15 resultados para Area Under Curve

em Université de Lausanne, Switzerland


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Purpose: While imatinib has revolutionized the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumors (GIST), its pharmacokinetic-pharmacodynamic relationships have been poorly studied. This study aimed to explore the issue in oncologic patients, and to evaluate the specific influence of the target genotype in a GIST subpopulation. Patients and methods: Data from 59 patients (321 plasma samples) were collected during a previous pharmacokinetic study. Based on a population model purposely developed, individual post-hoc Bayesian estimates of pharmacokinetic parameters were derived, and used to estimate drug exposure (AUC; area under curve). Free fraction parameters were deduced from a model incorporating plasma alpha1-acid glycoprotein levels. Associations between AUC (or clearance) and therapeutic response (coded on a 3-point scale), or tolerability (4-point scale), were explored by ordered logistic regression. Influence of KIT genotype on response was also assessed in GIST patients. Results: Total and free drug exposure correlated with the number of side effects (p < 0.005). A relationship with response was not evident in the whole patient set (with good-responders tending to receive lower doses and bad-responders higher doses). In GIST patients however, higher free drug exposure predicted better responses. A strong association was notably observed in patients harboring an exon 9 mutation or a wild type KIT, known to decrease tumor sensitivity towards imatinib (p < 0.005). Conclusions: Our results are arguments to further evaluate the potential benefit of a therapeutic monitoring program for imatinib. Our data also suggest that stratification by genotype will be important in future trials.

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Atazanavir inhibits UDP-glucuronyl-transferase-1A1 (UGT1A1), which metabolizes raltegravir, but the magnitude of steady-state inhibition and role of the UGT1A1 genotype are unknown. Sufficient inhibition could lead to reduced-dose and -cost raltegravir regimens. Nineteen healthy volunteers, age 24 to 51 years, took raltegravir 400 mg twice daily (arm A) and 400 mg plus atazanavir 400 mg once daily (arm B), separated by ?3 days, in a crossover design. After 1 week on each regimen, raltegravir and raltegravir-glucuronide plasma and urine concentrations were measured by liquid chromatography-tandem mass spectrometry in multiple samples obtained over 12 h (arm A) or 24 h (arm B) and analyzed by noncompartmental methods. UGT1A1 promoter variants were detected with a commercially available kit and published primers. The primary outcome was the ratio of plasma raltegravir C(tau), or concentration at the end of the dosing interval, for arm B (24 h) versus arm A (12 h). The arm B-to-arm A geometric mean ratios (95% confidence interval, P value) for plasma raltegravir C(tau), area under the concentration-time curve from 0 to 12 h (AUC(0-12)), and raltegravir-glucuronide/raltegravir AUC(0-12) were 0.38 (0.22 to 0.65, 0.001), 1.32 (0.62 to 2.81, 0.45), and 0.47 (0.38 to 0.59, <0.001), respectively. Nine volunteers were heterozygous and one was homozygous for a UGT1A1 reduction-of-function allele, but these were not associated with metabolite formation. Although atazanavir significantly reduced the formation of the glucuronide metabolite, its steady-state boosting of plasma raltegravir did not render the C(tau) with a once-daily raltegravir dose of 400 mg similar to the C(tau) with the standard twice-daily dose. UGT1A1 promoter variants did not significantly influence this interaction.

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AIMS/HYPOTHESIS: Several susceptibility genes for type 2 diabetes have been discovered recently. Individually, these genes increase the disease risk only minimally. The goals of the present study were to determine, at the population level, the risk of diabetes in individuals who carry risk alleles within several susceptibility genes for the disease and the added value of this genetic information over the clinical predictors. METHODS: We constructed an additive genetic score using the most replicated single-nucleotide polymorphisms (SNPs) within 15 type 2 diabetes-susceptibility genes, weighting each SNP with its reported effect. We tested this score in the extensively phenotyped population-based cross-sectional CoLaus Study in Lausanne, Switzerland (n = 5,360), involving 356 diabetic individuals. RESULTS: The clinical predictors of prevalent diabetes were age, BMI, family history of diabetes, WHR, and triacylglycerol/HDL-cholesterol ratio. After adjustment for these variables, the risk of diabetes was 2.7 (95% CI 1.8-4.0, p = 0.000006) for individuals with a genetic score within the top quintile, compared with the bottom quintile. Adding the genetic score to the clinical covariates improved the area under the receiver operating characteristic curve slightly (from 0.86 to 0.87), yet significantly (p = 0.002). BMI was similar in these two extreme quintiles. CONCLUSIONS/INTERPRETATION: In this population, a simple weighted 15 SNP-based genetic score provides additional information over clinical predictors of prevalent diabetes. At this stage, however, the clinical benefit of this genetic information is limited.

