Hisashi Masuyama

Epithelial ovarian cancer is predominantly characterized by peritoneal dissemination, providing a strong biological rationale for intraperitoneal (IP) chemotherapy. Although IP cisplatin-based regimens have demonstrated substantial survival benefits in pivotal randomized trials, toxicity and catheter-related complications limit their widespread adoption. IP carboplatin has emerged as a pragmatic alternative with improved tolerability while preserving its pharmacokinetic advantages. This review summarizes the biological and pharmacological rationale for IP carboplatin and critically examines the clinical evidence, with a particular emphasis on the Intraperitoneal Carboplatin for Ovarian Cancer (iPocc) trial and its divergence from Gynecologic Oncology Group (GOG)-252. We further discuss the potential applicability of IP carboplatin beyond the traditional setting of minimal residual disease, including patients undergoing neoadjuvant chemotherapy and interval debulking surgery, as well as its possible use in the contemporary era of maintenance therapy. Collectively, the accumulated evidence supports renewed consideration of IP carboplatin as a versatile component in modern ovarian cancer management.

Epithelial ovarian cancer is predominantly characterized by peritoneal dissemination, providing a strong biological rationale for intraperitoneal (IP) chemotherapy. Although IP cisplatin-based regimens have demonstrated substantial survival benefits in pivotal randomized trials, toxicity and catheter-related complications limit their widespread adoption. IP carboplatin has emerged as a pragmatic alternative with improved tolerability while preserving its pharmacokinetic advantages. This review summarizes the biological and pharmacological rationale for IP carboplatin and critically examines the clinical evidence, with a particular emphasis on the Intraperitoneal Carboplatin for Ovarian Cancer (iPocc) trial and its divergence from Gynecologic Oncology Group (GOG)-252. We further discuss the potential applicability of IP carboplatin beyond the traditional setting of minimal residual disease, including patients undergoing neoadjuvant chemotherapy and interval debulking surgery, as well as its possible use in the contemporary era of maintenance therapy. Collectively, the accumulated evidence supports renewed consideration of IP carboplatin as a versatile component in modern ovarian cancer management.

Nakamura K, et al. J Gynecol Oncol. 2026 ;37:e96. https://doi.org/10.3802/jgo.2026.37.e96

The concept of “platinum sensitivity” has long guided prognostic assessment and treatment selection in recurrent ovarian cancer. However, the emergence of targeted agents, such as bevacizumab and poly (ADP-ribose) polymerase inhibitors, has complicated its clinical utility. In contrast, emerging evidence suggests that platinum sensitivity may also be applicable to recurrent endometrial cancer. As in ovarian cancer, a prolonged platinum-free interval (PFI) in recurrent endometrial cancer is associated with an improved efficacy of subsequent platinum-based chemotherapy. The PFI is linearly correlated with the response rate to platinum re-administration, progression-free survival, and overall survival. Patients are typically classified as having platinum-resistant or platinum-sensitive disease based on a PFI cutoff of 6 or 12 months. However, unlike in ovarian cancer—where the duration of response to second-line platinum-based chemotherapy rarely exceeds the prior PFI (~3%)—approximately 30% of patients with recurrent endometrial cancer exhibit a sustained response to platinum rechallenge that extends beyond their preceding PFI. Despite the incorporation of immune checkpoint inhibitors into the treatment landscape of endometrial cancer, the role of platinum sensitivity in clinical decision-making—particularly regarding treatment sequencing and drug selection—remains a critical and unresolved issue. Further research is warranted to elucidate the mechanisms underlying platinum resistance and to guide optimal therapeutic strategies.

