Mapping the landscape of gynecological cancer – analyzing presenting features by social network analysis

Authors

  • Indra Sambasivam School of Public Health, SRM Institute of Science and Technology, Kattankulathur Campus, Chengalpattu, Tamilnadu, India; Department of Public Health, School of Allied Health Sciences, VMRF-DU, Salem, Tamilnadu, India https://orcid.org/0000-0002-5123-4427
  • H. Gladius Jennifer School of Public Health, SRM Institute of Science and Technology, Kattankulathur Campus, Chengalpattu, Tamilnadu, India https://orcid.org/0000-0003-3934-1884

DOI:

https://doi.org/10.15584/ejcem.2025.1.1

Keywords:

gynecological cancer, mapping, network visualization, social network analysis, symptoms

Abstract

Introduction and aim. The term ‘gynecological cancers’ refers to a wide range of malignancies that affect the female reproduc tive system. These types of cancer include ovarian, cervical, uterine, vaginal, and vulvar cancers. This study aims to employ SNA techniques to map the landscape of gynecological cancer by systematically analyzing the presenting features associated with different types of gynecological malignancies.

Material and methods. In this study, a total of 60 women diagnosed with gynecological cancer were included. An exploratory study design was used. A pre-tested questionnaire was used which includes basic demographic details, type of cancer and symptoms presented at the time of diagnosis.

Results. Nearly 44% of the women diagnosed with cancer were between the age of 51 to 60 years. Symptoms such as abdom inal pain, lumps, mild and moderate symptoms that appeared to be highly connected and influential among the cancer patients. Abdominal pain, lumps, abdominal distension/bloating, and mild symptoms had a stronger connection with all other symptoms among the cancer patients.

Conclusion. Educating patients about the significance of symptoms such as abdominal pain, lumps, and abdominal disten sion/bloating in the context of ovarian cancer can empower them to seek timely medical attention. Increased awareness of the potential implications of these symptoms may prompt patients to undergo screening and diagnostic tests earlier, leading to improved detection rates and treatment outcomes.

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Published

2025-03-30

How to Cite

Sambasivam, I., & Jennifer, H. G. (2025). Mapping the landscape of gynecological cancer – analyzing presenting features by social network analysis. European Journal of Clinical and Experimental Medicine, 23(1), 21–27. https://doi.org/10.15584/ejcem.2025.1.1

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ORIGINAL PAPERS