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RATIONALE: A dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a well-documented neurobiological finding in major depression. Moreover, clinically effective therapy with antidepressant drugs may normalize the HPA axis activity. OBJECTIVE: The aim of this study was to test whether citalopram (R/S-CIT) affects the function of the HPA axis in patients with major depression (DSM IV). METHODS: Twenty depressed patients (11 women and 9 men) were challenged with a combined dexamethasone (DEX) suppression and corticotropin-releasing hormone (CRH) stimulation test (DEX/CRH test) following a placebo week and after 2, 4, and 16 weeks of 40 mg/day R/S-CIT treatment. RESULTS: The results show a time-dependent reduction of adrenocorticotrophic hormone (ACTH) and cortisol response during the DEX/CRH test both in treatment responders and nonresponders within 16 weeks. There was a significant relationship between post-DEX baseline cortisol levels (measured before administration of CRH) and severity of depression at pretreatment baseline. Multiple linear regression analyses were performed to identify the impact of psychopathology and hormonal stress responsiveness and R/S-CIT concentrations in plasma and cerebrospinal fluid (CSF). The magnitude of decrease in cortisol responsivity from pretreatment baseline to week 4 on drug [delta-area under the curve (AUC) cortisol] was a significant predictor (p<0.0001) of the degree of symptom improvement following 16 weeks on drug (i.e., decrease in HAM-D21 total score). The model demonstrated that the interaction of CSF S-CIT concentrations and clinical improvement was the most powerful predictor of AUC cortisol responsiveness. CONCLUSION: The present study shows that decreased AUC cortisol was highly associated with S-CIT concentrations in plasma and CSF. Therefore, our data suggest that the CSF or plasma S-CIT concentrations rather than the R/S-CIT dose should be considered as an indicator of the selective serotonergic reuptake inhibitors (SSRIs) effect on HPA axis responsiveness as measured by AUC cortisol response.

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Objectives Nosocomial Pseudomonas aeruginosa pneumonia remains a major concern in critically ill patients. We explored the potential impact of microorganism-targeted adjunctive immunotherapy in such patients. Patients and methods This multicentre, open pilot Phase 2a clinical trial (NCT00851435) prospectively evaluated the safety, pharmacokinetics and potential efficacy of three doses of 1.2 mg/kg panobacumab, a fully human monoclonal anti-lipopolysaccharide IgM, given every 72 h in 18 patients developing nosocomial P. aeruginosa (serotype O11) pneumonia. Results Seventeen out of 18 patients were included in the pharmacokinetic analysis. In 13 patients receiving three doses, the maximal concentration after the third infusion was 33.9 ± 8.0 μg/mL, total area under the serum concentration-time curve was 5397 ± 1993 μg h/mL and elimination half-life was 102.3 ± 47.8 h. Panobacumab was well tolerated, induced no immunogenicity and was detected in respiratory samples. In contrast to Acute Physiology and Chronic Health Evaluation II (APACHE II) prediction, all 13 patients receiving three doses survived, with a mean clinical resolution in 9.0 ± 2.7 days. Two patients suffered a recurrence at days 17 and 20. Conclusions These data suggest that panobacumab is safe, with a pharmacokinetic profile similar to that in healthy volunteers. It was associated with high clinical cure and survival rates in patients developing nosocomial P. aeruginosa O11 pneumonia. We concluded that these promising results warrant further trials.

