Ascites and Serum Interleukin-10 Levels as a Prognostic Tool for Ovarian Cancer Outcomes.

Interleukin-10 (IL-10) has been shown to be present at high levels in the ascites of ovarian cancer (OC) patients; however, little is known about its prognostic value. We sought to correlate IL-10 levels in ascites and sera of OC patients with clinicopathologic characteristics and oncologic outcomes. IL-10 levels and clinical data from biobanked ascites and serum samples of OC patients were evaluated. Receiver operating characteristic curves were used to quantify marker performance and identify IL-10-high and IL-10-low groups. Correlations between IL-10 levels and clinicopathologic data were performed. Survival outcomes were calculated, while the factors affecting them were also investigated. A total of 106 patients had ascites samples, of which 44 serum samples were also available. Mean ascites IL-10 levels were significantly higher in patients with serous histology compared to endometrioid histology (p = 0.024). Fold-change in ascites IL-10 during treatment positively correlated with clinical response, as determined by a change in serum cancer antigen (CA)-125 levels (p = 0.0126). Median progression-free survival (PFS) and overall survival (OS) were shorter in patients with high compared with low ascites IL-10 levels (PFS: 18 versus 60 months; p = 0.007, OS: 42 versus 85 months; p = 0.029). A significant positive correlation was seen between ascites and sera IL-10 levels (p = 0.019). In multivariable analyses, a high ascites IL-10 level was associated with a significantly worse prognosis (PFS hazard ratio (HR) = 1.93; p = 0.02). Patients with high ascites levels of IL-10 have worse outcomes, which are likely reflective of the immunosuppressive effect of IL-10. This highlights its potential role as an immunomodulator in the tumor microenvironment, leading to OC immune evasion.

It takes one to know one-Machine learning for identifying OBGYN abstracts written by ChatGPT.

OBJECTIVES: To use machine learning to optimize the detection of obstetrics and gynecology (OBGYN) Chat Generative Pre-trained Transformer (ChatGPT) -written abstracts of all OBGYN journals. METHODS: We used Web of Science to identify all original articles published in all OBGYN journals in 2022. Seventy-five original articles were randomly selected. For each, we prompted ChatGPT to write an abstract based on the title and results of the original abstracts. Each abstract was tested by Grammarly software and reports were inserted into a database. Machine-learning modes were trained and examined on the database created. RESULTS: Overall, 75 abstracts from 12 different OBGYN journals were randomly selected. There were seven (58%) Q1 journals, one (8%) Q2 journal, two (17%) Q3 journals, and two (17%) Q4 journals. Use of mixed dialects of English, absence of comma-misuse, absence of incorrect verb forms, and improper formatting were important prediction variables of ChatGPT-written abstracts. The deep-learning model had the highest predictive performance of all examined models. This model achieved the following performance: accuracy 0.90, precision 0.92, recall 0.85, area under the curve 0.95. CONCLUSIONS: Machine-learning-based tools reach high accuracy in identifying ChatGPT-written OBGYN abstracts.

Ethnic disparities in the incidence of gynecologic malignancies among Israeli Women of Arab and Jewish Ethnicity: a 10-year study (2010-2019).

Background: Ethnic disparities in healthcare outcomes persist, even when populations share the same environmental factors and healthcare infrastructure. Gynecologic malignancies are a significant health concern, making it essential to explore how these disparities manifest in terms of their incidence among different ethnic groups. Objective: To investigate ethnic disparities in the incidence of gynecologic malignancies incidence among Israeli women of Arab and Jewish ethnicity. Design: Our research employs a longitudinal, population-based retrospective cohort design. Method: Data on gynecologic cancer diagnoses among the Israeli population from 2010 to 2019 was obtained from a National Registry. Disease incidence rates and age standardization were calculated. A comparison between Arab and Jewish patients was performed, with Poisson regression models being used to analyze significant rate changes. Results: Among Jewish women, the age-standardized ratio (ASR) for gynecologic malignancies decreased from 288 to 251 (p < 0.001) between 2014 and 2019. However, there was no significant change in the ASR among Arab women during the same period, with rates going from 192 to 186 (p = 0.802). During the study period, the incidence of ovarian cancer decreased significantly among Jewish women (p = 0.042), while the rate remained stable among Arab women (p = 0.102). A similar trend was observed for uterine cancer. The ASR of CIN III (Cervical Intraepithelial Neoplasia Grade 3) in Jewish women notably increased from 2017 to 2019, with an annual growth rate of 43.3% (p < 0.001). A similar substantial rise was observed among Arab women, with an annual growth rate of 40.5% (p < 0.001). In contrast, the incidence of invasive cervical cancer remained stable from 2010 to 2019 among women of both ethnic backgrounds. Conclusion: Our findings indicate that Arab women in Israel have a lower incidence rate of gynecologic cancers, warranting further investigation into protective factors. Both ethnic groups demonstrate effective utilization of cervical screening.

