Hélène Pluchart

Impact de la polymédication et des comorbidités chez les patients hospitalisés porteurs d’un cancer bronchopulmonaireLes patients ayant un cancer bronchopulmonaire peuvent avoir des comorbidités préexistantes au diagnostic ou qui apparaissent après réalisation du traitement antitumoral. Ces comorbidités peuvent avoir un impact sur la décision de traitement antitumoral ainsi que sur la survie des patients. De plus, ces comorbidités apparues avant ou après le diagnostic peuvent entrainer de la polymédication. Cette polymédication peut potentiellement engendrer des interactions médicamenteuses avec le traitement antitumoral, et ainsi avoir une conséquence sur la prise en charge du patient.Dans ce travail, nous nous sommes intéressés au lien entre le cancer bronchopulmonaire, les comorbidités, la polymédication, et leurs conséquences sur la réalisation du traitement systémique et sur la survie des patients. Dans une première partie, une revue narrative de la littérature a été faite et propose une synthèse des connaissances actuelles sur le lien entre ces entités, et notamment sur ce qui a déjà été décrit dans le cancer du poumon. Dans la deuxième partie, le protocole de cette étude qui est originale de par son design mais également de par son analyse statistique a été décrit. Par la suite dans une troisième partie, nous nous sommes focalisés sur les comorbidités et le calcul des scores de comorbidités. Une étude de comparaison de scores de comorbidités a été réalisée afin de choisir le score qui prédit le mieux la mortalité dans la cohorte de patients. Enfin, l’impact de la polymédication et des comorbidités sur la réalisation du traitement systémique et sur la survie médiane des patients a été étudié.Mots-clés : Cancer bronchopulmonaire, comorbidités, polymédication, médicament, modèles de survie

Most patients with lung cancer are smokers and are of advanced age. They are therefore at high risk of having age- and lifestyle-related comorbidities. These comorbidities are subject to treatment or even polypharmacy. There is growing evidence of a link between lung cancer, comorbidities and medications. The relationships between these entities are complex. The presence of comorbidities and their treatments influence the time of cancer diagnosis, as well as the diagnostic and treatment strategy. On the other hand, cancer treatment may have an impact on the patient’s comorbidities such as renal failure, pneumonitis or endocrinopathies. This review highlights how some comorbidities may have an impact on lung cancer presentation and may require treatment adjustments. Reciprocal influences between the treatment of comorbidities and anticancer therapy will also be discussed.

Background: The comorbidity burden has a negative impact on lung-cancer survival. Several comorbidity scores have been described and are currently used. The current challenge is to select the comorbidity score that best reflects their impact on survival. Here, we compared seven usable comorbidity scores (Charlson Comorbidity Index, Age adjusted Charlson Comorbidity Index, Charlson Comorbidity Index adapted to lung cancer, National Cancer Institute combined index, National Cancer Institute combined index adapted to lung cancer, Elixhauser score, and Elixhauser adapted to lung cancer) with coded administrative data according to the tenth revision of the International Statistical Classification of Diseases and Related Health Problems to select the best prognostic index for predicting four-month survival. Materials and methods: This cohort included every patient with a diagnosis of lung cancer hospitalized for the first time in the thoracic oncology unit of our institution between 2011 and 2015. The seven scores were calculated and used in a Cox regression method to model their association with four-month survival. Then, parameters to compare the relative goodness-of-fit among different models (Akaike Information Criteria, Bayesian Information Criteria), and discrimination parameters (the C-statistic and Harrell’s c-statistic) were calculated. A sensitivity analysis of these parameters was finally performed using a bootstrap method based on 1,000 samples. Results: In total, 633 patients were included. Male sex, histological type, metastatic status, CCI, CCI-lung, Elixhauser score, and Elixhauser-lung were associated with poorer four-month survival. The Elixhauser score had the lowest AIC and BIC and the highest c-statistic and Harrell’s c-statistic. These results were confirmed in the sensitivity analysis, in which these discrimination parameters for the Elixhauser score were significantly different from the other scores. Conclusions: Based on this cohort, the Elixhauser score is the best prognostic comorbidity score for predicting four-month survival for hospitalized lung cancer patients.

