Oğuzcan Kınıkoğlu

Background: The optimal use of chemotherapy rechallenge in later-line metastatic colorectal cancer (mCRC) remains uncertain. We compared third-line FOLFOX plus bevacizumab rechallenge with regorafenib and examined whether the oxaliplatin-free interval was associated with treatment outcomes. Methods: This retrospective single-center study included 122 patients with metastatic left-sided, RAS (KRAS/NRAS) and BRAF wild-type, proficient mismatch repair (pMMR) colorectal adenocarcinoma treated between 2018 and 2025. All patients had received first-line FOLFOX plus cetuximab or panitumumab, followed by FOLFIRI plus bevacizumab after progression. In the third-line setting, 65 patients received FOLFOX plus bevacizumab as oxaliplatin rechallenge and 57 received regorafenib. The primary endpoint was progression-free survival (PFS). Cox regression, propensity score-based inverse probability of treatment weighting (IPTW), and treatment-by-oxaliplatin-free interval interaction analyses were performed. Results: Median third-line PFS was 7.33 months with FOLFOX plus bevacizumab rechallenge and 6.17 months with regorafenib (log-rank p < 0.001). FOLFOX plus bevacizumab rechallenge was associated with a lower hazard of progression in multivariable analysis (adjusted HR, 0.58; 95% CI, 0.39–0.88; p = 0.009), with consistent results in the propensity score-based IPTW sensitivity analysis (HR, 0.58; 95% CI, 0.40–0.86; p = 0.006). Restricted cubic spline analysis indicated a nonlinear association between OFI and PFS (p for nonlinearity = 0.005), while flexible modeling did not provide robust evidence of a treatment-by-OFI interaction (global p = 0.806). In exploratory subgroup analyses, FOLFOX plus bevacizumab rechallenge was associated with longer PFS than regorafenib among patients with an OFI of ≥6 months (adjusted HR, 0.39; 95% CI, 0.24–0.65; p < 0.001), whereas no significant difference was observed among those with an OFI of p = 0.199). Conclusions: FOLFOX plus bevacizumab rechallenge was associated with longer third-line PFS than regorafenib in this selected and uniformly treated mCRC cohort. OFI was associated with PFS in a nonlinear manner, but there was no robust evidence that it modified the relative treatment effect across its continuous range. Exploratory subgroup findings based on a 6-month cutoff require external validation.

Background/Objectives: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype characterized by substantial biological heterogeneity and variable clinical outcomes. Reliable prognostic tools are needed to improve risk stratification following neoadjuvant chemotherapy (NACT). This study aimed to evaluate the association of the Clinical–Pathologic Stage, Estrogen/Grade (CPS-EG) score with pathological complete response (pCR) and survival outcomes in patients with locally advanced TNBC treated with NACT. Methods: In this multicenter retrospective cohort study, 690 patients with locally advanced TNBC treated with NACT between 2010 and 2024 at 25 oncology centers were included. Patients were categorized according to CPS-EG score (≤3 vs. >3). Associations between CPS-EG score, clinicopathological characteristics, pCR, disease-free survival (DFS), and overall survival (OS) were analyzed. Survival outcomes were evaluated using Kaplan–Meier and Cox regression analyses. Results: Patients with a CPS-EG score > 3 had significantly lower pCR rates and higher recurrence rates compared with those with a CPS-EG score ≤ 3 (p < 0.001 for both). Five-year OS rates were 83.7% and 54.1% in the CPS-EG ≤ 3 and > 3 groups, respectively, while the corresponding five-year DFS rates were 76.4% and 51.9% (p < 0.001 for both). In the multivariable analysis, CPS-EG > 3 remained independently associated with worse OS (HR 1.46, 95% CI 1.08–1.98, p = 0.015) and DFS (HR 1.73, 95% CI 1.26–2.38, p < 0.001). Conclusions: A higher CPS-EG score is associated with a lower likelihood of achieving pCR and poorer long-term survival outcomes in patients with locally advanced TNBC treated with NACT. The CPS-EG score represents a simple and readily available tool that may support risk stratification and clinical decision-making in routine practice.