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Metalworking fluid-associated hypersensitivity pneumonitis (MWF-HP) is a pulmonary disease caused by inhaling microorganisms present in the metalworking fluids used in the industrial sector. Mycobacterium immunogenum is the main etiological agent. Among the clinical, radiological and biological tools used for diagnosis, serological tests are important. The aim of this study was to identify immunogenic proteins in M. immunogenum and to use recombinant antigens for serological diagnosis of MWF-HP. Immunogenic proteins were detected by two-dimensional Western blot and candidate proteins were identified by mass spectrometry. Recombinant antigens were expressed in Escherichia coli and tested by enzyme-linked immunosorbent assay (ELISA) with the sera of 14 subjects with MWF-HP and 12 asymptomatic controls exposed to M. immunogenum. From the 350 spots visualized by two-dimensional gel electrophoresis with M. immunogenum extract, 6 immunogenic proteins were selected to be expressed as recombinant antigens. Acyl-CoA dehydrogenase antigen allowed for the best discrimination of MWF-HP cases against controls with an area under the receiver operating characteristics (ROC) curve of 0.930 (95% CI=0.820-1), a sensitivity of 100% and a specificity of 83% for the optimum threshold. Other recombinant antigens correspond to acyl-CoA dehydrogenase FadE, cytosol aminopeptidase, dihydrolipoyl dehydrogenase, serine hydroxymethyltransferase and superoxide dismutase. This is the first time that recombinant antigens have been used for the serodiagnosis of hypersensitivity pneumonitis. The availability of recombinant antigens makes it possible to develop standardized serological tests which in turn could simplify diagnosis, thus making it less invasive.

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The World Health Organization (WHO) criteria for the diagnosis of osteoporosis are mainly applicable for dual X-ray absorptiometry (DXA) measurements at the spine and hip levels. There is a growing demand for cheaper devices, free of ionizing radiation such as promising quantitative ultrasound (QUS). In common with many other countries, QUS measurements are increasingly used in Switzerland without adequate clinical guidelines. The T-score approach developed for DXA cannot be applied to QUS, although well-conducted prospective studies have shown that ultrasound could be a valuable predictor of fracture risk. As a consequence, an expert committee named the Swiss Quality Assurance Project (SQAP, for which the main mission is the establishment of quality assurance procedures for DXA and QUS in Switzerland) was mandated by the Swiss Association Against Osteoporosis (ASCO) in 2000 to propose operational clinical recommendations for the use of QUS in the management of osteoporosis for two QUS devices sold in Switzerland. Device-specific weighted "T-score" based on the risk of osteoporotic hip fractures as well as on the prediction of DXA osteoporosis at the hip, according to the WHO definition of osteoporosis, were calculated for the Achilles (Lunar, General Electric, Madison, Wis.) and Sahara (Hologic, Waltham, Mass.) ultrasound devices. Several studies (totaling a few thousand subjects) were used to calculate age-adjusted odd ratios (OR) and area under the receiver operating curve (AUC) for the prediction of osteoporotic fracture (taking into account a weighting score depending on the design of the study involved in the calculation). The ORs were 2.4 (1.9-3.2) and AUC 0.72 (0.66-0.77), respectively, for the Achilles, and 2.3 (1.7-3.1) and 0.75 (0.68-0.82), respectively, for the Sahara device. To translate risk estimates into thresholds for clinical application, 90% sensitivity was used to define low fracture and low osteoporosis risk, and a specificity of 80% was used to define subjects as being at high risk of fracture or having osteoporosis at the hip. From the combination of the fracture model with the hip DXA osteoporotic model, we found a T-score threshold of -1.2 and -2.5 for the stiffness (Achilles) determining, respectively, the low- and high-risk subjects. Similarly, we found a T-score at -1.0 and -2.2 for the QUI index (Sahara). Then a screening strategy combining QUS, DXA, and clinical factors for the identification of women needing treatment was proposed. The application of this approach will help to minimize the inappropriate use of QUS from which the whole field currently suffers.