Background: Although polypharmacy has been described among cancer patients, very few studies have focused on those with lung cancer. We aimed to assess whether polypharmacy and comorbidity have an impact on systemic parenteral treatment administration and survival among lung-cancer patients. Methods: In this retrospective monocenter cohort study, we included patients hospitalized in thoracic oncology for the first time between 2011 and 2015. The Elixhauser score was used to assess comorbidity and polypharmacy was estimated with a threshold of at least five prescribed medications. The Fine and Gray competitive risk model was used to estimate the impact of polypharmacy and comorbidity on systemic parenteral treatment administration within the first two months of hospitalization. The effect of comorbidity and polypharmacy on overall survival was evaluated by Cox proportional hazards analysis. Results: In total, 633 patients were included (71% men), with a median age of 66 years. The median Elixhauser score was 6 and median overall survival was four months. Among the patients, 24.3% were considered to be receiving polypharmacy, with a median number of medications of 3, and 49.9% received systemic parenteral treatment within two months after hospitalization. Severe comorbidity (Elixhauser score > 11), but not polypharmacy, was independently associated with a lower rate of systemic parenteral treatment prescription (SdHR = 0.4 [0.3;0.6], p < 0.01) and polypharmacy, but not a high comorbidity score, was independently associated with poorer four-month survival (HR = 1.4 [1.1;1.9], p < 0.01) Conclusions: This first study to evaluate the consequences of comorbidity and polypharmacy on the care of lung-cancer patients shows that a high comorbidity burden can delay systemic parenteral treatment administration, whereas polypharmacy has a negative impact on four-month survival.

We investigate dalbavancin efficiency and tolerance among elderly in Grenoble-Alpes 32 university hospital. Among the 65 patients who received dalbavancin, 51% (33) were considered as old. Patients presented mainly bones and joint infections (52%), surgical site infection 34 (31%), and infective endocarditis (IE) (8%). Clinical cure was confirmed for 79% of old 35 patients at 1, 3, and 6 months. Six adverse events (9%) were reported after 36 dalbavancin’s administration, but each time in combination with other antibiotics. 37 Dalbavancin had a significant effectiveness and safety profile and represents a real 38 therapeutic option in the management of deep and complex infections of elderly patients.

Objectives Lung transplant (LT) recipients require multidisciplinary care because of the complexity of therapeutic management. Pharmacists are able to detect drug-related problems and provide recommendations to physicians through pharmacists’ interventions (PIs). We aimed at assessing the clinical impact of PIs on therapeutic management in LT outpatients. Design Data were collected prospectively from an LT recipients cohort during 7 years. A multidisciplinary committee assessed retrospectively the clinical impact of accepted PIs. Setting French University Hospital. Participants LT outpatients followed from 2009 to 2015. Primary outcome measures Clinical impact of PIs performed by pharmacists using the CLEO tool and the Pareto chart. Results 1449 PIs led to a change in patient therapeutic management and were mainly related to wrong dosage (39.6%) and untreated indication (19.6%). The clinical impact of PIs was ‘avoids fatality’, ‘major’ and ‘moderate’, in 0.1%, 7.0% and 57.9%, respectively. Immunosuppressants, antimycotics for systemic use and antithrombotic agents had the greatest clinical impact according to the Pareto chart. PIs related to drug–drug interactions (10%) mainly had a moderate and major clinical impact (82.3%, pConclusion Clinical pharmacists play a key role for detecting drug-related problems mostly leading to a change in therapeutic management among LT outpatients. Our study provides a new insight to analyse the clinical impact of PIs in order to target PIs which have most value and contribute to patient care through interdisciplinary approach.

One of the post‐transplantation complications is represented by chronic lung allograft dysfunction, which has two main clinical presentations: bronchiolitis obliterans syndrome and restrictive allograft syndrome. The latter being challenging because of poor prognosis and only symptomatic treatment, and characterized by fibrotic process. A 63‐year‐old man was right lung transplanted in 2009 due to idiopathic pulmonary fibrosis. In 2011, bronchiolitis obliterans syndrome was diagnosed evolving to restrictive allograft syndrome in 2016. An off‐label treatment by nintedanib (150 mg twice a day) was introduced. Unfortunately, it was stopped four months later because of digestive intolerance, without any clinical improvement. Contrary to a previous case reported, our patient did not have any benefit of nintedanib. Antifibrotic agents’ effects such as nintedanib on restrictive allograft syndrom should be assessed in further randomized double blind placebo‐controlled studies.