Background: Adrenocortical carcinoma (ACC) is a rare and aggressive endocrine malignancy, for which population-level evidence regarding prognostic factors and survival conditions is limited. The available data mostly represent single-institution series, limiting their applicability. This study, therefore, assesses clinicopathological features and determines independent predictive variables of overall survival (OS) in patients with ACC using a population-based cohort. Methods: This retrospective observational cohort study used data from the Surveillance, Epidemiology, and End Results (SEER) Program between 2000 and 2022, initially identifying 1176 patients with ACC. Adult patients (≥18 years) with histologically confirmed ACC were identified using ICD-O-3 histology code 8370/3 and primary site code C74.0. Cases with zero-month survival, missing survival data, or identified only through autopsy or death certificate were excluded. To ensure dataset harmonization, patients with missing or indeterminate tumor grade and unknown stage were also excluded. After applying these inclusion and exclusion criteria, the final analytic cohort consisted of 267 patients. Data on demographic factors, stage of the disease, and treatment (surgery, chemotherapy, radiotherapy) were extracted. OS was evaluated using the Kaplan–Meier method, and independent prognostic factors were identified using Cox proportional hazards regression analysis. Results: The median OS was 54 months [95% confidence intervals (CI): 36–85]. The estimated 1-, 3-, and 5-year OS rates were 77%, 57%, and 48%, respectively. Survival differed significantly according to tumor grade, stage, and surgical treatment. In multivariable Cox regression analysis, increasing age [Hazard ratio (HR): 1.03, 95% CI: 1.02–1.04; p < 0.001], high tumor grade (HR: 2.21, 95% CI: 1.43–3.41; p < 0.001), and distant-stage disease (HR: 3.24, 95% CI: 1.95–5.38; p < 0.001) were independently associated with an increased risk of mortality, whereas surgical treatment was associated with improved survival (HR 0.53, 95% CI 0.30–0.93; p = 0.028). Chemotherapy and radiotherapy were not significantly associated with mortality. Conclusions: In this SEER-based cohort of patients with adrenocortical carcinoma, older age, high tumor grade, and distant-stage disease were independently associated with worse OS, whereas documented receipt of surgery was associated with longer OS. Treatment-related associations should be interpreted cautiously in view of the inherent limitations of registry-based data. Further prospective multicenter studies are needed to confirm these findings.

Background/Objectives: Neoadjuvant dual HER2 blockade is standard for HER2-positive breast cancer, yet response rates vary based on tumor biology. This multicenter study aimed to identify clinicopathological predictors of pathological complete response (pCR), focusing on quantitative hormone receptor (HR) expression and HER2 staining intensity, and to evaluate their impact on survival. Methods: This multicenter retrospective study included 290 female patients diagnosed with HER2-positive early or locally advanced breast cancer treated with neoadjuvant trastuzumab and pertuzumab-based regimens (anthracycline-based [AC-THP] or non-anthracycline [TCHP]) across six centers. HR expression was stratified into low (p < 0.001) and strong HER2 overexpression (IHC Score 3) (OR = 2.20; p = 0.037) as primary predictors. Uniquely, patients with low HR expression (p = 0.001), biologically mimicking hormone-negative disease. The non-anthracycline TCHP regimen showed a strong trend toward superior efficacy (OR = 2.22; p = 0.054). pCR was the sole independent predictor of OS (HR = 0.134; p = 0.009). Crucially, adjusting for pCR unmasked hormone-negative status as a significant risk factor for recurrence (HR = 2.49; p = 0.028), highlighting its dual nature: high chemosensitivity but inherent biological aggression. Conclusions: “Strong” HER2 positivity and “weak” HR expression (<50%) are the primary determinants of pCR. pCR remains the strongest surrogate for survival, neutralizing initial risk factors. These findings support using quantitative biomarker thresholds for personalization and reinforce the efficacy of non-anthracycline regimens.

Background: Antibiotic exposure has been shown to negatively affect immune checkpoint inhibitor (ICI) efficacy in several cancers, possibly by disrupting gut microbiota. It represents a potentially modifiable clinical factor that may influence immunotherapy efficacy in RCC. However, data on renal cell carcinoma (RCC) remain limited, especially regarding prognostic risk groups. Methods: We conducted a retrospective cohort study of 120 RCC patients treated with ICIs between 2018 and 2024 at Kartal Dr. Lütfi Kırdar City Hospital. Patients were classified based on systemic antibiotic exposure within ±30 days of ICI start. Survival outcomes were compared using Kaplan–Meier and Cox regression analyses. Subgroup analyses were performed according to the International Metastatic RCC Database Consortium (IMDC) risk classification. Results: Of the 120 patients, 38 (31.7%) received antibiotics during the peri-ICI period. Median progression-free survival (PFS) was significantly shorter in the antibiotic-exposed group (5.1 vs. 9.4 months; p = 0.004), as was overall survival (OS) (14.8 vs. 22.5 months; p = 0.03). Antibiotic use remained an independent predictor of both PFS (HR = 1.87; 95% CI: 1.21–2.89) and OS (HR = 1.64; 95% CI: 1.04–2.59). In subgroup analyses, intermediate-risk patients had worse OS with antibiotics (13.5 vs. 20.6 months; p = 0.035), as did poor-risk patients (8.1 vs. 13.9 months; p = 0.049). Conclusions: Antibiotic exposure during the peri-immunotherapy period is linked to significantly poorer outcomes in RCC patients, especially those with intermediate and poor IMDC risk scores. These findings emphasize the importance of antimicrobial stewardship and suggest a potential role for microbiome-informed patient management in RCC.

