Background: Multidisciplinary Tumor Councils (MDTs) are vital platforms that provide tailored treatment plans for cancer patients by combining expertise from various medical disciplines. Recently, Artificial Intelligence (AI) tools have been investigated as decision-support systems within these councils. Methods: In this prospective study, the compatibility of AI (ChatGPT-4.0) with MDT decisions was evaluated in 100 cancer patients presented to the tumor council between November 2024 and January 2025. AI-generated treatment recommendations based on anonymized, detailed clinical summaries were compared with real-time MDT decisions. Cohen’s Kappa and Spearman correlation tests were used for statistical analysis. Results: Neoadjuvant treatment (45%) and surgery (36%) were the most frequent MDT decisions. AI recommended surgery (39%) and neoadjuvant treatment (37%) most frequently. A high concordance rate of 76.4% was observed between AI and MDT decisions (κ = 0.764 [95% CI; 0.658–0.870] p < 0.001, ρ = 0.810 [95% CI; 0.729–0.868], p < 0.001). Most inconsistencies arose in cases requiring individualized decisions, indicating AI’s current limitations in incorporating contextual clinical judgment. Conclusion: AI demonstrates substantial agreement with MDT decisions, particularly in cases adhering to standardized oncological guidelines. However, for AI integration into clinical workflows, it must evolve to interpret real-time patient data and function transparently within ethical and legal frameworks.

Objectives: Spontaneous bacterial peritonitis (SBP) is a serious infectious complication in patients with decompensated cirrhosis. Although serum procalcitonin (PCT) has been evaluated as a potential indicator of bacterial infection, its clinical value in the diagnosis of SBP remains uncertain. This study investigated the diagnostic contribution of serum procalcitonin in cirrhotic patients with SBP. Methods: This prospective, single-center study included 100 participants: 50 patients with SBP, 25 patients with sterile ascites, and 25 healthy controls. The diagnosis of SBP was established according to the ascitic fluid polymorphonuclear leukocyte (PMNL) count and/or positive ascitic fluid culture findings. Serum procalcitonin levels and ascitic inflammatory parameters were compared among the study groups. Results: Serum procalcitonin levels were numerically higher in patients with SBP than in patients with sterile ascites and healthy controls; however, the differences were not statistically significant (p>0.05). In contrast, ascitic fluid leukocyte and PMNL counts were significantly elevated in the SBP group (p

Aims: Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, with limited survival despite multimodal treatment. This retrospective study evaluated the prognostic impact molecular markers and clinical factors on survival outcomes in a real world GBM cohort. Methods: We conducted a retrospective analysis of 60 patients diagnosed with GBM between 2020 and 2023. Clinical, radiological, surgical, and molecular data were retrospectively collected. Overall survival (OS) and progression-free survival (PFS) were analyzed using Kaplan-Meier curves, with compared with log-rank test. Multivariable Cox regression analysis was performed to identify independent prognostic factors. Results: Median OS and PFS for the entire cohort were 16.5 and 9.8 months, respectively. Molecular markers were the strongest prognostic factors: IDH-mutant and MGMT-methylated tumors showed significantly prolonged OS and PFS compared to their wild-type/unmethylated counterparts (p

Association of Tumor Distribution Pattern with Stage at Diagnosis and Presentation Pattern in Patients with Invasive Breast Cancer - Bagcilar Medical Bulletin

Aims: Gastric epithelial dysplasia is a well-recognized precursor lesion in gastric carcinogenesis; however, the prognostic significance of documented dysplasia after the development of metastatic gastric adenocarcinoma remains uncertain. This study investigated the association between documented dysplasia, clinicopathological characteristics, and survival outcomes in patients with metastatic gastric adenocarcinoma. Methods: In this retrospective cohort study, consecutive patients with histopathologically confirmed metastatic gastric adenocarcinoma who received first-line systemic chemotherapy between January 2020 and December 2024 at a tertiary referral center were included. Clinicopathological characteristics, treatment data, laboratory findings, and survival outcomes were retrieved from institutional medical records. Overall survival (OS) was the primary endpoint, and OS and progression-free survival (PFS) were estimated using the Kaplan–Meier method. Prognostic factors for OS were evaluated using Cox proportional hazards regression. Results: A total of 67 patients were included (median age, 63.7 years; 77.6% male), of whom 21 (31.3%) had documented dysplasia. Median follow-up estimated using the reverse Kaplan–Meier method was 34.13 months (95% CI, 23.0–not estimable). Median PFS was 5.77 months (95% CI, 4.03–6.90), and median OS was 10.40 months (95% CI, 7.90–12.00). Patients with documented dysplasia had significantly shorter OS than those with no documented dysplasia (6.0 vs 10.9 months; log-rank p=0.012). In the forward-stepwise multivariable Cox regression model, higher ECOG performance status (HR 2.528, 95% CI 1.645–3.885; p

Background: Prognostic assessment after neoadjuvant chemotherapy and curative gastrectomy remains challenging in patients with gastric adenocarcinoma because postoperative outcomes are influenced by both pretreatment disease burden and pathological response. We aimed to develop and internally validate a clinicopathological prognostic model and a simple postoperative risk classification for predicting disease-free survival (DFS). Methods: This single-center retrospective cohort study included patients with gastric adenocarcinoma who underwent neoadjuvant chemotherapy followed by curative gastrectomy. Pretreatment clinicopathological variables, Becker tumor regression grade (TRG), and serum tumor markers were evaluated. Logistic regression was used to identify predictors of favorable pathological response, whereas Cox proportional hazards regression was performed to identify independent prognostic factors for disease-free survival (DFS). Sequential prognostic models were developed and internally validated using 1000 bootstrap resamples. A simplified postoperative clinicopathological risk classification based on pretreatment clinical N stage and Becker tumor regression grade was additionally developed to facilitate clinical interpretation and postoperative risk stratification. Results: A total of 109 patients were included. Favorable pathological response (Becker TRG1–2) was achieved in 68 patients (62.4%), whereas 41 patients (37.6%) had minimal or no pathological response (TRG3). In multivariable logistic regression analysis, pretreatment clinical T stage (cT4 vs. cT1–3) and clinical N stage (cN2–3 vs. cN0–1) were independently associated with a lower likelihood of achieving a favorable pathological response. For disease-free survival, pretreatment clinical N stage, Becker tumor regression grade, and log10-transformed CA19-9 remained independent prognostic factors in the multivariable Cox model. Sequential model development demonstrated progressive improvement in model discrimination, with the optimism-corrected Harrell’s C-index increasing from 0.697 for the clinical N stage model to 0.770 for the final model incorporating clinical N stage, Becker tumor regression grade, and CA19-9. Bootstrap internal validation demonstrated minimal optimism, and calibration analysis showed good agreement between predicted and observed disease-free survival. A simple postoperative clinicopathological risk classification successfully stratified patients into distinct prognostic groups. Conclusions: A clinicopathological prognostic model integrating pretreatment clinical N stage, Becker tumor regression grade, and serum CA19-9 demonstrated improved prognostic discrimination for disease-free survival compared with clinical N stage alone. The derived postoperative risk classification may provide a simple framework for postoperative risk stratification and could assist in individualizing postoperative surveillance. External validation is warranted before routine clinical implementation.