Background and Objectives: Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy, but their use is associated with a spectrum of immune-related adverse events (irAEs), including endocrine disorders. This study aims to investigate the incidence, timing, treatment modalities, and impact of ICI-related endocrine side effects in cancer patients. Materials and Methods: This retrospective study analyzed 139 cancer patients treated with ICIs between 2016 and 2022. Data regarding endocrine irAEs, including hypothyroidism, hyperthyroidism, hypophysitis, and diabetes mellitus, were collected. The study examined the timing of irAE onset, management approaches, and the association between irAEs and treatment outcomes. Results: The most common endocrine irAE was hypothyroidism (65.5%), followed by hyperthyroidism (2.3%), hypophysitis (8.6%), and diabetes mellitus (0.7%). These disorders typically emerged within the first six months of ICI therapy. Most cases were managed conservatively or with hormone replacement therapy. Patients who developed endocrine irAEs exhibited a higher objective response rate (ORR) and clinical benefit rate (CBR) compared to those without irAEs. Conclusions: Endocrine dysfunction is a significant toxicity of ICI therapy. Early recognition, prompt diagnosis, and appropriate management are crucial to minimize their impact on patient health and quality of life. This study highlights the potential association between irAEs and improved clinical outcomes. Further research is needed to elucidate the underlying mechanisms and identify predictive biomarkers for irAE development.

Background and Objectives: Abdominal compartment syndrome (ACS) is a severe clinical condition caused by intra-abdominal hypertension (IAH), often observed in surgical and trauma patients. However, ACS can also develop in non-surgical patients with massive ascites, leading to acute kidney injury (AKI) due to renal hypoperfusion. This study investigates the association between intra-abdominal pressure (IAP) changes, renal biomarkers, and mortality in patients with ACS-related AKI. Materials and Methods: A prospective cohort study was conducted on 24 hospitalized patients with ascites due to malignancy, cirrhosis, or heart failure. IAP was measured via the trans-vesical method on the first and seventh days of hospitalization. Serum and urinary biomarkers, including kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), and interleukin-6 (IL-6), were assessed for their correlation with IAP changes. The primary outcome was in-hospital mortality, and the secondary outcomes included AKI progression and the effect of paracentesis on IAP reduction. Results: The overall in-hospital mortality rate was 50%. Patients who survived had significantly lower IAP on the seventh day compared to those who died (14.9 ± 3.5 mmHg vs. 20.2 ± 5.6 mmHg, p = 0.01). A 25% reduction in IAP was associated with improved kidney function and increased survival (p < 0.001). Urinary KIM-1 and serum NGAL levels showed a moderate correlation with IAP (r = 0.55, p = 0.02 and r = 0.61, p = 0.018, respectively), while IL-6 levels were significantly higher in non-survivors (p = 0.03). Paracentesis was associated with improved survival outcomes (p = 0.04). Conclusions: ACS is a critical but often overlooked cause of AKI in non-surgical patients with massive ascites. Lowering IAP significantly improves renal function and reduces mortality. Urinary KIM-1 and serum NGAL may serve as useful biomarkers for monitoring IAP changes. The early identification and management of IAH through timely interventions such as paracentesis and volume control strategies could improve patient outcomes.

Immune checkpoint inhibitors (ICIs) therapy has revolutionized cancer treatment. However, it is important to acknowledge that ICI therapy can lead to immune-related adverse events (irAEs), including myocarditis. While early-onset myocarditis is well-documented, late-onset cases are increasingly recognized. This case series presents four cases of late-onset ICI-associated myocarditis, emphasizing the need for long-term surveillance of this potentially fatal complication. Patients exhibited a range of cardiac symptoms, including chest pain, shortness of breath, and arrhythmias. The diagnosis was confirmed through cardiac magnetic resonance imaging (MRI) and elevated cardiac biomarkers. Treatment involved the immediate discontinuation of ICI therapy and the initiation of high-dose corticosteroids. In cases with an inadequate response, additional immunosuppressive agents were considered. This case series underscores the importance of prolonged monitoring for late-onset ICI-associated myocarditis. Further research is needed to establish optimal treatment strategies and long-term management approaches for this complex condition.