Brigatinib, a next-generation anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitor, has demonstrated efficacy in pivotal trials in both pretreated and treatment-naïve patients with ALK-positive non-small-cell lung cancer (NSCLC). However, real-world evidence from large multicenter cohorts remains limited. We conducted a retrospective multicenter study including 114 patients with advanced ALK-positive NSCLC treated with brigatinib across 28 centers in Turkey between May 2020 and December 2024. Objective response rate (ORR) was assessed by RECIST v1.1. Median progression-free survival (mPFS) and overall survival (mOS) were estimated by the Kaplan-Meier method, and prognostic factors were analyzed using Cox regression. The median age was 55 years. Brigatinib was administered as first-line therapy in 68.4% of cases. In the overall cohort, the mPFS and OS were 24.2 and 44.2 months. The ORR was 70.2%. In the first-line setting, the ORR was 79.5%, with an mPFS of 28.6 months and an mOS of 50.3 months. In contrast, those treated in the second-line or later setting had less-favorable outcomes, which independently correlated with worse OS in multivariate analysis. Patients with baseline brain metastases achieved favorable outcomes, with an mPFS of 26.2 months, an mOS of 46.3 months, and an ORR of 76.5%. Adverse events were reported in 83.3% of patients, most commonly gastrointestinal toxicities, creatine phosphokinase elevation, and liver enzyme abnormalities. This nationwide multicenter study offers comprehensive real-world evidence confirming the effectiveness and tolerability of brigatinib in ALK-positive NSCLC, with especially favorable outcomes in the first-line setting and in patients with brain metastases.

Background: Time to prostate-specific antigen (PSA) nadir (TTN) has been proposed as an early indicator of treatment responsiveness in metastatic hormone-sensitive prostate cancer (mHSPC). However, its prognostic relevance in patients treated with next-generation androgen receptor pathway inhibitors (ARPIs), such as abiraterone or enzalutamide, remains incompletely defined. Methods: This retrospective cohort study included 147 patients with mHSPC treated with abiraterone or enzalutamide between 2019 and 2024. TTN, PSA kinetics, radiologic progression-free survival (rPFS), and PSA progression-free survival (PSA-PFS) were analyzed using Kaplan–Meier methods and multivariable Cox regression. TTN was evaluated both as a continuous variable and dichotomized at the cohort median (≤9 vs. >9 months). Results: TTN distributions were comparable between treatment groups (median 9.0 vs. 6.0 months, p = 0.197). Patients with a shorter TTN (≤9 months) experienced significantly longer median rPFS compared with those with longer TTN (>9 months) (10.7 vs. 7.95 months; p = 0.036). No significant association was observed between TTN and PSA-PFS (9.3 vs. 10.75 months; p = 0.34). In multivariable analysis, enzalutamide was independently associated with a reduced risk of radiologic progression compared with abiraterone (HR 0.622; 95% CI 0.441–0.877), whereas TTN was not an independent predictor. Conclusions: A shorter TTN was associated with improved radiologic outcomes, suggesting that rapid PSA suppression may reflect more favorable disease biology in patients receiving ARPI therapy. Although TTN showed limited value in predicting biochemical progression, it may serve as a simple and accessible biomarker for early risk stratification and tailoring follow-up intensity in mHSPC. Validation in larger, multicenter cohorts is warranted.

