Michiel Thomeer

Skeletal muscle weakness in patients with sarcoidosis and its relationship with exercise intolerance and reduced health status

Background: Skeletal muscle weakness is assumed to be present in patients with sarcoidosis but has never been reported in a consecutive group of patients. Moreover, its relationship with previously observed exercise intolerance and reduced health status has never been studied in these patients. Methods: Pulmonary function, skeletal and respiratory muscle forces, peak and functional exercise capacity, health status, and the circulating levels of inflammatory and anabolic markers were determined in 25 patients with sarcoidosis who complained of fatigue (15 men) and in 21 healthy subjects (13 men). Results: Patients with sarcoidosis had lower respiratory and skeletal muscle forces, reduced exercise capacity and health status, higher anxiety and depression scores, and higher circulating levels of tumour necrosis factor-α than healthy subjects (all p⩽0.01). Its soluble receptor p75 tended to be higher (p = 0.04). Circulating levels of interleukin (IL)-6, IL-8, insulin-like growth factor I and its binding protein 3 were not significantly different between the two groups. Skeletal muscle weakness was related to exercise intolerance, depression, and reduced health status in patients with sarcoidosis, irrespective of age, sex, body weight and height (p⩽0.05). Quadriceps peak torque was inversely related to fatigue but not to the circulating levels of inflammatory or anabolic markers. The mean daily dose of corticosteroids received in the 6 month period before testing was related to quadriceps peak torque only in patients who received oral corticosteroids. Conclusion: Skeletal muscle weakness occurs in patients with sarcoidosis who complain of fatigue and is associated with reduced health status and exercise intolerance.

Multidisciplinary interobserver agreement in the diagnosis of idiopathic pulmonary fibrosis

The purpose of the present study was to evaluate the accuracy of the diagnosis of idiopathic pulmonary fibrosis (IPF) by respiratory physicians in six European countries, and to calculate the interobserver agreement between high-resolution computed tomography reviewers and histology reviewers in IPF diagnosis. The diagnosis of usual interstitial pneumonia (UIP) was assessed by a local investigator, following the American Thoracic Society/European Respiratory Society consensus statement, and confirmed when a minimum of two out of three expert reviewers from each expert panel agreed with the diagnosis. The level of agreement between readers within each expert panel was calculated by weighted kappa. The diagnosis of UIP was confirmed by the expert panels in 87.2% of cases. A total of 179 thoracic high-resolution computed tomography scans were independently reviewed, and an interobserver agreement of 0.40 was found. Open or thoracoscopic lung biopsy was performed in 97 patients, 82 of whom could be reviewed by the expert committee. The weighted kappa between histology readers was 0.30. It is concluded that, although the level of agreement between the readers within each panel was only fair to moderate, the overall accuracy of a clinical diagnosis of idiopathic pulmonary fibrosis in expert centres is good (87.2%).

Safety and Immunogenicity of MAGE-A3 Cancer Immunotherapeutic with or without Adjuvant Chemotherapy in Patients with Resected Stage IB to III MAGE-A3-Positive Non-Small-Cell Lung Cancer

Introduction: To assess the safety and immunogenicity of MAGE-A3 immunotherapeutic in patients with stage IB–III MAGE-A3-positive non–small-cell lung cancer (NSCLC) who were or were not undergoing standard cisplatin/vinorelbine chemotherapy. Methods: This open, prospective, multicenter, parallel-group phase I study (NCT00455572) enrolled patients with resected (cohorts 1–3) or unresectable (cohort 4) MAGE-A3-positive NSCLC. MAGE-A3 immunotherapeutic (300 &mgr;g recombinant MAGE-A3 formulated with AS15) was administered (eight doses, 3 weeks apart) concurrent with (cohort 1), after (cohort 2), or without (cohort 3) standard-adjuvant chemotherapy, or after standard radiotherapy and/or chemotherapy (cohort 4). Results: Sixty-seven patients received greater than or equal to 1 dose of MAGE-A3 immunotherapeutic. Grade 3/4 adverse events (AEs) were reported for 16 out of 19 (84%), 2 out of 18 (11%), 5 out of 18 (28%), and 1 out of 12 (8%) patients in cohorts 1, 2, 3, and 4, respectively. Many grade 3/4 AEs in cohort 1 (e.g., neutropenia) were typical of chemotherapy. Six patients, including three in cohort 1, reported study treatment–related grade 3/4 AEs (injection-site reactions or musculoskeletal/back pain, which resolved within 5 days). One patient (in cohort 4) died, but this and the other serious adverse events were not study treatment related. MAGE-A3-specific antibody responses to immunotherapy were induced in all patients evaluated in all cohorts. MAGE-A3-specific CD4+ T-cell responses to immunotherapy were detected in 4 out of 11 (36%), 4 out of 15 (27%), 2 out of 8 (25%), and 5 out of 6 (83%) evaluated patients in cohorts 1, 2, 3, and 4, respectively; and CD8+ T-cell responses were only detected in four patients. Conclusion: In resected and unresectable NSCLC patients and irrespective of whether standard chemotherapy was concurrent or not, MAGE-A3 immunotherapeutic is well tolerated and induces MAGE-A3-specific immune responses.

