Background: Pathological complete response (pCR) following neoadjuvant therapy (NAT) is a key surrogate marker for long-term outcomes in HER2-positive breast cancer. Identifying clinical and biological predictors of pCR, including systemic inflammatory and nutritional markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), neutrophil-to-albumin ratio (NAR), C-reactive protein-to-albumin ratio (CAR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI), may help refine treatment strategies and improve patient outcomes. Methods: We retrospectively analyzed 174 patients with stage II–III HER2-positive breast cancer who received neoadjuvant anti-HER2-based regimens at multiple centers between 2010 and 2025. Demographic, clinicopathological, and laboratory data were collected, and inflammatory and nutritional indices (NLR, PLR, LMR, NAR, CAR, SII, PNI) were calculated. Predictors of pCR were evaluated using univariate and multivariate logistic regression analyses. Results: Overall, 49% of patients achieved pCR. In multivariate analysis, independent predictors of pCR were hormone receptor negativity, smaller tumor size, HER2 IHC 3+ expression, dual HER2 blockade, and a higher prognostic nutritional index (PNI ≥ 55). In contrast, systemic inflammatory indices such as NLR, PLR, LMR, NAR, CAR, and SII were not significantly associated with pCR. Conclusions: This multicenter real-world study demonstrates that conventional inflammatory markers have limited predictive value, whereas the PNI emerges as a simple and practical biomarker reflecting nutritional and immune status. Integrating PNI with clinicopathological factors may enhance risk stratification and help guide individualized neoadjuvant treatment strategies in HER2-positive breast cancer.

Objective: Patients with solid malignancies are more vulnerable to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection than the healthy population. The outcome of SARS-CoV-2 infection in highly immunosuppressed populations, such as in patients with hematological malignancies, is a point of interest. We aimed to analyze the symptoms, complications, intensive care unit admissions, and mortality rates of patients with hematological malignancies infected with SARS-CoV-2 in Turkey. Materials and Methods: In this multicenter study, we included 340 adult and pediatric patients diagnosed with SARS-CoV-2 from March to November 2020. Diagnosis and status of primary disease, treatment schedules for hematological malignancies, time from last treatment, life expectancy related to the hematological disease, and comorbidities were recorded, together with data regarding symptoms, treatment, and outcome of SARS-CoV-2 infection. Results: Forty four patients were asymptomatic at diagnosis of SARSCoV-2 infection. Among symptomatic patients, fever, cough, and dyspnea were observed in 62.6%, 48.8%, and 41.8%, respectively. Sixtynine (20%) patients had mild SARS-CoV-2 disease, whereas moderate, severe, and critical disease was reported in 101 (29%), 71 (20%), and 55 (16%) patients, respectively. Of the entire cohort, 251 (73.8%) patients were hospitalized for SARS-CoV-2. Mortality related to SARS-CoV-2 infection was 26.5% in the entire cohort; this comprised 4.4% of those patients with mild disease, 12.4% of those with moderate disease, and 83% of those with severe or critical disease. Active hematological disease, lower life expectancy related to primary hematological disease, neutropenia at diagnosis of SARS-CoV-2, ICU admission, and first-line therapy used for coronavirus disease-2019 treatment were found to be related to higher mortality rates. Treatments with hydroxychloroquine alone or in combination with azithromycin were associated with a higher rate of mortality in comparison to favipiravir use. Conclusion: Patients with hematological malignancy infected with SARS-CoV-2 have an increased risk of severe disease and mortality.

Adjuvant chemotherapy decision-making in stage II colon cancer remains challenging. Although multidisciplinary tumor boards (MDTs) guide treatment, their recommendations vary. Artificial intelligence (AI) tools such as ChatGPT may support decision-making, but direct comparative evidence with MDTs is limited. We retrospectively analyzed 179 patients with stage II colon cancer who underwent surgery between 2019-2024. MDT recommendations (observation, fluoropyrimidine monotherapy, or oxaliplatin-based chemotherapy) were compared with ChatGPT-5 outputs. Clinical factors - including age, ECOG performance status (PS), tumor stage, minor risk factors, and mismatch repair (MMR) status - were incorporated. Agreement was evaluated using Cohen's kappa (κ) and McNemar's test. Across the three treatment categories, agreement between MDT and AI was moderate (70.4%, κ = 0.542, p < 0.001), while in the binary comparison of adjuvant therapy versus observation, concordance improved to substantial (91.1%, κ = 0.719, p < 0.001). Discordance mainly reflected AI's tendency to escalate therapy. Agreement decreased in patients ≥70 years, those with ECOG PS 2, and those with multiple risk factors. AI showed moderate agreement with MDTs in detailed three-category recommendations but substantial concordance in binary adjuvant decisions. While AI may serve as a supportive tool, clinical judgment remains essential, particularly for elderly and frail patients.

