Introduction and importance: Poorly differentiated thyroid carcinomas represent a rare heterogeneous group of malignant tumors that constitute ~2–4% of all thyroid neoplasms. Substernal goiter (SG) is defined as an enlargement of the thyroid gland that is located below the thoracic inlet. Malignant neoplasms arising from a SG were reported in only 2–3% of cases. This case report has been reported in line with the Surgical CAse REport (SCARE) Criteria. ²¹ Case presentation: This article presents a 54-year-old Syrian female who presented at our institution due to dysphagia, dyspnea, cervical swelling, and loss of appetite. Following clinical and radiological examinations, total thyroidectomy with lymph node dissection was performed. Microscopic examination revealed an infiltrative growth pattern of insular, trabecular, and solid formations of epithelial cells with scant eosinophilic cytoplasm, hyperchromatic nuclei, and bizarre mitotic figures with areas of necrosis. Subsequently, the final diagnosis was confirmed as a multifocal poorly differentiated thyroid carcinoma arising from a SG. Clinical discussion: The heterogeneity of histologic features of poorly differentiated thyroid carcinoma represents a diagnostic challenge. Diagnosis of poorly differentiated thyroid carcinomas is based on the Turin Criteria, which highlights histopathological features. Computed tomography plays a major role in SG for further evaluation. Conclusion: In this manuscript, the authors aimed to present a unique case report with challenging diagnostic features including the rapid development of an infiltrative poorly differentiated thyroid carcinoma from a SG highlighting the importance of a detailed histopathological examination of thyroid nodules in the absence of significant medical history.

Despite the high burden and regional variability of ovarian cancer (OC), data on its status in Syria, a country impacted by long-standing conflict, remain scarce. This study aimed to provide the first nationwide analysis of OC epidemiological and clinicopathological characteristics. In this national, multicenter, retrospective cross-sectional study, we collected data from three tertiary referral university hospitals in Syria: Tishreen University Hospital, Al-Bairouni University Hospital, and Ibn Rushd Hospital. The inclusion period spanned from 2017 to 2021. All included patients were 18 years or older and had a newly diagnosed, confirmed primary OC. Data collected included sociodemographic information, presenting symptoms, CA-125 levels, and treatment details. A total of 531 patients with OC with a mean age of 53.1 years (range: 18–91) were included in the study, representing 1.2% (95% confidence interval: 1.1%-1.3%) of the 44,248 patients diagnosed with all types of cancer. Serous carcinoma (55.4%) was the most common OC subtype, followed by mucinous (13.8%) and endometrioid carcinoma (9.7%). Among epithelial OCs, having high levels of CA-125 was associated with higher odds of serous carcinoma (adjusted OR: 2.30, 95% CI: 1.08–4.91) and lower odds of endometrioid cancer adjusted OR: 0.21, 95% CI: 0.08–0.54). Abdominal bloating was the most frequently reported symptom, affecting 194 patients (36.5%). Our study revealed a lower proportion of OCs diagnoses among all cancer cases compared to global and regional data which may be attributed to underreporting, influenced by the disease’s specific characteristics and presence of more barriers for women to healthcare access in Syria’s conflict-affected setting. Given the study’s limitations, further research is essential to provide a more comprehensive assessment of the OC burden in Syria.

Males and females are known to age differently and develop certain diseases at different rates. Here, we examined the livers of aged male and female mice to see if they show different DNA methylation patterns. We found that aged male and female mice had distinct DNA methylation patterns at specific genes. Interestingly, most of these methylation differences were not present in younger mice, suggesting that sex differences in the genome may change with age.

Background/Objectives: Universal surgical risk calculators are not validated for use and poorly predict postoperative morbidity and mortality for women undergoing gynaecological oncology surgery. This adversely affects communication of risk resulting in poorly informed decisions and missed opportunities for medical optimization to mitigate risk preoperatively. We present the development and external validation of our novel GO SOAR surgical risk calculator for use to preoperatively predict postoperative thirty-day surgical morbidity and mortality in relation to gynaecological oncology surgeries. Methods: New logistic regression models were developed using the GO SOAR1 training cohort (n = 1811) and externally validated in an independent prospective cohort (n = 416) for two outcomes: thirty-day postoperative mortality (alive versus dead) and thirty-day postoperative morbidity (any complication (Clavien–Dindo I–V) versus none). Performance of the GO SOAR models was compared against established all-purpose surgical risk calculators (SORT/POSSUM/P-POSSUM/NSQIP). Model discrimination was assessed with sensitivity calculated at a clinically significant prespecified specificity threshold of 90%. Results: For mortality, AUROC was 0.752 (95% CI 0.570–0.935) for GO SOAR full and 0.795 (95% CI 0.660–0.930) for GO SOAR condensed; corresponding sensitivities at 90% specificity were 57.1% and 42.9%. For morbidity, AUROC was 0.698 (95% CI 0.641–0.755) and 0.703 (95% CI 0.646–0.760) for the full and condensed models, respectively, with sensitivities of 30.4% and 32.1% at 90% specificity. Conclusions: The GO SOAR model using a data-driven, gynaecological-oncology-specific approach at 90% specificity, achieved the highest observed sensitivity among the evaluated calculators. Accurate surgical risk predictions are crucial for major oncological surgery, where complications can diminish quality of life and affect long-term cancer survival. A model such as the GO SOAR surgical risk calculator that uses readily available preoperative data, regardless of income setting, is essential in reducing global disparities in surgical outcomes.