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Life
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Cancer Epidemiology
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Cancer Epidemiology

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Epidemiology".

Deadline for manuscript submissions: closed (19 December 2024) | Viewed by 1922

Special Issue Editors

Prof. Dr. Daniela-Cristina Stefan

E-Mail Website
Guest Editor
1. Pro-Vice Chancellor, University of Namibia, Windhoek 13301, Namibia
2. Sing Duke-NUS Global Health Institute Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore
3. The Doctoral School of the University, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
Interests: global oncology; cervical cancer; cancer equity
Dr. Honoré K. Mitonga

E-Mail
Guest Editor
Department of Public Health, Faculty of Health Sciences and Veterinary Medicine, University of Namibia, Namibia, South Africa
Interests: epidemiology and biostatistics; general public health

Special Issue Information

Dear Colleagues,

Cancer epidemiology is a rapidly evolving field that seeks to understand the patterns, causes, and effects of cancer across different populations. In this Special Issue, we will delve into several critical areas of cancer epidemiology, aiming to provide comprehensive insights and foster advancements in research and clinical practice. Some of the key topics that might be covered in this Special Edition include the following:

Cancer in Specific Populations:

  • Pediatric cancer epidemiology: focus on trends, risk factors, and outcomes of childhood cancers (special focus on LMIC countries);
  • Cancer in older adults: studies on the epidemiology of cancer in the aging population and the unique challenges they face.

Geographic disparities: examination of cancer prevalence in different regions, highlighting disparities and possible causes, such as environmental factors

Advances in Cancer Screening and Early Detection:

  • Screening programs: evaluation of the effectiveness of current cancer screening programs for cancers such as breast, cervical, colorectal, and prostate;
  • Innovative technologies: emerging technologies in cancer screening, such as liquid biopsies and advanced imaging techniques.

Methodological Advances in Epidemiology:

  • Big data and cancer research: use of big data analytics, machine learning, and bioinformatics in cancer epidemiology;
  • Statistical methods: advances in statistical methods to better analyze and interpret epidemiological data.

Through this Special Issue, we aim to provide researchers and clinicians with a platform to share cutting-edge research, foster interdisciplinary collaborations, and promote a deeper understanding of emerging trends in cancer epidemiology. This includes the roles of various factors in cancer pathogenesis and the development of innovative screening and therapeutic interventions.

Prof. Dr. Daniela-Cristina Stefan
Dr. Honoré K. Mitonga
Guest Editors

Alicia Fernandes
Guest Editor Assistant

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. Life 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 2600 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

  • cancer disparities
  • specific populations
  • methodological advances
  • cancer trends
  • cancer causes
  • prevention strategies

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

10 pages, 2122 KiB  
Article
Two Decades of Insights: Comprehensive Histopathological and Epidemiological Analysis of Conjunctival Tumors
by Dolika D. Vasović, Dejan M. Rašić, Zoran Latković, Bojana Dačić-Krnjaja, Jelena Vasilijević, Ivan Marjanović, Jelena Simonović, Anica Bobić Radovanović, Miodrag Karamarković, Milan Stojičić, Milica Mićović and Tanja Kalezić
Life 2024, 14(11), 1381; https://doi.org/10.3390/life14111381 - 27 Oct 2024
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Abstract
This study analyzed 2102 conjunctival lesions excised between 1981 and 2003 at a single tertiary center in Serbia, with the aim of evaluating their histopathological characteristics, anatomical localization, and demographic distribution. Of the total cases recorded, 55.1% were male, indicating a slight male [...] Read more.
This study analyzed 2102 conjunctival lesions excised between 1981 and 2003 at a single tertiary center in Serbia, with the aim of evaluating their histopathological characteristics, anatomical localization, and demographic distribution. Of the total cases recorded, 55.1% were male, indicating a slight male predominance. The bulbar conjunctiva was the most commonly affected site (34.5%), with 39.3% of tumors extended to multiple regions of the conjunctiva, including areas such as the plica and caruncula. The most common benign lesion was compound conjunctival nevus (16.7%), while squamous cell carcinoma (SCC) (11.4%) and melanoma (11.3%) were the most prevalent malignant tumors. Tumor incidence peaked in the 61–70 and 51–60 year age groups, with malignant tumors such as SCC being more frequent in males. Comparisons with similar global studies reveal that our findings align with worldwide trends, such as the predominance of SCC, which has been linked to UV exposure, and the frequency of melanoma in fair-skinned populations. However, the lower prevalence of fibrodegenerative lesions like pterygia and pinguecula in our cohort likely reflects Serbia’s cooler climate compared to regions with higher UV exposure. These findings underscore the diverse nature of conjunctival tumors, the critical role of histopathological examination for diagnosis, and the influence of environmental factors. This study provides valuable insights into the epidemiology of conjunctival tumors, contributing to global understanding and guiding future diagnostic and therapeutic approaches. Full article
(This article belongs to the Special Issue Cancer Epidemiology)
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13 pages, 1549 KiB  
Article
An Artificial Neural Network Prediction Model of Depressive Symptoms among Women with Abnormal Papanicolaou Smear Results before and after Diagnostic Procedures
by Irena Ilic, Goran Babic, Aleksandra Dimitrijevic, Sandra Sipetic Grujicic and Milena Ilic
Life 2024, 14(9), 1130; https://doi.org/10.3390/life14091130 - 7 Sep 2024
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Abstract
(1) Background: Cervical screening and additional diagnostic procedures often lead to depression. This research aimed to develop a prediction model for depression in women who received an abnormal Papanicolaou screening test, prior to and following the diagnostic procedures. (2) Methods: The study included [...] Read more.
(1) Background: Cervical screening and additional diagnostic procedures often lead to depression. This research aimed to develop a prediction model for depression in women who received an abnormal Papanicolaou screening test, prior to and following the diagnostic procedures. (2) Methods: The study included women who had a positive Papanicolaou screening test (N = 172) and attended the Clinical Center of Kragujevac in Serbia for additional diagnostic procedures (colposcopy/biopsy/endocervical curettage). Women filled out a sociodemographic survey and the Center for Epidemiologic Studies Depression questionnaire (CES-D scale) before and after diagnostic procedures. A prediction model was built with multilayer perceptron neural networks. (3) Results: A correlation-based filter method of feature selection indicated four variables that correlated with depression both prior to and following the diagnostic procedures—anxiety, depression, worry, and concern about health consequences. In addition, the use of sedatives and a history of both induced and spontaneous abortion correlated with pre-diagnostic depression. Important attributes for predicting post-diagnostic depression were scores for the domains ‘Tension/discomfort’ and ‘Embarrassment’ and depression in personal medical history. The accuracy of the pre-diagnostic procedures model was 70.6%, and the area under the receiver operating characteristic curve (AUROC) was 0.668. The model for post-diagnostic depression prediction showed an accuracy of 70.6%, and an AUROC = 0.836. (4) Conclusions: This study helps provide means to predict the occurrence of depression in women with an abnormal Papanicolaou screening result prior to and following diagnostic procedures, which can aid healthcare professionals in successfully providing timely psychological support to those women who are referred to further diagnostics. Full article
(This article belongs to the Special Issue Cancer Epidemiology)
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