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Frequency of Neuroendocrine Tumor Studies: Using Latent Dirichlet Allocation and HJ-Biplot Statistical Methods

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  • Karime Montes Escobar

    (Department of Mathematics and Statistics, Institute of Basic Sciences, Technical University of Manabí, Portoviejo 130105, Ecuador
    Department of Statistics, University of Salamanca, 37008 Salamanca, Spain)

  • José Luis Vicente-Villardon

    (Department of Statistics, University of Salamanca, 37008 Salamanca, Spain)

  • Javier de la Hoz-M

    (Facultad de Ingeniería, Universidad del Magdalena, Santa Marta 470004, Colombia)

  • Lelly María Useche-Castro

    (Department of Mathematics and Statistics, Institute of Basic Sciences, Technical University of Manabí, Portoviejo 130105, Ecuador)

  • Daniel Fabricio Alarcón Cano

    (Teaching and Research, SOLCA, Manabí, Portoviejo 130105, Ecuador)

  • Aline Siteneski

    (Research Institute, Faculty of Health Sciences, Technical University of Manabí, Portoviejo 130105, Ecuador)

Abstract

Background: Neuroendocrine tumors (NETs) are severe and relatively rare and may affect any organ of the human body. The prevalence of NETs has increased in recent years; however, there seem to be more data on particular types, even though, despite the efforts of different guidelines, there is no consensus on how to identify different types of NETs. In this review, we investigated the countries that published the most articles about NETs, the most frequent organs affected, and the most common related topics. Methods: This work used the Latent Dirichlet Allocation (LDA) method to identify and interpret scientific information in relation to the categories in a set of documents. The HJ-Biplot method was also used to determine the relationship between the analyzed topics, by taking into consideration the years under study. Results: In this study, a literature review was conducted, from which a total of 7658 abstracts of scientific articles published between 1981 and 2020 were extracted. The United States, Germany, United Kingdom, France, and Italy published the majority of studies on NETs, of which pancreatic tumors were the most studied. The five most frequent topics were t_21 (clinical benefit), t_11 (pancreatic neuroendocrine tumors), t_13 (patients one year after treatment), t_17 (prognosis of survival before and after resection), and t_3 (markers for carcinomas). Finally, the results were put through a two-way multivariate analysis (HJ-Biplot), which generated a new interpretation: we grouped topics by year and discovered which NETs were the most relevant for which years. Conclusions: The most frequent topics found in our review highlighted the severity of NETs: patients have a poor prognosis of survival and a high probability of tumor recurrence.

Suggested Citation

  • Karime Montes Escobar & José Luis Vicente-Villardon & Javier de la Hoz-M & Lelly María Useche-Castro & Daniel Fabricio Alarcón Cano & Aline Siteneski, 2021. "Frequency of Neuroendocrine Tumor Studies: Using Latent Dirichlet Allocation and HJ-Biplot Statistical Methods," Mathematics, MDPI, vol. 9(18), pages 1-15, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:18:p:2281-:d:636871
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    References listed on IDEAS

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    1. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
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