Güngör Utkan

Background: Regorafenib is a standard late-line treatment for refractory metastatic colorectal cancer (mCRC), yet clinical outcomes remain heterogeneous. Identifying accessible biomarkers to predict therapeutic benefit is crucial for balancing efficacy and toxicity. This study evaluated the prognostic value of early dynamic changes in carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA-19-9). Methods: We conducted a retrospective real-world analysis of 61 heavily pretreated mCRC patients receiving regorafenib. Tumor markers were assessed at baseline and after the third cycle (approximately 12 weeks). Systematic threshold optimization using Cox proportional hazards regression and Akaike Information Criterion (AIC) was performed to identify optimal percentage change cutpoints for predicting survival. Results: The optimal thresholds for defining unfavorable marker increases were +14.6% for CEA and +23.5% for CA-19-9. Patients with CEA changes below the cutoff demonstrated significantly superior progression-free survival (PFS) (median 6.1 vs. 4.0 months, p = 0.012) and overall survival (OS) (11.05 vs. 6.0 months, p = 0.035). CA-19-9 changes below the cutoff were associated with improved PFS (p = 0.022) but did not reach statistical significance for OS (p = 0.23). In multivariable analysis, neither marker retained independent significance, likely due to collinearity. Conclusions: Early dynamics of routine tumor markers are prognostic in regorafenib-treated mCRC. specifically, a CEA increase of <14.6% significantly predicts improved survival outcomes. These findings support the utility of serial marker monitoring in real-world practice, though prospective validation is warranted.

Background: Relationship between vitamin D level and pathological response and survival in rectal cancer patients receiving neoadjuvant therapy, is an unstudied issue.Aim: We planned to investigate the relationship between vitamin D level and pathological response in this population.Materials and Methods: Patients diagnosed with rectal cancer and followed up at Ankara University Faculty of Medicine, Medical Oncology Clinic between January 2012 and May 2023 were included. Patients' demographic data, vitamin D level, stages, chemotherapy and radiotherapy protocols, type of surgery and postoperative pathological responses were recorded and compared statistically.Results: Eighty-three patients were included in the study. Median vitamin D level at the time of diagnosis was 15.89 ng/mL. Each 1-year increase in age was associated with a 0.22 ng/mL decrease in vitamin D levels. No significant relationship between vitamin D level and pathological response was found. Vitamin D levels were 13 ng/mL lower in stage 4 compared to stage 1 disease, but the difference was not significant. Relapse and survival rates were not significantly related with Vitamin D levels. When patients over 60 years of age were evaluated, vitamin D levels were significantly lower in patients with ypT4 against ypT0 disease. Conclusion: No significant relationship could be demonstrated between vitamin D levels and pathological response. More studies are needed to investigate the effect of vitamin D levels on prognosis and pathological response in older age and more advanced disease.

Objective: Splenectomy is frequently performed in abdominal malignancy surgeries due to direct tumor invasion, vascular injury, or for technical reasons. Although its association with bacterial infections is well documented, the effect of splenectomy on the risk and prognosis of viral infections, particularly COVID-19, remains unclear. To evaluate the incidence of postoperative COVID-19 infection and its prognostic impact in cancer patients undergoing abdominal surgery with and without splenectomy. Methods: This retrospective, single-center study analyzed 337 patients who underwent abdominal surgery for malignancy between March 2020 and March 2022. Forty-four patients underwent splenectomy as part of their oncologic procedure. COVID-19 status, demographic characteristics, comorbidity burden (Charlson Comorbidity Index), and survival outcomes were compared between patients who underwent splenectomy and those who did not. Logistic regression and Kaplan–Meier survival analyses were performed. Results: Postoperative COVID-19 infection occurred in 18.4% of all cancer patients and in 17.7% of those who underwent splenectomy. Splenectomy was not associated with a statistically significant increase in COVID-19 risk (odds ratio (OR): 1.58; 95% CI: 0.75-3.33; P = .22). This finding remained consistent after adjustment for comorbidities (OR: 1.50; 95% CI: 0.70-3.19; P = .29). Similarly, COVID-19 infection was not a significant predictor of mortality in the splenectomy group (adjusted OR: 1.02; 95% CI: 0.22-4.59; P = .97). Kaplan–Meier survival analysis revealed comparable overall survival between patients with and without splenectomy, with no statistically significant difference observed (log-rank test, P = .54). Conclusion: Splenectomy in patients with abdominal malignancies was not found to be a risk factor for acquiring COVID-19 or for poor survival outcomes following infection. While this study suggests no detrimental effect of splenectomy on the clinical course of COVID-19 in patients with cancer, more comprehensive prospective investigations are necessary to support this conclusion. Cite this article as: Deryol R, Avşar G, Hakseven M, Çulcu S, Utkan G, Ünal AE. Splenectomy does not increase COVID-19 risk or mortality in abdominal cancer surgery: A retrospective cohort analysis. Cerrahpaşa Med J. 2026, 50, 0076, doi:10.5152/ cjm.2026.25076.

Aim: Regorafenib is a standard treatment for metastatic colorectal cancer (mCRC), typically administered at a dose of 160 mg/day. This study evaluates the efficacy and tolerability of lower doses of regorafenib compared to the standard dose.Material and Methods: A total of 58 mCRC patients were divided into two groups: low-dose (≤120 mg/day) and high-dose (>120 mg/day). We assessed disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and adverse events (AEs). Dose modifications and treatment discontinuations were recorded.Results: 58 patients with a median age of 57 years were included. Regorafenib was administered as a median fourth-line treatment, with 34 patients in the low-dose group and 24 in the high-dose group. Disease control rates were 37.9%, with no significant difference between low-dose and high-dose groups (35.3% vs. 41.7%, P=0.625). Median PFS was similar between the groups [3.3 months (95% CI: 2.2-4.3) vs. 4.1 months (95% CI: 2.3-5.8), P=0.695]. OS was also comparable across groups [7.8 months (95% CI: 5.8-9.7) vs. 10.3 months (95% CI: 5.1-15.5), P=0.213]. AEs were reported in 89.6% of patients, with a significantly higher rate of dose reductions or discontinuations in the high-dose group (41.7% vs. 11.8%, P=0.013).Conclusion: Lower doses of regorafenib (≤120 mg/day) provide comparable efficacy and similar disease control rates to the standard dose. The high-dose regimen is associated with greater tolerability issues, suggesting that lower doses may be a viable alternative for better patient management.