Introduction The COVID-19 pandemic led to a decline in fertility rates worldwide. Although many regions have experienced a temporary drop in fertility rates with the spread of the infection, subsequent recovery has varied across countries. This study aimed to evaluate the impact of COVID-19 infection rates and regional sociodemographic factors on the recovery of fertility rates in Japan following the state of emergency. Methods This study examined prefectural fertility data from before the COVID-19 pandemic to forecast fertility rates up to 2022 using a seasonal autoregressive integrated moving average model. A regression analysis was conducted on fertility rates during the first state of emergency and the subsequent recovery rate with respect to the number of new COVID-19 cases and sociodemographic factors specific to each prefecture. Results During the first state of emergency, the monthly fertility rate decreased by an average of −13.8% (SD: 6.26, min: −28.78, max: 0.15) compared with the previous year. Over the following 22 months, the average fertility recovery rate was +2.31% (SD: 3.57; min: −8.55, max: 19.54). Multivariate analysis of the impact of the pandemic on fertility changes during the first emergency indicated a negative correlation between new COVID-19 cases per capita and the proportion of nuclear households. No significant correlation was found between fertility recovery rate and new COVID-19 cases or emergency duration. When classifying fertility rate fluctuation patterns before and after the emergency into four clusters, variations were noted in the proportion of the elderly population, marriage divorce rate and the number of internet searches related to pregnancy intentions across the clusters. Conclusions No association was found between pregnancy intentions related to the spread of infection, such as the number of new cases and the fertility recovery rate following the first state of emergency. Differences in the patterns of decline and recovery during the pandemic were observed based on population composition and internet searches for infection and pregnancy across different prefectures.

BACKGROUND Screening for mental disorders in pregnant women is crucial, but traditional tools such as the Edinburgh Postnatal Depression Scale (EPDS) or Brief Symptom Inventory 18 (BSI18) lack objectivity. Voice analysis and AI show promise in identifying specific mental disorders; however, existing research focuses on general depression, neglecting other disorders in pregnant women. OBJECTIVE This study explored the use of an image classification model to detect vocal patterns and identify mental disorders in pregnant women. METHODS This prospective cohort study was conducted in Japan with 204 pregnant women attending a one-month postnatal checkup. The study involved voice recordings during interviews, supplemented by sociodemographic data and Edinburgh Postnatal Depression Scale (EPDS) scores. Voice samples were cleaned to remove environmental noise and other voices, then segmented and converted into spectrograms. Data augmentation techniques were employed to enhance training data diversity, and Efficientformer V2, pretrained with transfer learning, was used for categorization. Hyperparameters were optimized using Optuna, and an ensemble learning approach was used for final classifications, which were compared against the EPDS. RESULTS Of the 204 pregnant women enrolled, 32 were excluded due to inadequate data, resulting in 172 participants. The participants were divided into three groups: 97 for training, 32 for validation, and 43 for testing. The average audio duration was approximately 549.2±356.0 s. The segmented data yielded 2,942 training, 197 validation, and 323 test segments. After data expansion, the number of training segments increased to 14,170. Various hyperparameters were set for machine learning. The ensemble predictions displayed higher sensitivity (1.00) and recall (0.82) for vocal discrimination and higher specificity (0.97) and precision (0.84) for EPDS discrimination. The receiver operating characteristic area under the curve comparison revealed no significant difference (p = 0.759). CONCLUSIONS Voice analysis and artificial intelligence may provide better screening methods for detecting mental disorders during pregnancy.

Background: Gynecologic cancers are one of the most common types of malignancies in working-age women. We aimed to determine the factors that impede women from returning to the same workplace after treatment for such cancers. Methods: A questionnaire-based survey was conducted on 194 women who underwent treatment for gynecologic cancer at the Okayama University (≥1 year after cancer treatment and <65 years of age). We performed a logistic regression analysis to determine the relationship between returning to the same workplace and not taking sick leave. Results: The median age at diagnosis was 49.0 years, and the median time from cancer treatment to questionnaire completion was 3.8 years. Not returning to the same workplace was positively associated with not being regularly employed (P = 0.018), short work time per day (P = 0.023), low personal income (P = 0.004), not taking sick leave (P < 0.001), advanced cancer stage (P = 0.018) and long treatment time (P = 0.032). Interestingly, not taking sick leave was strongly associated with not returning to the same workplace in the multivariable analysis (P < 0.001). Conclusions: Not taking sick leave likely was negatively associated with returning to the same workplace after the treatment for gynecologic cancer. Therefore, we suggest that steps be taken to formally introduce a sick leave system over and above the paid leave system in Japan.