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PURPOSE: Pemetrexed has shown efficacy as monotherapy or in combination with platinum salts in the treatment of non-small cell lung cancer and mesothelioma. However, severe hematological toxicities induced by pemetrexed-based chemotherapy have been observed. Some studies have suggested that drug interactions may be associated with pemetrexed toxicity. The objective of this study was to determine predictive factors, including drug interactions, associated with pemetrexed toxicity. METHODS: This retrospective open monocentric study included patients consecutively treated with pemetrexed after a multidisciplinary risk assessment. Patients who experienced toxicity of grade 3 or 4 according to the Common Terminology Criteria for Adverse Events v5.0, or a grade 2 leading to a change in management, during the first four courses of pemetrexed, were assigned to the early limiting toxicities (ELT) group. Univariate and multivariable logistic regression models were used to test the association variables with the occurrence of ELT. RESULTS: Seventy-four patients were included in this study (median age: 67 years, with non-small cell lung cancer adenocarcinoma (88%), mesothelioma (7%), or others (5%). Thirty-six patients (49%) were assigned to the ELT group (27 grades 3 and 4; 9 grade 2 with management modification). Three baseline factors were associated with pemetrexed ELT in univariate and multivariate analysis: cystatin clearance (p = 0.0135), albumin level (p = 0.0333), and proton pump inhibitors use (p = 0.035). CONCLUSION: To conclude, ELT induced by pemetrexed-based treatments occur frequently in cancer patients in a real-world setting. A pretherapeutic assessment before pemetrexed initiation should include three major checkpoints: use of proton pump inhibitors, sarcopenia, and denutrition evaluation.

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Background: Nivolumab improved patients' survival in metastatic renal cell carcinoma (mRCC). We aimed to evaluate resting energy expenditure (REE) (i.e., patients' basal metabolism) to predict efficacy. Methods: We conducted a monocentric, observational study of mRCC patients receiving nivolumab between October 2015 and May 2020. REE was measured prior to initiating immunotherapy using indirect calorimetry to determine hypo, normo and hypermetabolism. Primary endpoint was 6-month, progression-free survival (PFS), and secondary endpoints were response rate, PFS and overall survival (OS). Results: Of the 51 consecutive patients, 15 (29%) were hypermetabolic, 24 (47%) normometabolic, and 12 (24%) hypometabolic. The 6-month PFS was 15% for hypermetabolic patients and 65% for non-hypermetabolic patients (p < 0.01). In the multivariate analysis, hypermetabolism was the only baseline factor predicting 6-month PFS (OR 9.91, 95%CI [1.62−60.55], p = 0.01). Disease progression was noted as the best response in 73% of hypermetabolic patients and 26% of non-hypermetabolic patients (p = 0.02). Median PFS was 2.8 and 8.7 months (p < 0.01), and median OS was 20.2 and 35.1 months (p = 0.13) in the hypermetabolic and non-hypermetabolic groups, respectively. Conclusions: Our study identifies an association between mRCC patients' energy expenditure and nivolumab efficacy. The measurement of REE by indirect calorimetry in routine practice could help identify patients at risk of nivolumab failure.

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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).

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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.

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The emergence of oral cancer treatment in oncology has shifted patient follow-up from the hospital to the home. This trend has resulted in an increase in phone and e-mail interactions initiated by patients, but also by pharmacists, by liberal nurses, by general practitioners, and an increase in calls to the emergency response services (SAMU) both for real or perceived emergencies. This increased volume of patient and pharmacist communication has caused significant disruption in the daily activity of affected oncology departments and in particular of the secretariats. The procedures for formulating and securing appropriate responses within a short time frame are generally not established, and as a result, there is a risk that decisions made could be inappropriate for the patient's situation, especially in the case of complications.. Tracking responses to phone calls is necessary and answers should be noted in the medical file, including side effects, in particular the serious AEs for a good quality of care. This guideline describes best practices for oncologists who manage "incoming" calls from patients or professionals involved in the care pathway.

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BACKGROUND: Docetaxel is frequently used for the treatment of metastatic prostate cancer patients. Nail toxicity is a commonly described side effect, but no precise recommendation exists concerning its management. We experimented the integration of a podiatrist in routine cancer care. METHODS: Patients having received docetaxel for a metastatic prostate cancer since the arrival of the podiatrist were studied. RESULTS: Fifty-six patients were included, half had docetaxel-induced nail toxicity and 18 were referred to the podiatrist. The integration of the podiatrist in routine care was feasible and allowed characterizing nail toxicity. The main lesions observed were non-coagulated nail hematomas, coagulated nail hematomas and onycholysis. This experience led to propose an integrated care for docetaxel-induced nail toxicity. CONCLUSION: The integration of podiatrist care is feasible in routine cancer care and can help improving the management of docetaxel-induced nail toxicity in metastatic prostate cancer patients.

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PURPOSE: Abiraterone acetate combined with prednisone improves survival in metastatic castration-resistant prostate cancer (mCRPC) patients. This oral anticancer agent may result in drug-drug interactions (DDI). We aimed to evaluate the prevalence of DDI with abiraterone and the possible determinants for the occurrence of these DDI. METHODS: We performed a single centre retrospective review from electronic medical records of mCRPC patients treated with abiraterone from 2011 to 2015. Potential DDI with abiraterone were identified using Micromedex and were categorized by a 4-point scale severity. RESULTS: Seventy-two out of ninety-five mCRPC pts (median age: 77 years [68-82]) had comorbidities. The median number of drugs used per patient was 7 [5-9]. 66 potential DDI with abiraterone were detected in 49 patients (52%): 39 and 61% were classified as major and moderate DDI, respectively. In the univariate analysis, pain (p < 0.0001), hypo-albuminemia (p = 0.032), and higher ECOG performance status (PS) (p = 0.013) were significantly associated with a higher risk of DDI with abiraterone. Pain (p < 0.0001) and PS (p = 0.018) remained significant in the multivariate analysis. CONCLUSIONS: Polypharmacy is an issue among mCRPC patients. In our study, half of the patients have potential DDI with abiraterone. Patients with pain and poor PS are at higher risk of DDI with abiraterone. A medication review by a pharmacist is of crucial importance to prevent DDI with abiraterone.

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