Unresectable hepatocellular carcinoma at dawn of immunotherapy era: real-world data from the French prospective CHIEF cohort.

BACKGROUND AND OBJECTIVES: Hepatocellular carcinoma epidemiological data are limited in France. The Epidemio Liver Immunotherapy Tecentriq outcome research (ELITor) retrospective study, based on real-world data from the Carcinome HépatocellulaIrE en France (CHIEF) French cohort of hepatocellular carcinoma patients, aimed to get insight into the treatment patterns, the sociodemographic, clinical, biological, and etiological characteristics, and the quality of life of patients with unresectable hepatocellular carcinoma. METHODS AND RESULTS: Between 1 September 2019 and 4 December 2020, 367 patients from the CHIEF cohort received at least one locoregional (52.8%) chemoembolization or radioembolization or systemic treatment (88.3%) and were selected for ELITor. Most patients had a Barcelona Clinic Liver Cancer (BCLC) C (93.2%) hepatocellular carcinoma stage and were affected by cirrhosis (67.7%). Alcohol was confirmed as the main etiology both as a single etiology (29.1%) and in association with other risk factors (26.9%), mainly metabolic disorders (16.2%).Tyrosine-kinase inhibitors, mainly sorafenib, were the most administered systemic treatments in first line. Patients who received at least one combination of atezolizumab and bevacizumab during the study period ( N  = 53) had a better performance status and less portal hypertension frequency than the overall population and more hepatitis B virus infection and fewer metabolic disorders as single etiology. Overall, the global health score before treatment (62.3 ±â€…21.9) was in line with that of reference cancer patients and worsened in 51.9% of the cases after first-line palliative-intent treatment. CONCLUSION: This study provided real-life data on advanced hepatocellular carcinoma characteristics and treatment patterns and described the first patients to receive the atezolizumab-bevacizumab combination before it became the new standard of care for advanced hepatocellular carcinoma.

Innovative Approach for a Typology of Treatment Sequences in Early Stage HER2 Positive Breast Cancer Patients Treated With Trastuzumab in the French National Hospital Database.

Background: Our objective was to describe the hospital-based systemic treatment sequences in early stage HER2+ breast cancer patients treated with trastuzumab in France in 2016. Methods: This retrospective observational study was based on the national hospital discharge database (PMSI). Patients hospitalized for breast cancer in 2016 and administration of trastuzumab between 6 months prior and 1 year after surgery were included. The following treatments were identified: (1) trastuzumab ± chemotherapy; (2) chemotherapy alone; (3) q3w trastuzumab weekly chemotherapy. Hospital admissions for cardiac events before and after the surgery were investigated. An unsupervised machine learning technic called TAK (Time-sequence Analysis through K-clustering) was used to identify and visualize typical systemic treatment sequences. Results: Overall, 3531 patients were included: 2619 adjuvant cohort patients (74.2%) and 912 neoadjuvant cohort patients (25.8%). The mean age was 56.4 years (±12.3), 99.7% patients were female. Treatment initiation occurred within 6 weeks of the surgery in 58% and 92% of patients, and trastuzumab treatment lasted 12 months (±1 month) in 75% and 66% of patients in the adjuvant and neoadjuvant cohorts, respectively. Nevertheless, 12% and 22% of patients were treated with trastuzumab for <11 months in the adjuvant and neoadjuvant cohorts, respectively. There was not one standard sequence of treatments per cohort, but 4 and 3 typical treatment sequences in the adjuvant and the neoadjuvant cohorts, respectively, plus 2 treatment sequences with an early treatment withdrawal. The frequency of patients with ⩾1 hospital stay with a cardiac event was higher among patients with an early treatment withdrawal. Conclusions: The treatment sequences of most patients were in line with the recommendations in force. The machine learning approach provided a telling visual display of the results, thereby allowing healthcare professionals, health authorities, patients, and care givers to see the whole picture of the hospital-administered drug strategies.