Limited evidence is available concerning the selection criteria and the outcomes of platinum unfit newly diagnosed advanced NSCLC patients receiving single-agent chemotherapy. We retrospectively collected data on consecutive, stage IIIB-IV, EGFR/ALK negative and PD-L1 < 50% NSCLC patients treated with first-line single agent chemotherapy. Baseline characteristics, outcome measures and toxicities were recorded, as well as criteria according to which treatment selection was made and what percentage of patients did not receive a first-line platinum-based chemotherapy. Two-hundred and twenty-one patients were included. Median age was 79 (range 56–92) years, M/F 165(74.6%)/56(25.4%), ECOG performance status (PS) 0/1/ ≥ 2 23(10.9%)/94(42.5%)/103(46.6%), with a median of two serious comorbidities. A median of 25% (range 10%-30%) of newly diagnosed NSCLC did not receive a first-line platinum combination. Clinical criteria according to which decision was made were older age (76.5%), comorbidities (72%), poor PS (55.2%) and familiar or social issues (10%). Single-agent treatment consisted of oral metronomic vinorelbine (MetV 78.6%), gemcitabine (Gem 10%), oral standard vinorelbine (Vin 8.2%) and other (O 3.2%). Median progression-free survival (PFS) and overall survival (OS) of single agent treatments ranged from 4.5 to 5 months and from 9 to 10.5 months, respectively. All grade toxicities did not differ among single agents, while grade 3–4 toxicities were less frequent with MetV. Up to 30% of newly diagnosed advanced EGFR/ALK negative and PD-L1 < 50% NSCLC patients do not receive a first-line platinum doublet. Main clinical selection criteria were older age (>70 years), comorbidities and poor PS. An oral treatment was frequently proposed with MetV being the most frequent choice according to its safety profile.

To investigate the role of dosiomics features extracted from physical dose (D_PHYS), RBE-weighted dose (D_RBE) and dose-averaged Linear Energy Transfer (LET_d), to predict the risk of local recurrence (LR) in skull base chordoma (SBC) treated with Carbon Ion Radiotherapy (CIRT). Thus, define and evaluate dosiomics-driven tumor control probability (TCP) models. 54 SBC patients were retrospectively selected for this study. A regularized Cox proportional hazard model (r-Cox) and Survival Support Vector Machine (s-SVM) were tuned within a repeated Cross Validation (CV) and patients were stratified in low/high risk of LR. Models' performance was evaluated through Harrell's concordance statistic (C-index), and survival was represented through Kaplan-Meier (KM) curves. A multivariable logistic regression was fit to the selected feature sets to generate a dosiomics-driven TCP model for each map. These were compared to a reference model built with clinical parameters in terms of f-score and accuracy. The LETd maps reached a test C-index of 0.750 and 0.786 with r-Cox and s-SVM, and significantly separated KM curves. D_PHYS maps and clinical parameters showed promising CV outcomes with C-index above 0.8, despite a poorer performance on the test set and patients stratification. The LETd-based TCP showed a significatively higher f-score (0.67[0.52-0.70], median[IQR]) compared to the clinical model (0.4[0.32-0.63], p < 0.025), while D_PHYS achieved a significatively higher accuracy (D_PHYS: 0.73[0.65-0.79], Clinical: 0.6 [0.52-0.72]). This analysis supports the role of LETd as relevant source of prognostic factors for LR in SBC treated with CIRT. This is reflected in the TCP modeling, where LETd and D_PHYS showed an improved performance with respect to clinical models.

Background: There are currently few data about the safety and effectiveness of chemotherapy for patients with metastatic non-small-cell lung cancer (NSCLC) who have progressed from prior immunotherapy. Methods: Data from patients with consecutive stage IIIB–IV, ECOG performance status (PS) 0–2, non-small-cell lung cancer (NSCLC) treated with combination or single-agent chemotherapy following progression on an earlier immunotherapy regimen were retrospectively gathered. Recorded were baseline attributes, outcome metrics, and toxicities. The neutrophil/lymphocyte (N/L) ratio’s predictive usefulness was examined through an exploratory analysis. Results: The analysis comprised one hundred subjects. The adeno/squamous carcinoma ratio was 77%/23%, the M/F ratio was 66%/34%, the ECOG PS was 0/1/≥2 47%/51%/2%, and the median PD-L1 expression was 50% (range 0–100). The median age was 67 (range 39–81) years. Prior immunotherapy included a single-agent treatment in 83% of cases, with pembrolizumab use being prevalent, and a median N/L ratio of four prior to chemotherapy. The overall median time-to-progression on previous immunotherapy was 6 months. After immunotherapy, just 33% of subjects underwent chemotherapy. A median of 4 (range 1–16) cycles of chemotherapy were administered; platinum doublets (primarily carboplatin) were delivered in only 31% of cases, vinorelbine accounted for 25%, taxanes for 25%, and gemcitabine for 8%. The median clinical benefit was 55%, while the overall response rate was 21%. The median overall survival was 5 months (range 1–22) and the median time to progression was 4 months (range 1–17). Subgroups with low and high N/L ratios were compared, but there was no discernible difference in survival. Conclusions: After immunotherapy, a small percentage of patients with advanced NSCLC had chemotherapy. Following immunotherapy advancement, chemotherapy demonstrated a moderate level of therapeutic effectiveness; no adverse concerns were noted. The effectiveness of chemotherapy following immunotherapy was not predicted by the baseline N/L ratio.

Background/Objectives: In skull-base proton therapy, T2-weighted brain magnetic resonance (MR) imaging may be acquired with or without fat saturation (FS). The present study investigated the impact of this protocol variation on radiomics feature stability and brain radionecrosis (BRN) prediction. Methods: Paired T2-weighted FS and non-FS follow-up MR scans of proton-treated skull-base chordoma patients (n = 52) were used to assess feature stability. For BRN prediction (CTCAEv5 grade ≥ 1), baseline planning scans of chordoma and chondrosarcoma patients (n = 80) with mixed FS protocols were used. Following automated brain tissue segmentation, 1911 radiomics features were extracted from cerebrospinal fluid, gray, and/or white matter using PyRadiomics (v3.1.0). Feature stability was quantified using Lin’s concordance correlation coefficient (CCC). Several MR image- and feature-level processing configurations were explored, and the stability of combined gray and white matter features served as the reference for selecting the optimal configuration. Features were stratified based on CCC thresholds and were subjected to univariable feature selection using a Mann–Whitney U-test. Logistic regression was used for predictive modeling and its performance was measured using micro-averaged AUC within a repeated stratified cross-validation framework. Results: Radiomics features were highly sensitive to FS variations (median CCC range: 0.21–0.58). Combat harmonization without image-level processing was selected as the optimal configuration, under which 30% of features achieved CCC ≥ 0.70, and 10.7% demonstrated a CCC ≥ 0.85. Restricting modeling to a highly stable subset eliminated nearly 90% of the baseline features while significantly improving predictive performance (ΔAUC = 0.05, p < 0.001). Conclusions: A subset of radiomics features robust to FS variations was identified. Use of these stable features may mitigate the impact of protocol-induced variability in mixed-FS T2-weighted MR data while simultaneously improving BRN prediction performance. These findings are preliminary and should be interpreted cautiously, given the pilot nature of the study.