Detection of Lung Cancer through Metabolic Changes Measured in Blood Plasma

Introduction: Low‐dose computed tomography, the currently used tool for lung cancer screening, is characterized by a high rate of false‐positive results. Accumulating evidence has shown that cancer cell metabolism differs from that of normal cells. Therefore, this study aims to evaluate whether the metabolic phenotype of blood plasma allows detection of lung cancer. Methods: The proton nuclear magnetic resonance spectrum of plasma is divided into 110 integration regions, representing the metabolic phenotype. These integration regions reflect the relative metabolite concentrations and were used to train a classification model in discriminating between 233 patients with lung cancer and 226 controls. The validity of the model was examined by classifying an independent cohort of 98 patients with lung cancer and 89 controls. Results: The model makes it possible to correctly classify 78% of patients with lung cancer and 92% of controls, with an area under the curve of 0.88. Important moreover is the fact that the model is convincing, which is demonstrated by validation in the independent cohort with a sensitivity of 71%, a specificity of 81%, and an area under the curve of 0.84. Patients with lung cancer have increased glucose and decreased lactate and phospholipid levels. The limited number of patients in the subgroups and their heterogeneous nature do not (yet) enable differentiation between histological subtypes and tumor stages. Conclusions: Metabolic phenotyping of plasma allows detection of lung cancer, even in an early stage. Increased glucose and decreased lactate levels are pointing to an increased gluconeogenesis and are in accordance with recently published findings. Furthermore, decreased phospholipid levels confirm the enhanced membrane synthesis.

Metabolic phenotyping of human blood plasma: a powerful tool to discriminate between cancer types?

BACKGROUND Accumulating evidence has shown that cancer cell metabolism differs from that of normal cells. However, up to now it is not clear whether different cancer types are characterized by a specific metabolite profile. Therefore, this study aims to evaluate whether the plasma metabolic phenotype allows to discriminate between lung and breast cancer. PATIENTS AND METHODS The proton nuclear magnetic resonance spectrum of plasma is divided into 110 integration regions, representing the metabolic phenotype. These integration regions reflect the relative metabolite concentrations and were used to train a classification model in discriminating between 80 female breast cancer patients and 54 female lung cancer patients, all with an adenocarcinoma. The validity of the model was examined by permutation testing and by classifying an independent validation cohort of 60 female breast cancer patients and 81 male lung cancer patients, all with an adenocarcinoma. RESULTS The model allows to classify 99% of the breast cancer patients and 93% of the lung cancer patients correctly with an area under the curve (AUC) of 0.96 and can be validated in the independent cohort with a sensitivity of 89%, a specificity of 82% and an AUC of 0.94. Decreased levels of sphingomyelin and phosphatidylcholine (phospholipids with choline head group) and phospholipids with short, unsaturated fatty acid chains next to increased levels of phospholipids with long, saturated fatty acid chains seem to indicate that cell membranes of lung tumors are more rigid and less sensitive to lipid peroxidation. The other discriminating metabolites are pointing to a more pronounced response of the body to the Warburg effect for lung cancer. CONCLUSION Metabolic phenotyping of plasma allows to discriminate between lung and breast cancer, indicating that the metabolite profile reflects more than a general cancer marker. CLINICAL TRIAL REGISTRATION NUMBER NCT02362776.

