Thirty-day mortality in hospitalised patients with lung cancer: incidence and predictors.

OBJECTIVES: Patients with lung cancer experience high rates of hospitalisation, mainly due to the high risk of complications that emerge during the natural history of the disease. We designed a retrospective, single-centre, observational study aimed at defining the clinical predictors of 30-day mortality in hospitalised patients with lung cancer. METHODS: Clinical records from the first admission of patients with lung cancer to the oncology ward of the University Hospital of Parma from 1 January 2017 to 1 January 2022 were collected. RESULTS: 251 consecutive patients were enrolled at the time of data cut-off. In the univariate analysis, baseline clinical predictors of 30-day mortality were Eastern Cooperative Oncology Group performance status (ECOG PS) (≥2 vs 0-1: 27.5% vs 14.8%, p=0.028), high Blaylock Risk Assessment Screening Score (BRASS) (high vs intermediate-low: 34.3% vs 11.9%, p<0.001), presence of pain (yes vs no: 24.4% vs 11.7%, p=0.009), number of metastatic sites (≥3 vs <3: 26.5% vs 13.4%, p=0.017) and presence of bone metastases (yes vs no: 29.0% vs 10.8%, p=0.001). In the multivariate analysis, high BRASS remained significantly associated with increased 30-day mortality (high vs intermediate-low; OR 2.87, 95% CI 1.21 to 6.78, p=0.016). CONCLUSION: Our results suggest that baseline poor ECOG PS, high BRASS, presence of pain, high tumour burden and presence of bone metastases could be used as clinical predictors of 30-day mortality in hospitalised patients with lung cancer. In particular, the BRASS scale should be used as a simple tool to predict 30-day mortality in hospitalised patients with lung cancer.

Focus on Therapeutic Options for Surgically Resectable Pancreatic Adenocarcinoma Based on Novel Biomarkers.

Pancreatic ductal adenocarcinoma remains associated with a poor prognosis, even when diagnosed at an early stage. Consequently, it is imperative to carefully consider the available therapeutic options and tailor them based on clinically relevant biomarkers. In our comprehensive review, we specifically concentrated on the identification of novel predictive and prognostic markers that have the potential to be integrated into multiparametric scoring systems. These scoring systems aim to accurately predict the efficacy of neoadjuvant chemotherapy in surgically resectable pancreatic cancer cases. By identifying robust predictive markers, we can enhance our ability to select patients who are most likely to benefit from neoadjuvant chemotherapy. Furthermore, the identification of prognostic markers can provide valuable insights into the overall disease trajectory and inform treatment decisions. The development of multiparametric scoring systems that incorporate these markers holds great promise for optimizing the selection of patients for neoadjuvant chemotherapy, leading to improved outcomes in resectable pancreatic neoplasia. Continued research efforts are needed to validate and refine these markers and scoring systems, ultimately advancing the field of personalized medicine in pancreatic adenocarcinoma management.