Development and validation of a host-dependent, PDL1-independent, biomarker to predict 6-month progression-free survival in metastatic non-small cell lung cancer (mNSCLC) patients treated with anti-PD1 immune checkpoint inhibitors (ICI) in the CERTIM Cohort: The ELY study.

BACKGROUND: Immune checkpoint inhibitors (ICI) are dramatically active in a minority of non-small cell lung cancer (NSCLC) patients. We studied here the relationship between patients's metabolism and outcome under ICI. METHODS: Metastatic NSCLC patients underwent a nutritional assessment prior to initiating immunotherapy. Resting energy expenditure (REE) was measured (mREE) using ambulatory indirect calorimetry and compared with the theoretical value (tREE) provided by the Harris and Benedict formula. The primary endpoint was 6-month progression-free survival (PFS). Secondary endpoints included objective response rate (ORR) and disease control rate (DCR) based on investigator review per RECIST v1.1. and overall survival (OS). The association of patient's metabolism with 6-month PFS was first explored in a single-center training cohort to estimate the effect size. The relationship between patient's metabolism and 6-month PFS was then tested in an independent non interventional observational prospective cohort (ELY) of 100 patients recruited in two tertiary university centers. FINDINGS: In the entire cohort, the ORR was 14% for the hypermetabolic group (n = 10/74) vs 38% for the normometabolic group (n = 26/68), respectively (estimated difference 25%, 95CI 9-40%, p = 0.001). The DCR was 28% for the hypermetabolic group (n = 21/74) vs 53% for the normometabolic group (n = 36/68), respectively (estimated difference 25%, 95CI 7-42%, p = 0.005). In the validation cohort (100 patients, 2 centers), normometabolic patients (defined as mREE/tREE < 110%) had increased 6-month PFS (57% versus 22%; odds ratio: 4.76; IC95 [1.87 - 12.89]; p<0.001) and improved overall survival (HR 2.20; IC95: 1.41-3.44; p<0.001). The positive and negative predictive values of normometabolism to identify non-progressive patients at 6 months, were 57% and 78% respectively, sensitivity was 72% and specificity was 66%. In multivariate analysis including PD-L1 tumor status, basal metabolism was an independent predictive factor for 6-month PFS. INTERPRETATION: Normometabolism is a new independent parameter to identify mNSCLC patients who will benefit from ICI, with both improved tumor response, 6-month PFS, and survival. FUNDING: This work was supported by Baxter (04012016).

Prevalence of drug-drug interactions in sarcoma patients: key role of the pharmacist integration for toxicity risk management.

BACKGROUND: The risk of drug-drug interactions (DDI) has become a major issue in cancer patients. However, data in sarcoma patients are scarce. We aimed to evaluate the frequency and the factors associated with DDI with antitumor treatments, and to evaluate the impact of a pharmacist evaluation before anticancer treatment. PATIENTS AND METHODS: We performed a retrospective review of consecutive sarcoma patients starting chemotherapy (CT) or Tyrosine kinase inhibitor (TKI). A pharmacist performed medication reconciliation and established an early toxicity risk assessment. Potential DDI with antitumor drugs were identified using Micromedex electronic software. RESULTS: One hundred and twenty-two soft-tissue and 80 bone sarcoma patients (103 males, median age 50 years,) were included before CT (86%) or TKI (14%). The median number of medications was 3; 34 patients (22% of patients with medication reconciliation) reported complementary medicine use. 37 potential DDI classified as major, were identified (12% of the 243 pre-therapeutic assessments). In multivariate analysis, TKI (p < 0.0001), proton pump inhibitor (p = 0.026) and antidepressant (p < 0.001) were identified as risk factors of DDI (p < 0.02). Only marital status (p = 0.003) was associated with complementary medicine use. A pharmacist performed 157 medication reconciliations and made 71 interventions among 59 patients (37%). In multivariate analysis, factors associated with pharmacist intervention were: complementary medicines (p = 0.004), drugs number (p = 0.005) and treatment with TKI (p = 0.0002) CONCLUSIONS: Clinical interventions on DDI are more frequently required among sarcoma patients treated with TKI than CT. Multidisciplinary risk assessment including a medication reconciliation by a pharmacist could be crucial to prevent DDI with TKI.