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Biomedicines
Special Issues
Personalized Diagnosis and Therapy in Endocrinology and Gynecology
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Personalized Diagnosis and Therapy in Endocrinology and Gynecology

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 1320

Editor

Dr. Sarah Allegra

E-Mail Website
Guest Editor
Department of Biological and Clinical Sciences, University of Turin, S. Luigi Gonzaga Hospital, 10043 Orbassano, Italy
Interests: sex and gender pharmacology; gender medicine; pharmacokinetics; pharmacogenomics; personalized therapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advances in genomics, molecular biology, and digital health technologies are transforming the landscape of endocrine and gynecological care. Traditional "one-size-fits-all" treatment models are increasingly giving way to personalized therapeutic approaches that consider the patient’s genetic profile, hormonal environment, lifestyle, and comorbid conditions. This Special Issue aims to explore the current state and future directions of personalized medicine in endocrinology and gynecology, focusing on how individualized treatment strategies can improve patient outcomes, reduce adverse effects, and optimize resource utilization.

We welcome the submission of high-quality original research and reviews investigating personalized interventions in areas such as reproductive endocrinology, endometriosis, polycystic ovary syndrome (PCOS), thyroid disorders, menopause management, metabolic syndromes, and hormone-related cancers. Studies addressing the role of biomarkers, pharmacogenomics, digital tools, and AI-driven decision-making in tailoring treatments are particularly encouraged.
This issue will serve as a platform for clinicians, researchers, and healthcare innovators to share insights, methodologies, and clinical applications that support the integration of precision medicine into everyday practice.

Dr. Sarah Allegra
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines 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

  • personalized medicine
  • endocrine disorders
  • gynecological diseases
  • reproductive endocrinology
  • pharmacogenomics
  • hormonal therapy
  • polycystic ovary syndrome (PCOS)
  • precision medicine
  • biomarkers
  • women’s health

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Published Papers (2 papers)

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Research

15 pages, 858 KB  
Article
The Limited Diagnostic Utility of Metabolic and Inflammatory Indices in Adolescent Polycystic Ovary Syndrome: A Case–Control Study
by Sefer Ustebay, Rulin Deniz, Alihan Tigli, Guzide Ece Akinci, Muhammet Bora Uzuner, Nazli Sener, Yasemin Ercan Degirmenci, Dondu Ulker Ustebay, Oğuzhan Karakoç, Yasin Selcuk Yardibi, Deniz Almak and Yakup Baykus
Biomedicines 2026, 14(7), 1598; https://doi.org/10.3390/biomedicines14071598 - 16 Jul 2026
Viewed by 214
Abstract
Background: The aim of this study was to evaluate the clinical and diagnostic utility of metabolic and systemic inflammatory marker indices in adolescent patients with polycystic ovary syndrome (PCOS). Methods: This retrospective case–control study included 63 adolescent girls diagnosed with PCOS, based [...] Read more.
Background: The aim of this study was to evaluate the clinical and diagnostic utility of metabolic and systemic inflammatory marker indices in adolescent patients with polycystic ovary syndrome (PCOS). Methods: This retrospective case–control study included 63 adolescent girls diagnosed with PCOS, based on the strict presence of both menstrual irregularity and hyperandrogenism, and 63 healthy controls matched for age and body mass index (BMI). Fasting blood glucose (FBG), fasting insulin (FI), and lipid profiles were measured. Metabolic indices, including the Triglyceride-Glucose (TyG) index, Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), and Metabolic Score for Insulin Resistance (METS-IR), as well as systemic inflammatory indices (Systemic Immune-Inflammation Index (SII), Systemic Inflammation Response Index (SIRI), and the Aggregate Index of Systemic Inflammation (AISI)), were calculated. The diagnostic performance of these markers was evaluated using Receiver Operating Characteristic (ROC) curves and binary logistic regression analyses. Results: No statistically significant difference was observed between the PCOS and control groups in terms of age and BMI (p > 0.05). FBG levels (p = 0.001) and the TyG index (p = 0.028) were found to be significantly higher in the PCOS group. However, no significant differences were observed between the groups in terms of other metabolic indices (HOMA-IR, METS-IR) and systemic inflammatory markers (SII, SIRI, AISI). In the ROC analysis, only the TyG index demonstrated statistically significant but weak discriminatory power for PCOS (AUC = 0.614; 95% CI: 0.515–0.712; p = 0.028). Furthermore, binary logistic regression analysis revealed that the TyG index was not an independent predictor of PCOS after adjustment. Conclusions: While early metabolic signals such as elevated FBG and TyG index were detected, the evaluated systemic inflammatory indices did not demonstrate significant differences. However, the weak discriminatory capacity of the TyG index and the failure of other composite indices restrict their clinical utility. Therefore, these biomarkers cannot be recommended as reliable standalone diagnostic tools in adolescent PCOS. Full article
(This article belongs to the Special Issue Personalized Diagnosis and Therapy in Endocrinology and Gynecology)
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11 pages, 984 KB  
Article
A Personalized FSH Dosing Strategy for Women with Polycystic Ovary Syndrome Undergoing GnRH Antagonist Protocols
by Yixin Chen, Turui Yang, Zicong Luo, Lu Luo, Ziqing Zhang, Yanwen Xu and Minghui Chen
Biomedicines 2026, 14(4), 769; https://doi.org/10.3390/biomedicines14040769 - 28 Mar 2026
Viewed by 654
Abstract
Background: Polycystic ovary syndrome (PCOS) is characterized by substantial inter-individual variability in ovarian sensitivity to recombinant follicle-stimulating hormone (rFSH) during controlled ovarian stimulation (COS). Clinically applicable tools for personalized dosing in this population remain limited. Methods: This retrospective single-center study (2013–2024) analyzed 369 [...] Read more.
Background: Polycystic ovary syndrome (PCOS) is characterized by substantial inter-individual variability in ovarian sensitivity to recombinant follicle-stimulating hormone (rFSH) during controlled ovarian stimulation (COS). Clinically applicable tools for personalized dosing in this population remain limited. Methods: This retrospective single-center study (2013–2024) analyzed 369 PCOS patients undergoing GnRH antagonist protocols who achieved optimal ovarian responses (10–20 oocytes with at least 40% of follicles ≥ 16 mm in diameter on trigger day). The final retrospective dataset was randomly split into modeling (n = 258) and validation (n = 111) groups. A multivariate linear regression model incorporating age, BMI, basal FSH, basal LH, AMH, and AFC was developed to estimate the average daily rFSH dose. Model performance was evaluated using correlation analysis, prediction error metrics, and calibration assessment. Results: Age, BMI, and basal FSH were positively associated with average daily rFSH dose, whereas basal LH, AMH, and AFC were negatively associated. The model explained 40.4% of the variability in average daily rFSH dose. In the modeling cohort, 77.9% of estimated doses fell within ±20% of the observed values, with a moderate correlation between predicted and observed doses (ρ = 0.646). In the validation cohort, 67.6% of estimates met the predefined accuracy threshold (ρ = 0.676). Calibration analyses demonstrated robust agreement between predicted and observed doses. Conclusions: By integrating endocrine markers, ovarian reserve indicators, and clinical characteristics, this study provides a practical example of personalized medicine in COS in women with PCOS. The internally validated approach may support individualized rFSH dosing during COS and serve as a basis for future development of decision support tools in this specific population. Full article
(This article belongs to the Special Issue Personalized Diagnosis and Therapy in Endocrinology and Gynecology)
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