Ejmi Eurasian Journal of Medical Investigation

Lactate Dehydrogenase in Patients with Metastatic Colorectal Cancer: Retrospective Study to Explore a Target Subgroup for Utilization as a Tumor Marker - Turkish Journal of Colorectal Disease

Purpose Accurate prognostication in metastatic colorectal cancer (mCRC) remains challenging due to disease heterogeneity. This study aimed to develop and validate an artificial intelligence-augmented deep learning model for risk stratification in patients receiving first-line treatment. Methods/patients We developed a deep neural network with artificial intelligence augmentation, using data from patients with de novo mCRC treated at two major reference centers between 2010 and 2024. Patients with BRAF-mutated and MSI-high tumors were excluded. The model incorporated clinical characteristics, laboratory parameters, and treatment data. The primary outcome was progression-free survival (PFS). Results A total of 214 patients were included in the study, with 127 patients in the training and internal validation cohort and 87 patients in the external validation cohort. The model stratified patients into three distinct risk groups with significantly different PFS (log-rank p < 0.001). The low-risk group (n = 34) achieved a median PFS of 16.8 months with a 29% event rate, the medium-risk group (n = 33) showed a median PFS of 9.3 months with a 58% event rate, and the high-risk group (n = 34) demonstrated a median PFS of 7.5 months with a 76% event rate. Feature importance analysis identified carcinoembryonic antigen, neutrophil/lymphocyte ratio, and liver function tests as the strongest predictors of PFS. The model’s performance was consistent across both internal and external validation cohorts. Conclusions This deep learning model demonstrates robust prognostic capabilities in mCRC, effectively stratifying patients into distinct risk groups. The model could aid in clinical decision-making and treatment planning for patients receiving first-line therapy.

Ewing sarcoma (ES) mainly affects children and adolescents; thus, treatment protocols for adult patients are adapted from pediatric protocols. Long treatment durations often lead to treatment discontinuation for adults. This single-center retrospective study evaluated real-world outcomes and compliance with standard chemotherapy regimens in adult patients with localized ES. Adult patients diagnosed with localized ES who underwent curative intent treatment between 2007 and 2022 were retrospectively analyzed. Patients who were intended to receive the vincristine, adriamycin, and cyclophosphamide (VAC)/(ifosfamide, etoposide) regimen, consisting of 18 cycles along with local treatment, were included in this study. Adherence to the treatment protocol and outcomes were evaluated. Event-free survival (EFS) and overall survival were calculated, and predictors of treatment completion were assessed. A total of 31 patients were analyzed. Median age was 28 years (range, 18–71 yr); 17 patients were male (54.8%) and 14 were female (45.2%). Fourteen (45.1%) patients underwent surgery, 10 (32.3%) received radiotherapy, and 7 (22.5%) received both treatments. Eighteen (58.1%) patients completed 18 chemotherapy cycles. Patients undergoing surgical resection were likelier to complete all the chemotherapy cycles (odds ratio: 0.117, 95% confidence interval: 0.016–0.835). The estimated 5-year EFS and overall survival rates were 37% and 58%, respectively. Multivariate analysis identified a neutrophil-lymphocyte ratio ≥ 5 as an independent predictor of EFS (hazard ratio: 4.50, 95% confidence interval: 1.52–13.30, P = .006). Compliance with the 51-week-long vincristine, adriamycin (doxorubicin), and cyclophosphamide/ifosfamide and etoposide chemotherapy regimen remains a critical issue for adult patients. Our findings suggest that surgical resection may be associated with better compliance with the chemotherapy protocol, and a neutrophil-lymphocyte ratio of ≥5 may be linked to poorer outcomes.

Liver is the most common metastatic site in colorectal cancer. This study aims to evaluate the effectiveness of different machine learning (ML) models in predicting liver metastasis in CRC patients using routine biochemical tests. Cross-sectional study employed various ML algorithms for predictive modeling. The study was conducted at two academic reference centers in Ankara, Turkey: a total of 810 CRC patients diagnosed between January 2010 and December 2023 were included. The training and internal validation dataset comprised 710, and external validation dataset included 100 patients. Inclusion criteria were patients aged ≥ 18 years with a pathological CRC diagnosis, pre-treatment biochemical tests, and known initial staging. Exclusion criteria encompassed non-adenocarcinoma histologies, incomplete biochemical data, other malignancies. Logistic regression achieved the highest internal validation AUC (0.956), accuracy (0.901), and F1 score (0.936), with a sensitivity of 0.971 and specificity of 0.703. ElasticNet and Lasso regression followed closely with AUCs of 0.958. In external validation, logistic regression maintained high performance (AUC 0.951, accuracy 0.900), while the K-nearest neighbors (KNN) model achieved perfect sensitivity (1.0) with an AUC of 0.891. The optimal predictor combination included ALP, LDH, CEA, and CA-19-9. Different ML models, can effectively predict liver metastasis in CRC patients using routine biochemical tests. Further refinement and prospective clinical trials are necessary to validate and implement these predictive tools in clinical practice.