Objectives: To determine whether routinary walking activity and the derived neutrophil-to-lymphocyte ratio are associated with outcomes in patients with recurrent and/or metastatic squamous cell carcinoma of head and neck. Methods: This multicenter retrospective cohort study included 64 patients diagnosed with recurrent and/or metastatic squamous cell carcinoma of head and neck and treated with immunotherapy (Programmed Death-1 and Programmed Death-ligand-1 proteins inhibitors) at two tertiary centers. We compared a group that performed uninterrupted physical activity for 1 h per day and controls who performed no activity. The derived neutrophil-to-lymphocyte ratio was calculated as follows: [neutrophils / (leukocytes – neutrophils)]. Progression-free survival and overall survival were evaluated. Results: We included 28 (44%) and 36 (56%) patients in the activity and non-activity groups, respectively. Patient characteristics, treatment details, and tumor Programmed Death-ligand-1 expression were not associated with either progression-free survival or overall survival. Physical activity was an independent beneficial factor for progression-free survival (p < 0.001) and overall survival (p < 0.001). By contrast, a derived neutrophil-to-lymphocyte ratio <3.5 was an independent beneficial factor for overall survival (p = 0.013), but not for progression-free survival (p = 0.328). Conclusions: Walking one hour per day and having a high proportion of lymphocytes to neutrophiles (expressed as a low derived neutrophil-to-lymphocyte ratio) independently predict a better prognosis in patients with recurrent and/or metastatic squamous cell carcinoma of head and neck treated with immunotherapy. Level of evidence: III.

The use of first-line single agent immunotherapy in patients with advanced NSCLC and ECOG PS ≥ 2 remains controversial, as this frail population has been largely excluded from pivotal clinical trials. Real-world evidence suggests that although median survival is poor, a subset of these patients may achieve long-term benefit. We analyzed data from the Pembro-Real 5Y registry, a global real-world dataset with > 5 years follow-up. The cohort included patients with advanced NSCLC, PD-L1 TPS ≥ 50 %, treated with first line pembrolizumab outside of clinical trials. Univariable analyses were conducted to identify descriptive characteristics associated with survival. To address the complexity of long-term outcome prediction, we integrated Elastic Net regression and a transformer-based AI model (NAIM). The Elastic Net model was employed to mitigate collinearity and select relevant prognostic factors, while NAIM was used to explore non-linear, time-dependent interactions between variables. Endpoints included overall survival (OS) and 5-year survival rates. Out of 1050 patients, 161 patients with ECOG PS ≥ 2 were included, showing a median OS of 5.4 months (95 % CI: 3.8-7.8), and a 5-year survival rate of 13.0 % (95 % CI: 8.1-19.9). Univariable analysis indicated that no single baseline variable was strongly predictive of 5-year survival, except for TMB, KRAS, and BRAF status, which were significantly limited by missingness. Elastic Net identified only two significant predictors of 5-year survival: high TMB (with unstable confidence intervals) and KRAS mutation. NAIM provided a dynamic perspective, confirming that bone metastases and baseline corticosteroid use were strong predictors of early mortality, whereas BMI increase and systemic health markers/host factors (e.g., hypertension and dyslipidemia) gained importance in long-term survivors. However, NAIM exhibited a notable performance drop from training to validation suggesting overfitting and the challenge of modeling long-term outcomes using baseline static variables. Despite the overall poor prognosis, a subset of patients with ECOG PS ≥ 2 achieves long-term survival with pembrolizumab monotherapy, indicating that performance status alone should not preclude treatment in all cases. Our analysis highlights the limitations of traditional statistical approaches and AI-driven models in predicting long-term benefit in this heterogeneous population. Future efforts should focus on refining hybrid modeling strategies and incorporating prospective validation to better identify those who may benefit from immunotherapy beyond short-term expectations.

Soluble immune checkpoints (sICs) have emerged as potential biomarkers in various cancers. However, their role in extensive-stage small cell lung cancer (ES-SCLC), an aggressive tumor type with limited therapeutic options and poor prognosis, remains poorly characterized. We analyzed 14 circulating sICs, leukocyte–platelet (PLT) complexes, and PD-L1 surface expression in ES-SCLC patients treated with chemoimmunotherapy (n = 41) prior to treatment and healthy donors (HD, n = 10). We assessed their associations with clinical and demographic factors and performed survival analyses using Kaplan–Meier and log-rank tests. Levels of soluble (s) PD-L1, PD-L2, BTLA, HVEM, TIM-3, and CD27 were higher in plasma from ES-SCLC patients compared to those from HD (p < 0.05). Patients with liver metastases exhibited higher sIC levels, and a multivariate model demonstrated discriminative power. Network analyses revealed distinct patterns of immune dysregulation between ES-SCLC and HD. We observed correlations among sICs and leukocyte–PLT complexes and leukocyte PD-L1 expression, indicating links between systemic immune status and tumor–immune interactions. Furthermore, increased concentrations of sTIM-3, sCD27, sHVEM and sPD-L1 were associated with a poor prognosis. Overall, sICs reflect relevant clinical, prognostic, and immunological features in ES-SCLC. Their plasma measurement could aid in non-invasive patient stratification regarding liver metastases and survival risk.

Introduction: Despite improved efficacy with first-line immune checkpoint inhibitors plus platinum-based chemotherapy for extensive-stage small cell lung cancer (ES-SCLC), long-term survival remains limited. There is currently no available predictive biomarker to identify which patients would benefit most from this treatment. We hypothesized that pre-treatment PD-L1 expression on circulating immune cells might predict survival outcomes and toxicity. Material and methods: This prospective, multi-center observational study included patients with untreated ES-SCLC treated with first-line durvalumab plus platinum-based chemotherapy. The percentages of circulating PD-L1 ⁺ immune cells at baseline were analysed by flow cytometry to assess their association with survival outcomes and the development of immune-related adverse events (irAEs). Results: Among 41 patients with ES-SCLC, 65.9% were male, 73.2% had an ECOG-PS 1, 9.8% had central nervous system (CNS) metastases and 31.7% had liver metastases. Sixteen patients (39%) experienced irAEs. Median PFS was longer in patients with high percentages of circulating PD-L1 ⁺ monocytes compared to those with low percentages: 8.97 months (95% CI NR to NR) vs. 5.97 months (95% CI 4.65 to 7.28), p = 0.007. There was a trend toward longer median OS in patients with ES-SCLC and high percentages of circulating PD-L1 ⁺ monocytes versus low percentages: NR (95% CI NR-NR) vs. 9.13 months (95% CI 6.34 to 11.92), p = 0.092. Patients with higher circulating PD-L1 ⁺ neutrophils correlated with the development of irAES ( p = 0.007). Conclusions: Our results showed a statistically significant longer PFS in patients with ES-SCLC and high percentages of circulating PD-L1 ⁺ monocytes. This suggests PD-L1 expression on monocytes might be established as a predictive biomarker for patients with ES-SCLC treated with upfront chemo-immunotherapy. Trial registration: NCT04712903 Trial. Last registered 1 December 2025, https://www.clinicaltrials.gov/study/NCT04712903 .