Converting to Open Access in Obstetrics and Gynaecology Journal: A Bibliometric Analysis.

For various reasons, journals may convert from subscription-based to open-access (OA) publishing models, commonly referred to as flipping. In 2022, the Acta Obstetricia et Gynecologica Scandinavica flipped to OA. We performed a bibliometric analysis of authorship patterns in this journal during and after the flipping period. A total of 898 research articles were included. In the period after flipping to OA, there were more publications by authors in various countries, including from China (7.2% vs. 3.3%, P = 0.001). Accordingly, the flip to OA in a leading obstetrics and gynaecology journal seemed to impact the authorship locale.

Performance of ChatGPT in French language Parcours d'Accès Spécifique Santé test and in OBGYN.

OBJECTIVES: To evaluate the performance of ChatGPT in a French medical school entrance examination. METHODS: A cross-sectional study using a consecutive sample of text-based multiple-choice practice questions for the Parcours d'Accès Spécifique Santé. ChatGPT answered questions in French. We compared performance of ChatGPT in obstetrics and gynecology (OBGYN) and in the whole test. RESULTS: Overall, 885 questions were evaluated. The mean test score was 34.0% (306; maximal score of 900). The performance of ChatGPT was 33.0% (292 correct answers, 885 questions). The performance of ChatGPT was lower in biostatistics (13.3% ± 19.7%) than in anatomy (34.2% ± 17.9%; P = 0.037) and also lower than in histology and embryology (40.0% ± 18.5%; P = 0.004). The OBGYN part had 290 questions. There was no difference in the test scores and the performance of ChatGPT in OBGYN versus the whole entrance test (P = 0.76 vs P = 0.10, respectively). CONCLUSIONS: ChatGPT answered one-third of questions correctly in the French test preparation. The performance in OBGYN was similar.

Gender leadership in gynecologic oncology professional societies worldwide.

OBJECTIVE: We aim to study gender representation among the different national gynecologic oncology (GO) societies' presidents over the past decade. METHODS: A cross-sectional study examining the period 2013-2022. The leadership positions in 11 GO societies in the USA (SGO), internationally (IGCS), Europe (ESGO), Australia (ASGO), Israel (ISGO), Japan (JSGO), Asia-Oceania (AOGIN), India (INSGO), Latin America (SLAGO), South Africa (SASGO), and Turkey (TRSGO) was studied. The proportion of leadership positions held by women was calculated and trends were evaluated. RESULTS: Overall, the average rate of women's representation during the study period was 26.4%, and for the different organizations was: SASGO 70.0%, SGO 50.0%, ESGO 40.0%, ASGO 30.0%, INSGO 30.0%, and IGCS, ISGO, and SLAGO 20.0% each, TRSGO 10%, and no representation of women in JSGO and AOGIN. There was a significant decrease from 2013 to 2016 (63.6% to 9.1%) (P = 0.009) in women's representation as presidents of societies. From 2017 to 2022, there was no difference in women's representation (ranging from 9.1% to 36.4%) (P = 0.13). CONCLUSIONS: This study demonstrates that women are significantly under-represented in leadership positions in GO professional societies; however, in South Africa and the USA their representation in the last decade was close to equality.