Medico-economic evaluation of infliximab in rheumatoid arthritis—prospective French study of a cohort of 635 patients monitored for two years

Objectives. To perform, in real conditions of prescription, the medico-economic evaluation of infliximab in severe RA. Methods. A cost-effectiveness analysis of the annual costs was done with a comparison between the previous and the following year under infliximab. The effectiveness, determined from the HAQ, was expressed in clinically significant units and in quality-adjusted life years (QALYs). The incremental net benefit (INB), defined as willingness to pay (λ), was used to express the results. Results. A cohort of 635 patients was formed. Before the use of infliximab, after 1 and 2 years, the mean annual cost per patient for the care of RA was €9832, 27 723 and 46 704, respectively. Among the direct costs, infliximab accounts for €21 182 for the first year. The distribution of the different costs was similar after 2 years. By using the INB, the difference before and after 1 year under infliximab is significant, on average by 1.86 (s.e.m. = 0.76) when the effectiveness is expressed in clinically significant units. For severe HAQ, λ is €9841 (18 593 for all HAQ). When it is expressed in QALYs, also for severe HAQ, λ >€100 000. This can be explained by a short follow-up although severe complication of RA appears later. Conclusion. An evaluation of the more long-term costs is required in order to determine whether there are any full economic benefits with this treatmen

Under-treatment of elderly patients with ovarian cancer: a population based study

International audienceAbstractBackgroundOvarian cancer is the fourth most common cancer among women in France, and mainly affects the elderly. The primary objective of this study was to compare treatment of ovarian cancer according to age.MethodsAll patients with invasive cancer (n = 1151) diagnosed between 1997 and 2011 in the Herault Department of southern France were included. Demographic data (age, area of residence), cancer characteristics (stage, histology, grade) and treatment modality (type, period and location of treatment) were analysed. Univariate and multivariate logistic regression was used to compare treatment by age.ResultsOvarian cancer was less treated in elderly compared to younger patients, regardless of the type of treatment. This difference was more pronounced for chemotherapy, and was maximal for surgery followed by chemotherapy (odds ratio (OR) for surgery for patients aged >70 vs those aged 70 vs 70 vs <70 = 0.14 [0.08–0.28]). This effect of age was independent of other variables, including stage and grade. The probability of receiving standard treatment, in accordance with recommendations, was reduced by 50 % in elderly patients compared to their younger counterparts. Overall and net survival of elderly patients with standard treatment was similar to those of younger patients treated outside standard treatment.ConclusionsElderly women with ovarian cancer were therapeutically disadvantaged compared to younger women. Further studies including co morbidities are necessary to refine these results and to improve therapeutic management of elderly patients with ovarian cancer

Comparison of Supervised Classification Methods for Protein Profiling in Cancer Diagnosis

A key challenge in clinical proteomics of cancer is the identification of biomarkers that could allow detection, diagnosis and prognosis of the diseases. Recent advances in mass spectrometry and proteomic instrumentations offer unique chance to rapidly identify these markers. These advances pose considerable challenges, similar to those created by microarray-based investigation, for the discovery of pattern of markers from high-dimensional data, specific to each pathologic state (e.g. normal vs cancer). We propose a three-step strategy to select important markers from high-dimensional mass spectrometry data using surface enhanced laser desorption/ionization (SELDI) technology. The first two steps are the selection of the most discriminating biomarkers with a construction of different classifiers. Finally, we compare and validate their performance and robustness using different supervised classification methods such as Support Vector Machine, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Neural Networks, Classification Trees and Boosting Trees. We show that the proposed method is suitable for analysing high-throughput proteomics data and that the combination of logistic regression and Linear Discriminant Analysis outperform other methods tested

Serum Proteomic Profiling of Lung Cancer in High-Risk Groups and Determination of Clinical Outcomes

HypothesisLung cancer remains the leading cause of cancer-related mortality worldwide. Currently known serum markers do not efficiently diagnose lung cancer at early stage.MethodsIn the present study, we developed a serum proteomic fingerprinting approach coupled with a three-step classification method to address two important clinical questions: (i) to determine whether or not proteomic profiling differs between lung cancer and benign lung diseases in a population of smokers and (ii) to assess the prognostic impact of this profiling in lung cancer. Proteomic spectra were obtained from 170 pathologically confirmed lung cancer or smoking patients with benign chronic lung disease serum samples.ResultsAmong the 228 protein peaks differentially expressed in the whole population, 88 differed significantly between lung cancer patients and benign lung disease, with area under the curve diagnostic values ranging from 0.63 to 0.84. Multiprotein classifiers based on differentially expressed peaks allowed the classification of lung cancer and benign disease with an area under the curve ranging from 0.991 to 0.994. Using a cross-validation methodology, diagnostic accuracy was 93.1% (sensitivity 94.3%, specificity 85.9%), and more than 90% of the stage I/II lung cancers were correctly classified. Finally, in the prognosis part of the study, a 4628 Da protein was found to be significantly and independently associated with prognosis in advanced stage non-small cell lung cancer patients (p = 0.0005).ConclusionsThe potential markers that we identified through proteomic fingerprinting could accurately classify lung cancers in a high-risk population and predict survival in a non-small cell lung cancer population

TAFIRA [Material gráfico]

