies for research involving personalized nursing and clinical care in oncology.
  • Studies covering underlying mechanisms and priority cancer symptom clusters including: a) inflammation/immune system, b) sympathetic nervous system activation, c) hypothalamic–pituitary–adrenal axis activation; d) central nervous system changes; e) circadian rhythm disruption in order to determine the best approaches and methods to assess underlying genetic, epigenetic and biobehavioral mechanism, for cancer symptom clusters.
  • The impact of diagnostic genomic tests on clinical decision making for cancer patients as well as ethical issues.
  • Studies comprising cost–benefit assessment from an ethical perspective regarding the incorporation of new precision medicine technologies for patients with cancer.
  • The findings should have implications for the improvement of personalized nursing and clinical care, oncology, nursing education, personalized cancer medicine, and nursing management, as well as contributing to the construction of education and health policies.

This Special Issue encourages papers: (1) reporting the evaluation of experiments, observational studies as well as randomized trials; (2) investigating physiology, genetics, genomics, pharmacogenetics/pharmacogenomics, transcriptomics, proteomics, metabolomics and epigenomics, mechanisms linking environment and health outcomes for cancer patients. Additionally, papers are invited addressing the three pillars of interdisciplinary and highly related knowledge: omics sciences, bioinformatics and biomarkers. Original articles, experimental studies, systematic reviews and metanalyses, scoping reviews, methodological studies, and short communications are welcome. Proposals for editorials or commentaries on the public health significance and future directions for these subjects would also be appreciated. We would like to encourage authors to submit robust research articles/communications or review papers.

Dr. Luís Carlos Lopes-Júnior
Dr. Luciana Chain Veronez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • personalized nursing care
  • patient-centered care
  • oncology
  • pediatric oncology
  • cancer symptom clusters
  • symptom management
  • sickness behavior
  • biomarkers
  • patients’ prognosis
  • diagnosis
  • cancer treatment
  • cancer survival risk
  • psychoneuroimmunology in cancer
  • clinical decision making for cancer patients
  • personalized cancer medicine
  • circadian rhythms disruption
  • genetics
  • genomics
  • pharmacogenetics/pharmacogenomics
  • transcriptomics
  • proteomics
  • metabolomics
  • epigenomics
  • epigenetics
  • bioinformatics
  • precision medicine

Published Papers (3 papers)

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Editorial

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3 pages, 283 KiB  
Editorial
Personalized Care for Patients with Cancer in the Precision-Medicine Era
Int. J. Environ. Res. Public Health 2023, 20(4), 3023; https://doi.org/10.3390/ijerph20043023 - 09 Feb 2023
Cited by 2 | Viewed by 1027
Abstract
Important advances in cancer management have been made in the beginning of the 21st century [...] Full article

Research

Jump to: Editorial

12 pages, 808 KiB  
Article
Temporal Trends in the Completeness of Epidemiological Variables in a Hospital-Based Cancer Registry of a Pediatric Oncology Center in Brazil
Int. J. Environ. Res. Public Health 2024, 21(2), 200; https://doi.org/10.3390/ijerph21020200 - 09 Feb 2024
Viewed by 748
Abstract
This ecological time series study aimed to examine the temporal trends in the completeness of epidemiological variables from a hospital-based cancer registry (HbCR) of a reference center for pediatric oncology in Brazil from 2010 to 2016. Completeness categories were based on the percentage [...] Read more.
This ecological time series study aimed to examine the temporal trends in the completeness of epidemiological variables from a hospital-based cancer registry (HbCR) of a reference center for pediatric oncology in Brazil from 2010 to 2016. Completeness categories were based on the percentage of missing data, with the categories excellent (<5%), good (5–10%), regular (11–20%), poor (21–50%), and very poor (>50%). Descriptive and bivariate analyses were performed using R.4.1.0; a Mann–Kendall trend test was performed to examine the temporal trends. Variables with the highest incompleteness included race/color (17.24% in 2016), level of education (51.40% in 2015), TNM (56.88% in 2012), disease status at the end of the first treatment (12.09% in 2013), cancer family history (79.12% in 2013), history of alcoholic consumption (39.25% in 2015), history of tobacco consumption (38.32% in 2015), and type of admission clinic (10.28% in 2015). Nevertheless, most variables achieved 100% completeness and were classified as excellent across the time series. A significant trend was observed for race/color, TNM, and history of tobacco consumption. While most variables maintained excellent completeness, the increasing incompleteness trend in race/color and decreasing trend in TNM underscore the importance of reliable and complete HbCRs for personalized cancer care, for planning public policies, and for conducting research on cancer control. Full article
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17 pages, 1536 KiB  
Article
Importance of Social Support of Parents of Children with Cancer: A Multicomponent Model Using Partial Least Squares-Path Modelling
Int. J. Environ. Res. Public Health 2023, 20(3), 1757; https://doi.org/10.3390/ijerph20031757 - 18 Jan 2023
Cited by 1 | Viewed by 1409
Abstract
The purpose of the present study is to build a model combining some variables that have been previously studied separately to improve our understanding on how they relate in parents of children with cancer. A total of 112 parents with an average age [...] Read more.
The purpose of the present study is to build a model combining some variables that have been previously studied separately to improve our understanding on how they relate in parents of children with cancer. A total of 112 parents with an average age of 41 completed the self-assessment questionnaires containing the factors studied: social support received, social support provided, stress, adjustment of parents and life satisfaction. Two models were developed: one for social support received and one for social support provided. Structural equation models based on the variance estimated through partial least squares were used to analyze factors involved in quality of life based on an exploratory model of second order. The estimated model was robust in terms of quality of measurement (reliability and validity). According to results from the structural model, in the model of social support received, the impact of social support received on stress was considerable (β = −0.26; p = 0.02) and it explained 16% of the variance. The impact of social support received by parents on their adjustment (β = −0.56; p < 0.001) was also considerable, explaining 32% of the variance. Finally, adjustment of parents also showed an effect on life satisfaction (β = −0.33; p < 0.001) and it explained 26% of the variance. However, the relation between social support received (β = 0.15; p = 0.11) and life satisfaction, the relation between stress (β = −0.15; p = 0.08) and life satisfaction, and the relation between adjustment of parents (β = 0.20; p = 0.07) and stress were not significant. In the model of social support provided by parents, social support provided (β = 0.35; p < 0.001), and adjustment of parents (β = −0.31; p < 0.01) impacted life satisfaction, explaining 36% of the variance. Social support provided (β = −0.34; p < 0.01) impacted adjustment of parents and it explained 12% of the variance. Adjustment of parents (β = 0.28; p < 0.05) also impacted parents’ perception of stress, explaining 14% of the variance. However, the relation between social support provided (β = −0.17; p = 0.06) and stress, and the relation between stress (β = −0.13; p = 0.08) and life satisfaction, were not significant. Social support received showed a strong connection with stress and parents’ adjustment. Additionally, social support received showed a decrease in stress and parents’ adjustment. Social support provided by parents and the adjustments they experience are linked to their life satisfaction. Additionally, social support provided showed a decrease in adjustment and an increase in parents’ life satisfaction. The models can be used to improve parents’ situations and it has strong practical implications. Full article
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