STUDY QUESTION: What is the prevalence and trend of infertility among individuals of childbearing age at global, regional, and national levels by sex and socio-demographic index (SDI) across 21 regions and 204 countries and territories? SUMMARY ANSWER: Our findings reveal a growing prevalence of infertility among individuals aged 15–49 years worldwide from 1990 to 2021, with an expected continued increase through 2040. WHAT IS KNOWN ALREADY: Infertility is a persistent global reproductive health issue, leading to significant societal and health consequences. No study has specifically described the current prevalence of infertility, its secular trend, or the variations between regions or countries with different SDI levels. STUDY DESIGN, SIZE, DURATION: A sex- and SDI-stratified systematic analysis of the prevalence of infertility across 21 regions and 204 countries and territories from 1990 to 2021 has been performed. PARTICIPANTS/MATERIALS, SETTING, METHODS: We retrieved data from the Global Burden of Disease Study (GBD) 2021 on the count and crude rate of infertility prevalence for individuals aged 15–49 years across 204 countries and territories from 1990 to 2021. In the GBD 2021 framework, infertility is defined as the absence of a live birth in a couple who have been in a union for at least 5 years and are actively trying to conceive, or in a couple who have been in a union for at least 5 years since their last live birth, with no use of contraceptives during this period. Estimated annual percent change was calculated to quantify the temporal trend in age-standardized prevalence rates (ASPRs) for infertility by sex, age, and SDI. The Bayesian age-period-cohort model was used to project the ASPRs from 2022 to 2040. MAIN RESULTS AND ROLE OF CHANCE: In 2021, an estimated 55 000 818 men and 110 089 459 women were living with infertility worldwide, corresponding to approximately 1820.6 cases per 100 000 population (1.8%) for males and 3713.2 cases per 100 000 population (3.7%) for females. Regionally, the highest infertility prevalence was observed in middle SDI regions, such as East and South Asia and Eastern Europe. Infertility primarily affected the age group of 35–39 years and females in most regions, with some notable exceptions. Between 1990 and 2021, the global ASPRs of infertility increased by an average of 0.49% (95% CI 0.34–0.63) for males and 0.68% (0.51–0.86) for females. Additionally, the fastest increase in female infertility occurred in high SDI regions, while the most significant rise in male infertility was seen in low-middle SDI areas. Furthermore, the global ASPR of male infertility is projected to rise more rapidly than that of female infertility from 2022 to 2040. LIMITATIONS, REASONS FOR CAUTION: The primary data sources for the infertility burden in the GBD 2021 are population-based surveys; however, less-developed regions often lack complete population-based statistics, leading to potential reporting bias of the infertility burden in these areas due to data sparsity and incompleteness. Additionally, this study could not separately assess the prevalence and trends of primary and secondary infertility. Furthermore, the GBD 2021 does not provide the attributable proportion of each cause of infertility; hence, we cannot compare the contribution of these causes to infertility by sex, age, and location. WIDER IMPLICATIONS OF THE FINDINGS: Sexual and reproductive health are crucial for individuals’ health, economic development, and overall human wellbeing. It is essential for governments and the public to recognize the severity of infertility and prioritize the implementation of targeted interventions to enhance reproductive health. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by the grants from the Science and Technology Project of Jiangmen (2020030103110009027). The authors have declared no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Background: The global burden and trends in gynecological cancer (GC) by menopausal status worldwide remain unclear. Methods: Data on the number of incident cases and deaths, as well as age-standardized rates (ASR) and risk factors for GC in pre- and post-menopausal women were obtained from the Global Burden of Disease (GBD) Study 2019. The estimated annual percent change was calculated to quantify the temporal trend of GC burden by menopausal status between 1990 and 2019. The Bayesian age-period-cohort model was used to predict the trends in age-standardized incidence and mortality rates for pre- and post-menopausal GC during 2020–2040. Results: In 2019, an estimated 400 146 pre-menopausal and 879 476 post-menopausal GC cases were newly diagnosed worldwide, with ~111 420 and 442 821 GC-related deaths occurring in each menopausal group, respectively. The majority of both pre- and post-menopausal GC cases in low-to-middle-SDI regions was due to cervical cancer. In high- and high-middle-SDI regions, pre-menopausal GC was primarily attributed to cervical cancer, while post-menopausal GC was mainly attributed to uterine cancer. Additionally, the contribution of uterine cancer to GC was higher among post-menopausal women than pre-menopausal women, across all SDI levels and geographical regions. ASIRs either remained stable or increased from 1990 to 2019 worldwide for both pre- and post-menopausal GC [an average change of 0.03% (95% CI –0.02 to 0.08) and 0.09% (0.05–0.13) per year, respectively]. However, the age-standardized mortality rates (ASMRs) declined by an annual average of 0.86% (95% CI –0.92 to –0.8) and 0.63% (95% CI –0.66 to –0.6) globally during the same period. The risk-attributable proportion of post-menopausal GC deaths was higher than that of pre-menopausal GC and increased with increasing SDI. The projections indicate an increasing trend in the burden of pre-menopausal GC from 2020 to 2040, while the burden of post-menopausal GC is expected to decline. Conclusions: GC continues to be a significant public health concern worldwide, with notable regional and demographic disparities in the burden based on menopausal status. Policymakers and healthcare providers must be proactively aware of these evolving trends and tailor age-appropriate and region-specific screening strategies, as well as allocate resources accordingly.