Does nivolumab for progressed metastatic lung cancer fulfill its promises? An efficacy and safety analysis in 20 general hospitals

OBJECTIVES In patients with refractory or recurrent non-small-cell lung cancer (NSCLC) after first line chemotherapy, phase III trials showed superiority of nivolumab, an IgG4 programmed death-1 immune-checkpoint-inhibitor antibody, over docetaxel. We evaluated case mix, effectiveness and safety of nivolumab upon implementation in general practice. MATERIALS AND METHODS In 20 general hospitals, all consecutive NSCLC patients treated with nivolumab within the medical need program (inclusion period 12 months) in Flanders - Belgium were evaluated. RESULTS There were 267 patients, Eastern Cooperative Oncology Group (ECOG) score was 2 in 24% and 0-1 in 76%. In 48%, two or more systemic regimens were given before nivolumab. The median overall survival was 7.8 months (95% confidence interval (CI) 6.3-9.3). At one year, the overall survival rate was 36.5±0.34%. Median progression-free survival was 3.7 months (95% CI 2.9-4.5). An objective response was obtained in 23.2%. ECOG score 2 and presence of liver metastasis strongly correlated with worse survival (p<0.00001). Treatment related adverse events grade 3 or 4 were reported in 21%, colitis (4%) and pneumonitis (7%) were most frequent. CONCLUSION Upon implementation of nivolumab therapy in general hospitals, the case mix was characterized by a more heavily pretreated population with a substantial fraction of patients with ECOG score 2. The median overall survival is slightly inferior to what was published in the randomized phase III trials. An ECOG score 2 and the presence of liver metastasis correlated strongly with a worse survival. We report a high prevalence of serious adverse events.

Metabolic phenotyping of human plasma by 1H-NMR at high and medium magnetic field strengths: a case study for lung cancer: High-field (900 MHz) versus medium-field (400 MHz) NMR metabolomics

Accurate identification and quantification of human plasma metabolites can be challenging in crowded regions of the NMR spectrum with severe signal overlap. Therefore, this study describes metabolite spiking experiments on the basis of which the NMR spectrum can be rationally segmented into well‐defined integration regions, and this for spectrometers having magnetic field strengths corresponding to 1H resonance frequencies of 400 MHz and 900 MHz. Subsequently, the integration data of a case–control dataset of 69 lung cancer patients and 74 controls were used to train a multivariate statistical classification model for both field strengths. In this way, the advantages/disadvantages of high versus medium magnetic field strength were evaluated. The discriminative power obtained from the data collected at the two magnetic field strengths is rather similar, i.e. a sensitivity and specificity of respectively 90 and 97% for the 400 MHz data versus 88 and 96% for the 900 MHz data. This shows that a medium‐field NMR spectrometer (400–600 MHz) is already sufficient to perform clinical metabolomics. However, the improved spectral resolution (reduced signal overlap) and signal‐to‐noise ratio of 900 MHz spectra yield more integration regions that represent a single metabolite. This will simplify the unraveling and understanding of the related, disease disturbed, biochemical pathways. Copyright

1168PVALIDATION OF 1H-NMR-BASED METABOLOMICS AS A TOOL TO DETECT LUNG CANCER IN HUMAN BLOOD PLASMA

ABSTRACT Aim: Until today no effective method permits the early detection of lung cancer. Evidence has shown that disturbances in biochemical pathways which occur during the development of cancer provoke, changes in the metabolic phenotype. Recently, our research group has constructed a statistical classifier by means of multivariate orthogonal partial least squares-discriminant analysis (OPLS-DA). This classifier (constructed with 110 variables) allows to discriminate between 190 lung cancer patients (71% male, 29% female, age: 68 ± 10, BMI: 25.8 ± 4.7) and 182 controls (53% male, 47% female, age: 69 + 11, BMI: 28.1 ± 4.8) with a sensitivity of 76% and a specificity of 89%, with an AUC of 0.86. When only the 19 most discriminating variables (VIP value > 0.8) were selected to construct a classifier (i.e. glucose, lactate, myo-inositol, threonine, alanine, isoleucine and lipids signals) a sensitivity of 69%, a specificity of 83% and an AUC of 0.81 is achieved. The present study aims to examine the predictive accuracy of these statistical classifiers in an independent cohort of 50 lung cancer patients (60% male, 40% female, age: 67 ± 9, BMI: 25.6 ± 4.3) and 58 controls (64% male, 36% female, age: 63 ± 13, BMI: 26.9 ± 5.7). Methods: The metabolic phenotype of the plasma samples from this independent cohort is determined by 1H-NMR spectroscopy. Subsequently, the constructed classifiers are used to classify the independent samples. OPLS-DA is used as discriminant statistic. Results: By using the classifier constructed with all 110 variables, 72% of the lung cancer patients and 72% of the controls are correctly classified, with an AUC of 0.79. Moreover, when the classifier constructed with only the 19 most discriminating variables is used to classify the independent samples, a sensitivity of 82%, a specificity of 64% and an AUC of 0.79 is achieved. Conclusions: A statistical classifier constructed with only the most discriminating variables shows already a fair predictive accuracy, similar to this of the classifier build with all variables. Future experiments will investigate whether the constructed classifier can be used as a valid screening tool. Disclosure: All authors have declared no conflicts of interest.