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BACKGROUND: The presence of multiple melanocytic naevi is a strong risk factor for melanoma. Use of the whole body naevus count to identify at-risk patients is impractical. OBJECTIVES: To (i) identify a valid anatomical predictor of total naevus count; (ii) determine the number of naevi that most accurately predict total naevus count above 25, 50 and 100; and (iii) evaluate determinants of multiple melanocytic naevi and atypical naevi. METHODS: Clinical data from 292 consecutive Spanish patients consulting for skin lesions requiring debriding were collected throughout 2009 and 2010. Correlations between site-specific and whole body naevus counts were analysed. Cut-offs to predict total naevus counts were determined using the area under the receiver operating characteristic curve. RESULTS: The studied population was young (median age 31 years, interquartile range 28-43). The naevus count on the right arm correlated best with the total nevus count (R(2) 0·80 for men, 0·86 for women). Presence of at least five naevi on the right arm was the strongest determinant of a total naevus count above 50 [odds ratio (OR) 34·4, 95% confidence interval (CI) 13·9-85·0] and of having at least one atypical naevus (OR 5·7, 95% CI 2·4-13·5). Cut-off values of 6, 8 and 11 naevi on the right arm best predicted total naevus count above 25, 50 and 100, respectively. CONCLUSIONS: Our results support the arm as a practical and reliable site to estimate the total naevus count when screening or phenotyping large populations. Threshold values for the number of naevi on the arm are proposed to help identify patients for melanoma screening.

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QUESTIONS UNDER STUDY AND PRINCIPLES: Estimating glomerular filtration rate (GFR) in hospitalised patients with chronic kidney disease (CKD) is important for drug prescription but it remains a difficult task. The purpose of this study was to investigate the reliability of selected algorithms based on serum creatinine, cystatin C and beta-trace protein to estimate GFR and the potential added advantage of measuring muscle mass by bioimpedance. In a prospective unselected group of patients hospitalised in a general internal medicine ward with CKD, GFR was evaluated using inulin clearance as the gold standard and the algorithms of Cockcroft, MDRD, Larsson (cystatin C), White (beta-trace) and MacDonald (creatinine and muscle mass by bioimpedance). 69 patients were included in the study. Median age (interquartile range) was 80 years (73-83); weight 74.7 kg (67.0-85.6), appendicular lean mass 19.1 kg (14.9-22.3), serum creatinine 126 μmol/l (100-149), cystatin C 1.45 mg/l (1.19-1.90), beta-trace protein 1.17 mg/l (0.99-1.53) and GFR measured by inulin 30.9 ml/min (22.0-43.3). The errors in the estimation of GFR and the area under the ROC curves (95% confidence interval) relative to inulin were respectively: Cockcroft 14.3 ml/min (5.55-23.2) and 0.68 (0.55-0.81), MDRD 16.3 ml/min (6.4-27.5) and 0.76 (0.64-0.87), Larsson 12.8 ml/min (4.50-25.3) and 0.82 (0.72-0.92), White 17.6 ml/min (11.5-31.5) and 0.75 (0.63-0.87), MacDonald 32.2 ml/min (13.9-45.4) and 0.65 (0.52-0.78). Currently used algorithms overestimate GFR in hospitalised patients with CKD. As a consequence eGFR targeted prescriptions of renal-cleared drugs, might expose patients to overdosing. The best results were obtained with the Larsson algorithm. The determination of muscle mass by bioimpedance did not provide significant contributions.

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BACKGROUND: Multiple risk prediction models have been validated in all-age patients presenting with acute coronary syndrome (ACS) and treated with percutaneous coronary intervention (PCI); however, they have not been validated specifically in the elderly. METHODS: We calculated the GRACE (Global Registry of Acute Coronary Events) score, the logistic EuroSCORE, the AMIS (Acute Myocardial Infarction Swiss registry) score, and the SYNTAX (Synergy between Percutaneous Coronary Intervention with TAXUS and Cardiac Surgery) score in a consecutive series of 114 patients ≥75 years presenting with ACS and treated with PCI within 24 hours of hospital admission. Patients were stratified according to score tertiles and analysed retrospectively by comparing the lower/mid tertiles as an aggregate group with the higher tertile group. The primary endpoint was 30-day mortality. Secondary endpoints were the composite of death and major adverse cardiovascular events (MACE) at 30 days, and 1-year MACE-free survival. Model discrimination ability was assessed using the area under receiver operating characteristic curve (AUC). RESULTS: Thirty-day mortality was higher in the upper tertile compared with the aggregate lower/mid tertiles according to the logistic EuroSCORE (42% vs 5%; odds ratio [OR] = 14, 95% confidence interval [CI] = 4-48; p <0.001; AUC = 0.79), the GRACE score (40% vs 4%; OR = 17, 95% CI = 4-64; p <0.001; AUC = 0.80), the AMIS score (40% vs 4%; OR = 16, 95% CI = 4-63; p <0.001; AUC = 0.80), and the SYNTAX score (37% vs 5%; OR = 11, 95% CI = 3-37; p <0.001; AUC = 0.77). CONCLUSIONS: In elderly patients presenting with ACS and referred to PCI within 24 hours of admission, the GRACE score, the EuroSCORE, the AMIS score, and the SYNTAX score predicted 30 day mortality. The predictive value of clinical scores was improved by using them in combination.