Sustained activation of DNA damage response (DDR) signaling has been demonstrated to play vital role in chemotherapy failure in cancer. However, the mechanism underlying DDR sustaining in cancer cells remains unclear. In the current study, we found that the expression of the DDUP microprotein, encoded by the CTBP1-DT lncRNA, drastically increased in cisplatin-resistant ovarian cancer cells and was inversely correlated to cisplatin-based therapy response. Using a patient-derived human cancer cell model, we observed that DNA damage-induced DDUP foci sustained the RAD18/RAD51C and RAD18/PCNA complexes at the sites of DNA damage, consequently resulting in cisplatin resistance through dual RAD51C-mediated homologous recombination (HR) and proliferating cell nuclear antigen (PCNA)-mediated post-replication repair (PRR) mechanisms. Notably, treatment with an ATR inhibitor disrupted the DDUP/RAD18 interaction and abolished the effect of DDUP on prolonged DNA damage signaling, which resulted in the hypersensitivity of ovarian cancer cells to cisplatin-based therapy in vivo. Altogether, our study provides insights into DDUP-mediated aberrant DDR signaling in cisplatin resistance and describes a potential novel therapeutic approach for the management of platinum-resistant ovarian cancer.

Purpose: Accurate prediction of non-small cell lung cancer (NSCLC) progression is crucial for guiding clinical decision-making and alleviating patients’ psychological burden. Overtreatment risks unnecessary trauma for low-risk patients, while undertreatment may delay timely intervention for high-risk cases, worsening prognosis. This study aimed to develop a precise risk stratification system. The aim of this study is to develop an accurate risk stratification system to improve prediction accuracy and stratified management. To validate the proposed framework’s versatility and robustness, we conducted multiple cross-task validation experiments. Materials and methods: This retrospective study included 926 patients with resected stage I–IIA NSCLC who underwent radical surgery at four centers between January 2014 and September 2019. A multi-center intelligent risk stratification model FesCPI (Federated cross-scale Common–Personal–Interactive learning) was developed. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Model stability was assessed with five-fold cross-validation, and clinical utility was further validated through decision curve analysis (DCA). Additionally, cross-task experiments for gastric cancer and endometrial cancer were conducted to validate the model’s performance. Results: FedCPI consistently outperformed clinical stratification ((DeLong test, p < 0.05)) and federated learning baselines across multicenter tasks. In early-stage NSCLC, it achieved AUCs up to 0.9255 and ACCs up to 0.8909, with 4.23–15.95% gains over competing models. The framework continues to demonstrate outstanding performance in various tasks, including predicting gastric cancer recurrence and endometrial cancer infiltration, thereby validating the effectiveness of this methodology. Feature analyses confirmed complementary roles of VFMs and ResNet18, while ablation studies showed that both Large–Small Model Feature Decomposition and Fusion (LMSF) and Federated Adaptive Communication Mechanism (FACM) were indispensable for optimal performance. Conclusion: Our findings suggest that the DL(deep learning)-based FedCPI framework provides a non-invasive, accurate, and reliable tool for early-stage lung cancer risk stratification. Furthermore, the methodology demonstrated excellent performance in independent validation experiments for clinical tasks involving gastric cancer and endometrial cancer. By improving diagnostic precision, this approach has the potential to optimize clinical decision-making and reduce the burden of overtreatment for patients.