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.

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.

Objectives: Hemophagocytic lymphohistiocytosis (HLH) is a rare but life-threatening hyperinflammatory syndrome increasingly reported with immune checkpoint inhibitors (ICIs). However, comparative real-world data across different ICI classes and treatment strategies are limited. This study aimed to characterize HLH reporting patterns associated with ICIs and to compare disproportionality signals among PD-1 inhibitors, PD-L1 inhibitors, and combination regimens using the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: A retrospective pharmacovigilance analysis was performed using FAERS reports submitted between 2013 and 2025. HLH-related cases were identified using core Medical Dictionary for Regulatory Activities (MedDRA) Preferred Terms. Reporting odds ratios (RORs) with 95% confidence intervals (Cis) were calculated to assess disproportionality across ICI treatment strategies, with ICI monotherapy as the reference. Restricted analyses compared PD-1 inhibitors, PD-L1 inhibitors, and ICI plus CTLA-4 inhibitor therapy. Results: A total of 733 HLH-related reports associated with ICIs were identified. The median age was 65 years (range 1–92), and 54.9% of patients were male. Lung cancer (34.4%) and melanoma (16.0%) were the most frequently reported malignancies. ICI monotherapy accounted for 34.7% of cases, while combination regimens included ICI plus chemotherapy (31.6%), ICI plus targeted therapy (17.8%), and ICI plus CTLA-4 inhibitors (15.9%). All cases were classified as serious adverse events; hospitalization occurred in 69.2% and death in 25.1%. Compared with monotherapy, combination regimens showed higher reporting odds of HLH, with the strongest signal for ICI plus targeted therapy (ROR 2.17, 95% CI 1.72–2.73). PD-1 inhibitors demonstrated higher reporting odds than PD-L1 inhibitors (ROR 1.86, 95% CI 1.41–2.46). Conclusions: This large real-world pharmacovigilance analysis demonstrates differential HLH reporting patterns across ICI classes and treatment strategies. Higher reporting odds with combination regimens and PD-1 inhibitors highlight the need for heightened clinical vigilance, particularly in combination treatment settings.

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.

Background: Trastuzumab deruxtecan (T-DXd) is an effective HER2-directed antibody–drug conjugate used across multiple solid tumors. Interstitial lung disease (ILD) and pneumonitis are well-recognized as clinically significant toxicities associated with T-DXd. However, most real-world studies have focused on signal detection rather than the clinical context in which ILD is reported. The patterns by which ILD co-occurs with other respiratory adverse events in routine clinical practice remain poorly characterized. Methods: We analyzed adverse event reports submitted to the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) between 2015 and 2025 in which T-DXd was listed as a suspect drug. ILD, pneumonitis, and respiratory adverse events were identified using MedDRA Preferred Terms. A binary case–event matrix was constructed, and hierarchical clustering was used to explore patterns of respiratory adverse event co-reporting. Subgroup analyses were conducted for breast, gastric/gastroesophageal junction (GEJ), and lung cancer. Cluster stability was assessed using bootstrap resampling. Results: A total of 759 ILD cases and 289 pneumonitis cases associated with T-DXd were identified. In breast cancer reports, ILD consistently clustered with dyspnea and cough, forming a concentrated respiratory co-reporting phenotype. In gastric/GEJ cancer reports, ILD showed strong co-reporting with pneumonia, suggesting overlap between drug-related lung injury and infectious respiratory presentations. Lung cancer reports demonstrated more heterogeneous respiratory co-reporting patterns, with less consistent clustering of ILD with specific symptoms. Network analysis identified ILD as a central node within the respiratory adverse event network. Across all tumor types, respiratory clusters were reproducible in bootstrap analyses, indicating stable and non-random co-reporting structures. Conclusions: ILD associated with T-DXd is reported alongside distinct respiratory adverse event patterns that differ across tumor types. Examining these co-reported respiratory events may help clinicians better interpret ILD reports in real-world practice, particularly in the setting of overlapping or non-specific pulmonary symptoms.

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.