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OBJECTIVE: Because of its high prevalence, early screening for occupational asthma (OA) is crucial. We aimed to evaluate the screening performance of the Occupational Asthma Screening Questionnaire-11 items (OASQ-11) in a clinical setting. METHODS: Between January 2009 and December 2011, 169 workers referred for potential OA to our hospital completed the OASQ-11 and underwent workups to determine the final diagnosis. The discriminative abilities of the OASQ-11 as a whole and in relation to demographic and exposure parameters were determined by the area under the receiving operator characteristic curve (AUC). RESULTS: Model 1, consisting of the OASQ's items, showed fair discrimination (AUC, 0.69; 95% confidence interval, 0.58 to 0.80). Addition of age and exposure duration to model 1 improved discrimination (AUC, 0.80; confidence interval, 0.72 to 0.88). CONCLUSION: A simple model consisting of the OASQ-11's items, age, and exposure duration could well discriminate subjects with OA in a clinical setting.

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QUESTIONS UNDER STUDY: The diagnostic significance of clinical symptoms/signs of influenza has mainly been assessed in the context of controlled studies with stringent inclusion criteria. There was a need to extend the evaluation of these predictors not only in the context of general practice but also according to the duration of symptoms and to the dynamics of the epidemic. PRINCIPLES: A prospective study conducted in the Medical Outpatient Clinic in the winter season 1999-2000. Patients with influenza-like syndrome were included, as long as the primary care physician envisaged the diagnosis of influenza. The physician administered a questionnaire, a throat swab was performed and a culture acquired to document the diagnosis of influenza. RESULTS: 201 patients were included in the study. 52% were culture positive for influenza. By univariate analysis, temperature >37.8 degrees C (OR 4.2; 95% CI 2.3-7.7), duration of symptoms <48 hours (OR 3.2; 1.8-5.7), cough (OR 3.2; 1-10.4) and myalgia (OR 2.8; 1.0-7.5) were associated with a diagnosis of influenza. In a multivariable logistic analysis, the best model predicting influenza was the association of a duration of symptom <48 hours, medical attendance at the beginning of the epidemic (weeks 49-50), fever >37.8 and cough, with a sensitivity of 79%, specificity of 69%, positive predictive value of 67%, negative predictive value of 73% and an area under the ROC curve of 0.74. CONCLUSIONS: Besides relevant symptoms and signs, the physician should also consider the duration of symptoms and the epidemiological context (start, peak or end of the epidemic) in his appraisal, since both parameters considerably modify the value of the clinical predictors when assessing the probability of a patient having influenza.