Background and Objectives: HER2-positive metastatic colorectal cancer (mCRC) represents a biologically distinct and clinically aggressive subtype associated with poor response to standard first-line chemotherapy. Reliable, low-cost prognostic biomarkers are urgently needed to identify early non-responders and guide treatment decisions. This real-world cohort study evaluated the prognostic value of carcinoembryonic antigen (CEA) kinetics and systemic inflammatory markers (SIMs) in HER2-positive mCRC treated with first-line chemotherapy. Materials and Methods: We retrospectively analyzed 98 patients with HER2-positive mCRC treated between 2015 and 2024. Serial CEA values were measured at baseline, after three cycles (week 6), and at radiologic progression. Early CEA change was categorized as ≥50% decline, 10–49% decline, or any increase. Baseline SIMs—including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII)—were calculated from pretreatment blood counts. Progression-free survival (PFS) was analyzed using Kaplan–Meier and Cox regression models. Results: Among patients with evaluable CEA kinetics (n = 60), early CEA increase occurred in 30% of patients (n = 18) and was strongly associated with inferior PFS (HR 2.84; 95% CI 1.81–4.44; p < 0.001). ROC analysis identified a ≥38% CEA reduction as the optimal predictor of radiologic response (AUC 0.79). High baseline NLR (≥3) and high SII (≥900) were also significantly associated with shorter PFS (median PFS: 5.2 vs. 9.1 months for NLR; 4.7 vs. 10.3 months for SII; both p < 0.01). In multivariate analysis, early CEA increase, high NLR, and high SII remained independent predictors of poor PFS. Conclusions: CEA dynamics and inflammation-based biomarkers provide robust, complementary prognostic information in HER2-positive mCRC. Early CEA increase is the strongest independent predictor of poor outcome, while high baseline NLR and SII further refine risk stratification. These inexpensive and widely accessible biomarkers may help identify early non-responders, optimize monitoring strategies, and support timely therapeutic adjustments in routine clinical practice.

Triple-negative breast cancer (TNBC) is an aggressive subtype with limited treatment options and poor prognosis. Effective prognostic tools are essential to guide risk-adapted strategies following neoadjuvant chemotherapy (NACT). In this multicenter retrospective study, we evaluated 690 patients with locally advanced TNBC treated between 2010 and 2023 across 25 oncology centers. Patients were stratified into CPS-EG risk groups: low (0–1), intermediate (2–3), and high (≥4). The CPS-EG score was strongly associated with pathological complete response (pCR), recurrence, disease-free survival (DFS), and overall survival (OS). Five-year DFS rates were 80.6%, 53.2%, and 31.5% in the low-, intermediate-, and high-risk groups, respectively, while OS rates were 76.7%, 53.2%, and 48.8% (p<0.001). Multivariate analysis confirmed CPS-EG as an independent predictor of both DFS and OS after adjusting for clinicopathological factors. These findings highlight the CPS-EG score as a simple, cost-effective, and widely applicable prognostic tool that may improve post-NACT risk stratification and support treatment decisions, especially in resource-limited oncology settings.

Background: Systemic inflammation is an essential factor in the formation of the tumor microenvironment and has an impact on patient response to immune checkpoint inhibitors. Although there is a growing interest in biomarkers of inflammation, there is a gap in understanding their predictive value for response to nivolumab in clinical practice. The objective of this research was to design and assess a multi-algorithmic machine learning (ML) model based on regular systemic inflammation measurements to forecast the response of treatment to nivolumab. Methods: An analysis of a retrospective real-world cohort of 177 nivolumab-treated patients was performed. Baseline inflammatory biomarkers, such as neutrophils, lymphocytes, platelets, CRP, LDH, albumin, and derived indices (NLR, PLR, SII), were derived. After preprocessing, 5 ML models (Logistic Regression, Random Forest, Gradient Boosting, Support Vector Machine, and Neural Network) were trained and tested on a 70/30 stratified split. Accuracy, AUC, precision, recall, F1-score, and Brier score were used to evaluate predictive performance. The interpretability of the model was analyzed based on feature-importance ranking and SHAP. Results: Gradient Boosting performed best in terms of discriminative (AUC = 0.816), whereas Support Vector Machine performed best on overall predictive profile (accuracy = 0.833; F1 = 0.909; recall = 1.00; and Brier Score = 0.134) performance. CRP and LDH became the most common predictors of all models, and then neutrophils and platelets. SHAP analysis has verified that high CRP and LDH were strong predictors that forced the prediction to non-response, whereas higher lymphocyte levels were weak predictors that increased the response probability prediction. Conclusions: Machine learning models based on common inflammatory systemic markers give useful predictive information about nivolumab response. Their discriminative ability is moderate, but the high performance of SVM and Gradient Boosting pays attention to the opportunities of inflammation-based ML tools in making personalized decisions regarding immunotherapy. A combination of clinical, radiomic, and molecular biomarkers in the future can increase predictive capabilities and clinical use.