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In the present study we investigated the prognostic value of Circulating Tumour Cells (CTC) and their utility for therapy monitoring in non-small cell lung cancer (NSCLC). A total of 43 patients newly diagnosed with NSCLC were prospectively enrolled. Blood samples were obtained before the 1st, 2nd and 5th cycles of chemotherapy and analyzed using CellSearch technology. Both CTC and CTC-related objects (not morphological standard or broken epithelial cells) were counted. At baseline 18 (41.9%) patients were positive for intact CTC count and 10 (23.2%) of them had ⩾5 CTC, while CK positive events were found in 79.1% of patients. The group of patients with CTC ⩾5 at baseline presented worse PFS and OS than those with <5 CTC (p = 0.034 and p = 0.008, respectively). Additionally, high levels of total CK positive events were associated with poor prognosis in the group of patients with <5 CTC. Regarding therapy monitoring, patients presenting increased levels of CTC during the treatment demonstrated lower OS and PFS rates. All these data supported the value of CTC as a prognostic biomarker and as surrogate indicator of chemotherapy effectiveness in advanced NSCLC patients, with the additional value of analyzing other "objects" such as apoptotic CTC or CK fragments to guide the clinical management of these patients. [ABSTRACT FROM AUTHOR]

Patient selection in phase 1 clinical trials (Ph1t) continues to be a challenge. The aim of this study was to develop a user-friendly prognostic calculator for predicting overall survival (OS) outcomes in patients to be included in Ph1t with immune checkpoint inhibitors (ICIs) or targeted agents (TAs) based on clinical parameters assessed at baseline. Using a training cohort with consecutive patients from the VHIO phase 1 unit, we constructed a prognostic model to predict median OS (mOS) as a primary endpoint and 3-month (3m) OS rate as a secondary endpoint. The model was validated in an internal cohort after temporal data splitting and represented as a web application. We recruited 799 patients (training and validation sets, 558 and 241, respectively). Median follow-up was 21.2 months (m), mOS was 10.2 m (95% CI, 9.3–12.7) for ICIs cohort and 7.7 m (95% CI, 6.6–8.6) for TAs cohort. In the multivariable analysis, six prognostic variables were independently associated with OS – ECOG, number of metastatic sites, presence of liver metastases, derived neutrophils/(leukocytes minus neutrophils) ratio [dNLR], albumin and lactate dehydrogenase (LDH) levels. The phase 1 prognostic online (PIPO) calculator showed adequate discrimination and calibration performance for OS, with C-statistics of 0.71 (95% CI 0.64–0.78) in the validation set. The overall accuracy of the model for 3m OS prediction was 87.2% (95% CI 85%–90%). PIPO is a user-friendly objective and interactive tool to calculate specific survival probabilities for each patient before enrolment in a Ph1t. The tool is available at https://pipo.vhio.net/. • PIPO tool calculates survival probabilities before enrolment in a phase 1 trial. • This new model is independently useful for both ICIs and TAs trials. • PIPO tool uses all available information with no dichotomisation of the variables. • PIPO tool provides a patient-specific risk prediction for any given time point. [ABSTRACT FROM AUTHOR]