The plasma glutamate concentration as a complementary tool to differentiate benign PET-positive lung lesions from lung cancer

BackgroundPulmonary imaging often identifies suspicious abnormalities resulting in supplementary diagnostic procedures. This study aims to investigate whether the metabolic fingerprint of plasma allows to discriminate between patients with lung inflammation and patients with lung cancer.MethodsMetabolic profiles of plasma from 347 controls, 269 cancer patients and 108 patients with inflammation were obtained by 1H-NMR spectroscopy. Models to discriminate between groups were trained by PLS-LDA. A test set was used for independent validation. A ROC curve was built to evaluate the diagnostic performance of potential biomarkers.ResultsSensitivity, specificity, PPV and NPV of PET-CT to diagnose cancer are 96, 23, 76 and 71%. Metabolic profiles differentiate between cancer and inflammation with a sensitivity of 89%, a specificity of 87% and a MCE of 12%. Removal of the glutamate metabolite results in an increase of MCE (38%) and a decrease of both sensitivity and specificity (62%), demonstrating the importance of glutamate for discrimination. At the cut-off point 0.31 on the ROC curve, the relative glutamate concentration discriminates between cancer and inflammation with a sensitivity of 85%, a specificity of 81%, and an AUC of 0.88. PPV and NPV are 92 and 69%. In PET-positive patients with a relative glutamate level ≤ 0.31 the sensitivity to diagnose cancer reaches 100% with a PPV of 94%. In PET-negative patients, a relative glutamate level > 0.31 increases the specificity of PET from 23% to 58% and results in a high NPV of 100%. In case of discrepancy between SUVmax and the glutamate concentration, lung cancer is missed in 19% of the cases.ConclusionThis study indicates that the 1H-NMR-derived relative plasma concentration of glutamate allows discrimination between lung cancer and lung inflammation. A glutamate level ≤ 0.31 in PET-positive patients corresponds to the diagnosis of lung cancer with a higher specificity and PPV than PET-CT. Glutamate levels > 0.31 in patients with PET negative lung lesions is likely to correspond with inflammation. Caution is needed for patients with conflicting SUVmax values and glutamate concentrations. Confirmation is needed in a prospective study with external validation and by another analytical technique such as HPLC-MS.

Sarcoidosis around the Globe

Abstract Despite sarcoidosis having a worldwide occurrence, the epidemiological map still has gaps. Prevalence and incidence rates‐inconsistences have been mainly due to a lack of uniformity in study definitions as well as data collection methods. Nonetheless, studies have been consistent in showing high prevalence and incidence in Scandinavian and African American populations. Data from racially diverse populations have consistently revealed highest incidence in people of African descent. Within populations, geographical (north‐to‐south gradient) and time clusters have also been demonstrated from place to place. Of great interest but still elusive to researchers is the cause of sarcoidosis. The most recent focus has mostly been on Mycobacteria species and Propionibacterium acnes, but results of research thus far have been less than outright and in some cases conflicting. Environmental exposures to such substances as mold and mildew and occupations such as agricultural employment, health care work, and firefighting have been widely cited as risk factors for diseases. Certain genotypes have been linked to sarcoidosis with familial and racial clusters apparent. Some disease phenotypes have also been linked to particular genes, leaving room for further genetic research. Sarcoidosis causes multisystemic morbidity, with pulmonary, cardiac, and neurological involvement carrying the worst prognosis. Disease phenotypes vary with ethnicity, suggesting a genetic predisposition; erythema nodosum is more common in Caucasian patients, cardiac manifestations in Japanese patients, and other extrathoracic disease in black patients.