Impact of prone position on dead-space fraction in COVID-19 related acute respiratory distress syndrome.

INTRODUCTION: COVID-19 Related Acute Respiratory Syndrome (C-ARDS) is characterized by a mismatch between respiratory mechanics and hypoxemia, suggesting increased dead-space fraction (DSF). Prone position is a cornerstone treatment of ARDS under invasive mechanical ventilation reducing mortality. We sought to investigate the impact of prone position on DSF in C-ARDS in a cohort of patients receiving invasive mechanical ventilation. METHODS: we retrospectively analysed data from 85 invasively mechanically ventilated patients with C-ARDS in supine and in prone positions, hospitalized in Intensive Care Unit (Reims University Hospital), between November, 1st 2020 and November, 1st 2022. DSF was estimated via 3 formulas usable at patients' bedside, based on partial pressure of carbon dioxide (PaCO2) and end-tidal carbon dioxide (EtCO2). RESULTS: there was no difference of DSF between supine and prone position, using the 3 formulas. According to Enghoff, Frankenfield and Gattinoni equations, DSF in supine vs. prone position was in median respectively [IQR]: 0.29 [0.13-0.45] vs. 0.31 [0.19-0.51] (p = 0.37), 0.5 [0.48-0.52] vs. 0.51 [0.49-0.53] (p = 0.43), and 0.71 [0.55-0.87] vs. 0.69 [0.57-0.81], (p = 0.32). CONCLUSION: prone position did not change DSF in C-ARDS.

High serum LDH and liver metastases are the dominant predictors of primary cancer resistance to anti-PD(L)1 immunotherapy.

AIM: Anti-PD-(L)1 immunotherapies improve survival in multiple cancers but remain ineffective for most patients. We applied machine-learning algorithms and multivariate analyses on baseline medical data to estimate their relative impact on overall survival (OS) upon anti-PD-(L)1 monotherapies. METHOD: This prognostic/predictive study retrospectively analysed 33 baseline routine medical variables derived from computed tomography (CT) images, clinical and biological meta-data. 695 patients with a diagnosis of advanced cancer were treated in prospective clinical trials in a single tertiary cancer centre in 3 cohorts including systemic anti-PD-(L)1 (251, 235 patients) versus other systemic therapies (209 patients). A random forest model combined variables to identify the combination (signature) which best estimated OS in patients treated with immunotherapy. The performance for estimating OS [95%CI] was measured using Kaplan-Meier Analysis and Log-Rank test. RESULTS: Elevated serum lactate dehydrogenase (LDHhi) and presence of liver metastases (LM+) were dominant and independent predictors of short OS in independent cohorts of melanoma and non-melanoma solid tumours. Overall, LDHhiLM+ patients treated with anti-PD-(L)1 monotherapy had a poorer outcome (median OS: 3.1[2.4-7.8] months]) compared to LDHlowLM-patients (median OS: 15.3[8.9-NA] months; P < 0.0001). The OS of LDHlowLM-patients treated with immunotherapy was 28.8[17.9-NA] months (vs 13.1[10.8-18.5], P = 0.02) in the overall population and 30.3[19.93-NA] months (vs 14.1[8.69-NA], P = 0.0013) in patients with melanoma. CONCLUSION: LDHhiLM+ status identifies patients who shall not benefit from anti-PD-(L)1 monotherapy. It could be used in clinical trials to stratify patients and eventually address this specific medical need.

Tumor infiltrating lymphocyte stratification of prognostic staging of early-stage triple negative breast cancer.

The importance of integrating biomarkers into the TNM staging has been emphasized in the 8th Edition of the American Joint Committee on Cancer (AJCC) Staging system. In a pooled analysis of 2148 TNBC-patients in the adjuvant setting, TILs are found to strongly up and downstage traditional pathological-staging in the Pathological and Clinical Prognostic Stage Groups from the AJJC 8th edition Cancer Staging System. This suggest that clinical and research studies on TNBC should take TILs into account in addition to stage, as for example patients with stage II TNBC and high TILs have a better outcome than patients with stage I and low TILs.

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer.

Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.