Background and Objectives: Epithelial ovarian cancer (EOC) remains a significant global health challenge. While traditional prognostic factors are well established, emerging biomarkers continue to gain attention. Materials and Methods: This retrospective study evaluated the impact of systemic inflammatory markers on progression-free survival (PFS) and overall survival (OS) in 154 EOC patients. Pre-treatment neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and systemic inflammatory index (SII) were calculated and categorized into low and high groups. Univariate and multivariate analyses were conducted to identify independent prognostic factors, while logistic regression analysis was used to determine predictors of platinum resistance. Results: In the univariate analysis, elevated NLR and PLR were associated with poorer PFS and OS. However, these markers did not maintain statistical significance in the multivariate analysis. Although SII demonstrated a trend toward worse outcomes, it did not reach statistical significance. Histopathological type, PLR, and surgical approach were identified as independent predictors of platinum resistance. Conclusions: Our findings indicate that systemic inflammatory markers may hold prognostic value in EOC; however, further validation through larger prospective studies is necessary.

Background: Although higher-generation TKIs are associated with improved progression-free survival in advanced NSCLC patients with EGFR mutations, the optimal selection of TKI treatment remains uncertain. To address this gap, we developed a web application powered by a reinforcement learning (RL) algorithm to assist in guiding initial TKI treatment decisions. Methods: Clinical and mutational data from advanced NSCLC patients were retrospectively collected from 14 medical centers. Only patients with complete data and sufficient follow-up were included. Multiple supervised machine learning models were tested, with the Extra Trees Classifier (ETC) identified as the most effective for predicting progression-free survival. Feature importance scores were calculated by the ETC, and features were then integrated into a Deep Q-Network (DQN) RL algorithm. The RL model was designed to select optimal TKI generation and a treatment line for each patient and was embedded into an open-source web application for experimental clinical use. Results: In total, 318 cases of EGFR-mutant advanced NSCLC were analyzed, with a median patient age of 63. A total of 52.2% of patients were female, and 83.3% had ECOG scores of 0 or 1. The top three most influential features identified were neutrophil-to-lymphocyte ratio (log-transformed), age (log-transformed), and the treatment line of TKI administration, as tested by the ETC algorithm, with an area under curve (AUC) value of 0.73, whereas the DQN RL algorithm achieved a higher AUC value of 0.80, assigning distinct Q-values across four TKI treatment categories. This supports the decision-making process in the web-based ‘EGFR Mutant NSCLC Treatment Advisory System’, where clinicians can input patient-specific data to receive tailored recommendations. Conclusions: The RL-based web application shows promise in assisting TKI treatment selection for EGFR-mutant advanced NSCLC patients, underscoring the potential for reinforcement learning to enhance decision-making in oncology care.

Background/Objectives: Extrapulmonary neuroendocrine carcinomas (EP-NECs) are rare, aggressive malignancies with no standardized treatment approach. Although platinum-based chemotherapy is considered the first-line therapy, overall survival (OS) and progression-free survival (PFS) remain limited. This study aims to evaluate the clinical and pathological characteristics of EP-NEC patients, their treatment responses, and survival outcomes. Methods: This retrospective observational study included 29 EP-NEC patients diagnosed and followed between 2015 and 2024. Clinical and demographic data, tumor localization, disease stage, administered treatments, and survival outcomes were analyzed. Kaplan–Meier survival analysis was used to assess OS and PFS, with subgroup comparisons performed via the log-rank test. Results: The most common primary tumor sites were the pancreas (21%), prostate (17%), and cervix (14%). At diagnosis, 55.2% of patients had metastatic disease. First-line platinum-based chemotherapy achieved an objective response rate of 82.1%, with a median PFS of 8.16 months and a median OS of 14.16 months. Surgical intervention significantly improved survival (p = 0.020), while a high Ki-67 proliferation index (>80%) was associated with worse PFS (p = 0.032). Other factors, including smoking status and liver-directed therapies, had no significant impact on survival. Conclusions: EP-NECs present with a poor prognosis despite platinum-based chemotherapy achieving high response rates. Surgical resection improves survival outcomes, whereas high Ki-67 expression is associated with a worse prognosis. These findings highlight the need for further research into novel therapeutic strategies for EP-NECs.