ADQUIRIDA POR EL COLECCIONISTA EN LAS PALMAS DE G.C.FOTO POSTAL DE "TAFIRA. VISTA PARCIAL"Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte. Subdirección General de Coordinación Bibliotecaria, 201

Personal non-commercial use only

ABSTRACT. Objective. To report the 5-year outcome of a large prospective cohort of patients with very early rheumatoid arthritis (RA), and to identify factors predictive of outcome. Methods. Patients were recruited if they had early arthritis of &lt; 6 months&apos; duration, had a high probability of developing RA, and had never been prescribed disease-modifying antirheumatic drugs (DMARD) or steroids. Logistic regression analysis was used to determine factors that predict outcome. Results. We included 813 patients from December 2002 to April 2005. Age was 48.1 ± 12.6 years, delay before referral 103.1 ± 52.4 days, 28-joint Disease Activity Score (DAS28) 5.1 ± 1.3, Health Assessment Questionnaire (HAQ) 1.0 ± 0.7; 45.8% and 38.7% had rheumatoid factor or antibodies to cyclic citrullinated peptide (anti-CCP), respectively; 22% had hand or foot erosions; 78.5% fulfilled the American College of Rheumatology/European League Against Rheumatism criteria for RA at baseline and 93.8% during followup. At 5 years, 573 patients were evaluated. The outcome was mild for most patients: disease activity (median DAS28 = 2.5) and HAQ disability (median 0.3) were well controlled over time; 50.6% achieved DAS28 remission and 64.7% low disease activity. Radiographic progression was low (2.9 Sharp unit/year) and only a few patients required joint surgery. Nevertheless, some patients developed new comorbidities. During the 5 years, 82.7% of patients had received at least 1 DMARD (methotrexate, 65.9%), 18.3% a biological DMARD, and about 60% prednisone at least once. Anti-CCP was the best predictor of remaining in the cohort for 5 years, of prescription of synthetic or biologic DMARD, and of radiographic progression. Conclusion. The 5-year outcome of an early RA cohort in the 2000s was described. Anti-CCP was a robust predictor of outcome. The generally good 5-year outcome could be related to early referral and early effective treatment, key processes in the management of early RA in daily practice

5-year RA outcomes Personal non-commercial use only

ABSTRACT. Objective. To report the 5-year outcome of a large prospective cohort of patients with very early rheumatoid arthritis (RA), and to identify factors predictive of outcome. Methods. Patients were recruited if they had early arthritis of &lt; 6 months&apos; duration, had a high probability of developing RA, and had never been prescribed disease-modifying antirheumatic drugs (DMARD) or steroids. Logistic regression analysis was used to determine factors that predict outcome. Results. We included 813 patients from December 2002 to April 2005. Age was 48.1 ± 12.6 years, delay before referral 103.1 ± 52.4 days, 28-joint Disease Activity Score (DAS28) 5.1 ± 1.3, Health Assessment Questionnaire (HAQ) 1.0 ± 0.7; 45.8% and 38.7% had rheumatoid factor or antibodies to cyclic citrullinated peptide (anti-CCP), respectively; 22% had hand or foot erosions; 78.5% fulfilled the American College of Rheumatology/European League Against Rheumatism criteria for RA at baseline and 93.8% during followup. At 5 years, 573 patients were evaluated. The outcome was mild for most patients: disease activity (median DAS28 = 2.5) and HAQ disability (median 0.3) were well controlled over time; 50.6% achieved DAS28 remission and 64.7% low disease activity. Radiographic progression was low (2.9 Sharp unit/year) and only a few patients required joint surgery. Nevertheless, some patients developed new comorbidities. During the 5 years, 82.7% of patients had received at least 1 DMARD (methotrexate, 65.9%), 18.3% a biological DMARD, and about 60% prednisone at least once. Anti-CCP was the best predictor of remaining in the cohort for 5 years, of prescription of synthetic or biologic DMARD, and of radiographic progression. Conclusion. The 5-year outcome of an early RA cohort in the 2000s was described. Anti-CCP was a robust predictor of outcome. The generally good 5-year outcome could be related to early referral and early effective treatment, key processes in the management of early RA in daily practice

On the censored cost-effectiveness analysis using copula information

Abstract Background Information and theory beyond copula concepts are essential to understand the dependence relationship between several marginal covariates distributions. In a therapeutic trial data scheme, most of the time, censoring occurs. That could lead to a biased interpretation of the dependence relationship between marginal distributions. Furthermore, it could result in a biased inference of the joint probability distribution function. A particular case is the cost-effectiveness analysis (CEA), which has shown its utility in many medico-economic studies and where censoring often occurs. Methods This paper discusses a copula-based modeling of the joint density and an estimation method of the costs, and quality adjusted life years (QALY) in a cost-effectiveness analysis in case of censoring. This method is not based on any linearity assumption on the inferred variables, but on a punctual estimation obtained from the marginal distributions together with their dependence link. Results Our results show that the proposed methodology keeps only the bias resulting statistical inference and don’t have anymore a bias based on a unverified linearity assumption. An acupuncture study for chronic headache in primary care was used to show the applicability of the method and the obtained ICER keeps in the confidence interval of the standard regression methodology. Conclusion For the cost-effectiveness literature, such a technique without any linearity assumption is a progress since it does not need the specification of a global linear regression model. Hence, the estimation of the a marginal distributions for each therapeutic arm, the concordance measures between these populations and the right copulas families is now sufficient to process to the whole CEA