Background and Objectives: Breast cancer is a leading cause of cancer-related mortality, particularly in aggressive subtypes such as HER2-positive and triple-negative breast cancer (TNBC). Achieving a pathological complete response (pCR) after neoadjuvant therapy is strongly associated with improved survival outcomes in these subgroups, making the prediction of pCR a clinical priority. Sarcopenia, a progressive loss of skeletal muscle mass and strength, is increasingly recognized in cancer patients and has been linked to chemotherapy toxicity and poorer survival. However, its specific impact on pCR in HER2-positive and TNBC patients remains unclear. This study aimed to evaluate the association between radiologically defined sarcopenia, or a low skeletal muscle index (SMI), and pathological response in these subtypes, and to explore its potential as a predictive biomarker. Materials and Methods: This retrospective study included patients with HER2-positive or TNBC who received neoadjuvant therapy between January 2015 and October 2023. SMI was assessed using pre-treatment positron emission tomography images at the L3 vertebral level, with values < 38.5 cm²/m² considered as low. Univariate and multivariate logistic regression analyses were performed to identify factors associated with pCR. Results: A total of 85 patients were included, with low SMI present in 35 (41.2%). In univariate analysis, clinical stage and low SMI were associated with pCR. However, in the multivariate model, only low SMI remained an independent predictor. Patients without low SMI had higher odds of achieving pCR (odds ratio [OR] 4.13; 95% confidence interval [CI] 1.55–10.95; p = 0.004). Low SMI was also associated with higher rates of treatment-related toxicity (42.9% vs. 20.0%, p = 0.023). Conclusions: Pre-treatment low SMI is strongly associated with lower pCR rates in patients with HER2-positive and TNBC undergoing neoadjuvant therapy. These findings underscore the importance of early identification and management of radiologically defined sarcopenia to optimize treatment response and improve clinical outcomes.

Objective: This study aimed to evaluate the prognostic significance of positron emission tomography/computed tomography (PET/CT)-derived sarcopenia in patients with hormone receptor-positive, HER2-negative metastatic breast cancer treated with cyclin-dependent kinase 4/6 (CDK4/6) inhibitors. Methods: This retrospective single-center study included 77 patients treated between January 2018 and March 2025. Sarcopenia was assessed using skeletal muscle index (SMI) at the L3 level on fluorodeoxyglucose (FDG) PET/CT. Patients were classified as sarcopenic or non-sarcopenic. Clinical, nutritional parameters including body mass index (BMI) and prognostic nutritional index (PNI), and inflammatory parameters including pan-immune inflammation value (PIV) were analyzed. The primary endpoint was progression-free survival (PFS). Results: Sarcopenia was present in 35.1% of patients. After a median follow-up of 38 months, sarcopenic patients had significantly shorter PFS compared with non-sarcopenic patients (18 vs. 38 months; HR: 2.37, 95% CI 1.12–4.99, p = 0.02, multivariable analysis). In multivariable analysis, sarcopenia, recurrent disease, brain metastasis, and liver metastasis were independent predictors of PFS. No significant association was observed between sarcopenia and overall survival. BMI, PNI, and PIV were not associated with survival outcomes. Toxicity profiles were comparable between groups. Conclusions: PET/CT-derived sarcopenia may be a prognostic factor for PFS in patients receiving CDK4/6 inhibitors, whereas conventional nutritional and inflammatory markers are not. These findings support the clinical utility of imaging-based body composition assessment. Prospective studies incorporating functional measures of sarcopenia are warranted.

Objective: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related death. Panimmune-inflammation value (PIV), a novel biomarker that reflects systemic inflammation and immune status, has been evaluated for prognostic efficacy in various cancer types. This study aimed to investigate theefficacy of PIV on survival outcomes in patients diagnosed with advanced NSCLC who were treated withnivolumab.Methods: The single-center, retrospective, and observational study included patients with metastatic NSCLCwho received nivolumab treatment. The receiver operating characteristic (ROC) curve analysis was performed to find the optimal PIV cutoff value for predicting outcomes, and patients were divided into 2groups: low-PIV and high-PIV.Results: The median age was 63 years. The patient cohort comprised 68 male and 20 female patients.Adenocarcinoma histology was identified in the majority of patients (56.8%). Nivolumab was administeredto 74% of patients as a second line of treatment and to 26% in the third line or later. In ROC analysis, theideal cutoff value for PIV was established at 652 (AUC: 0.691, 95% CI: 0.568-0.814, P = .013). No statistically significant differences were observed in the demographic and clinicopathological features of patientsbetween the low- and high-PIV groups. High PIV was independently associated with shorter progressionfree survival (HR: 0.47, 95% CI: 0.29-0.76; P = .002) and overall survival (HR: 0.54, 95% CI: 0.32-0.92;P = .023), independent of other factors affecting outcomes.Conclusion: The findings of the study indicate that PIV value may serve as a significant prognostic biomarkerfor predicting survival in metastatic NSCLC patients undergoing treatment with nivolumab.Cite this article as: Guliyev M, Alan Ö, Fidan MC, et al. Evaluating the prognostic role of pan-immune-inflammation value inpatients with advanced non-small cell lung cancer treated with nivolumab. Cerrahpaşa Med J. 2025, 49, 0038, doi:10.5152/cjm.2025.25038.