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OBJECTIVE: To develop predictive models for early triage of burn patients based on hypersusceptibility to repeated infections. BACKGROUND: Infection remains a major cause of mortality and morbidity after severe trauma, demanding new strategies to combat infections. Models for infection prediction are lacking. METHODS: Secondary analysis of 459 burn patients (≥16 years old) with 20% or more total body surface area burns recruited from 6 US burn centers. We compared blood transcriptomes with a 180-hour cutoff on the injury-to-transcriptome interval of 47 patients (≤1 infection episode) to those of 66 hypersusceptible patients [multiple (≥2) infection episodes (MIE)]. We used LASSO regression to select biomarkers and multivariate logistic regression to built models, accuracy of which were assessed by area under receiver operating characteristic curve (AUROC) and cross-validation. RESULTS: Three predictive models were developed using covariates of (1) clinical characteristics; (2) expression profiles of 14 genomic probes; (3) combining (1) and (2). The genomic and clinical models were highly predictive of MIE status [AUROCGenomic = 0.946 (95% CI: 0.906-0.986); AUROCClinical = 0.864 (CI: 0.794-0.933); AUROCGenomic/AUROCClinical P = 0.044]. Combined model has an increased AUROCCombined of 0.967 (CI: 0.940-0.993) compared with the individual models (AUROCCombined/AUROCClinical P = 0.0069). Hypersusceptible patients show early alterations in immune-related signaling pathways, epigenetic modulation, and chromatin remodeling. CONCLUSIONS: Early triage of burn patients more susceptible to infections can be made using clinical characteristics and/or genomic signatures. Genomic signature suggests new insights into the pathophysiology of hypersusceptibility to infection may lead to novel potential therapeutic or prophylactic targets.

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The updated Vienna Prediction Model for estimating recurrence risk after an unprovoked venous thromboembolism (VTE) has been developed to identify individuals at low risk for VTE recurrence in whom anticoagulation (AC) therapy may be stopped after 3 months. We externally validated the accuracy of the model to predict recurrent VTE in a prospective multicenter cohort of 156 patients aged ≥65 years with acute symptomatic unprovoked VTE who had received 3 to 12 months of AC. Patients with a predicted 12-month risk within the lowest quartile based on the updated Vienna Prediction Model were classified as low risk. The risk of recurrent VTE did not differ between low- vs higher-risk patients at 12 months (13% vs 10%; P = .77) and 24 months (15% vs 17%; P = 1.0). The area under the receiver operating characteristic curve for predicting VTE recurrence was 0.39 (95% confidence interval [CI], 0.25-0.52) at 12 months and 0.43 (95% CI, 0.31-0.54) at 24 months. In conclusion, in elderly patients with unprovoked VTE who have stopped AC, the updated Vienna Prediction Model does not discriminate between patients who develop recurrent VTE and those who do not. This study was registered at www.clinicaltrials.gov as #NCT00973596.

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UNLABELLED: Trabecular bone score (TBS) seems to provide additive value on BMD to identify individuals with prevalent fractures in T1D. TBS did not significantly differ between T1D patients and healthy controls, but TBS and HbA1c were independently associated with prevalent fractures in T1D. A TBS cutoff <1.42 reflected prevalent fractures with 91.7 % sensitivity and 43.2 % specificity. INTRODUCTION: Type 1 diabetes (T1D) increases the risk of osteoporotic fractures. TBS was recently proposed as an indirect measure of bone microarchitecture. This study aimed at investigating the TBS in T1D patients and healthy controls. Associations with prevalent fractures were tested. METHODS: One hundred nineteen T1D patients (59 males, 60 premenopausal females; mean age 43.4 ± 8.9 years) and 68 healthy controls matched for gender, age, and body mass index (BMI) were analyzed. The TBS was calculated in the lumbar region, based on two-dimensional (2D) projections of DXA assessments. RESULTS: TBS was 1.357 ± 0.129 in T1D patients and 1.389 ± 0.085 in controls (p = 0.075). T1D patients with prevalent fractures (n = 24) had a significantly lower TBS than T1D patients without fractures (1.309 ± 0.125 versus 1.370 ± 0.127, p = 0.04). The presence of fractures in T1D was associated with lower TBS (odds ratio = 0.024, 95 % confidence interval (CI) = 0.001-0.875; p = 0.042) but not with age or BMI. TBS and HbA1c were independently associated with fractures. The area-under-the curve (AUC) of TBS was similar to that of total hip BMD in discriminating T1D patients with or without prevalent fractures. In this set-up, a TBS cutoff <1.42 discriminated the presence of fractures with a sensitivity of 91.7 % and a specificity of 43.2 %. CONCLUSIONS: TBS values are lower in T1D patients with prevalent fractures, suggesting an alteration of bone strength in this subgroup of patients. Reliable TBS cutoffs for the prediction of fracture risk in T1D need to be determined in larger prospective studies.