Heterogeneity on long-term disability trajectories in patients with secondary progressive MS: a latent class analysis from Big MS Data network.

BACKGROUND: Over the decades, several natural history studies on patients with primary (PPMS) or secondary progressive multiple sclerosis (SPMS) were reported from international registries. In PPMS, a consistent heterogeneity on long-term disability trajectories was demonstrated. The aim of this study was to identify subgroups of patients with SPMS with similar longitudinal trajectories of disability over time. METHODS: All patients with MS collected within Big MS registries who received an SPMS diagnosis from physicians (cohort 1) or satisfied the Lorscheider criteria (cohort 2) were considered. Longitudinal Expanded Disability Status Scale (EDSS) scores were modelled by a latent class growth analysis (LCGA), using a non-linear function of time from the first EDSS visit in the range 3-4. RESULTS: A total of 3613 patients with SPMS were included in the cohort 1. LCGA detected three different subgroups of patients with a mild (n=1297; 35.9%), a moderate (n=1936; 53.6%) and a severe (n=380; 10.5%) disability trajectory. Median time to EDSS 6 was 12.1, 5.0 and 1.7 years, for the three groups, respectively; the probability to reach EDSS 6 at 8 years was 14.4%, 78.4% and 98.3%, respectively. Similar results were found among 7613 patients satisfying the Lorscheider criteria. CONCLUSIONS: Contrary to previous interpretations, patients with SPMS progress at greatly different rates. Our identification of distinct trajectories can guide better patient selection in future phase 3 SPMS clinical trials. Additionally, distinct trajectories could reflect heterogeneous pathological mechanisms of progression.

The use and quality of reporting of propensity score methods in multiple sclerosis literature: A review.

BACKGROUND: Propensity score (PS) analyses are increasingly used in multiple sclerosis (MS) research, largely owing to the greater availability of large observational cohorts and registry databases. OBJECTIVE: To evaluate the use and quality of reporting of PS methods in the recent MS literature. METHODS: We searched the PubMed database for articles published between January 2013 and July 2019. We restricted the search to comparative effectiveness studies of two disease-modifying therapies. RESULTS: Thirty-nine studies were included in the review, with most studies (62%) published within the past 3 years. All studies reported the list of covariates used for the PS model, but only 21% of studies mentioned how those covariates were selected. Most studies used PS matching (72%), followed by PS adjustment (18%), weighting (15%), and stratification (3%), with some overlap. Most studies using matching or weighting reported checking post-PS covariate imbalance (91%), although about 45% of these studies relied on p values from various statistical tests. Only 25% of studies using matching reported calculating robust standard errors for the PS analyses. CONCLUSIONS: The quality of reporting of PS methods in the MS literature is sub-optimal in general, and in some cases, inappropriate methods are used.

Recommendations for the use of propensity score methods in multiple sclerosis research.

BACKGROUND: With many disease-modifying therapies currently approved for the management of multiple sclerosis, there is a growing need to evaluate the comparative effectiveness and safety of those therapies from real-world data sources. Propensity score methods have recently gained popularity in multiple sclerosis research to generate real-world evidence. Recent evidence suggests, however, that the conduct and reporting of propensity score analyses are often suboptimal in multiple sclerosis studies. OBJECTIVES: To provide practical guidance to clinicians and researchers on the use of propensity score methods within the context of multiple sclerosis research. METHODS: We summarize recommendations on the use of propensity score matching and weighting based on the current methodological literature, and provide examples of good practice. RESULTS: Step-by-step recommendations are presented, starting with covariate selection and propensity score estimation, followed by guidance on the assessment of covariate balance and implementation of propensity score matching and weighting. Finally, we focus on treatment effect estimation and sensitivity analyses. CONCLUSION: This comprehensive set of recommendations highlights key elements that require careful attention when using propensity score methods.

Early treatment delays long-term disability accrual in RRMS: Results from the BMSD network.

BACKGROUND: The optimal timing of treatment starts for achieving the best control on the long-term disability accumulation in multiple sclerosis (MS) is still to be defined. OBJECTIVE: The aim of this study was to estimate the optimal time to start disease-modifying therapies (DMTs) to prevent the long-term disability accumulation in MS, using a pooled dataset from the Big Multiple Sclerosis Data (BMSD) network. METHODS: Multivariable Cox regression models adjusted for the time to first treatment start from disease onset (in quintiles) were used. To mitigate the impact of potential biases, a set of pairwise propensity score (PS)-matched analyses were performed. The first quintile, including patients treated within 1.2 years from onset, was used as reference. RESULTS: A cohort of 11,871 patients (median follow-up after treatment start: 13.2 years) was analyzed. A 3- and 12-month confirmed disability worsening event and irreversible Expanded Disability Status Scale (EDSS) 4.0 and 6.0 scores were reached by 7062 (59.5%), 4138 (34.9%), 3209 (31.1%), and 1909 (16.5%) patients, respectively. The risk of reaching all the disability outcomes was significantly lower (p < 0.0004) for the first quintile patients' group. CONCLUSION: Real-world data from the BMSD demonstrate that DMTs should be commenced within 1.2 years from the disease onset to reduce the risk of disability accumulation over the long term.

A two-stage prediction model for heterogeneous effects of treatments.

Treatment effects vary across different patients, and estimation of this variability is essential for clinical decision-making. We aimed to develop a model estimating the benefit of alternative treatment options for individual patients, extending a risk modeling approach in a network meta-analysis framework. We propose a two-stage prediction model for heterogeneous treatment effects by combining prognosis research and network meta-analysis methods where individual patient data are available. In the first stage, a prognostic model to predict the baseline risk of the outcome. In the second stage, we use the baseline risk score from the first stage as a single prognostic factor and effect modifier in a network meta-regression model. We apply the approach to a network meta-analysis of three randomized clinical trials comparing the relapses in Natalizumab, Glatiramer Acetate, and Dimethyl Fumarate, including 3590 patients diagnosed with relapsing-remitting multiple sclerosis. We find that the baseline risk score modifies the relative and absolute treatment effects. Several patient characteristics, such as age and disability status, impact the baseline risk of relapse, which in turn moderates the benefit expected for each of the treatments. For high-risk patients, the treatment that minimizes the risk of relapse in 2 years is Natalizumab, whereas Dimethyl Fumarate might be a better option for low-risk patients. Our approach can be easily extended to all outcomes of interest and has the potential to inform a personalized treatment approach.

Predicting disability progression in multiple sclerosis: Insights from advanced statistical modeling.

BACKGROUND: There is an unmet need for precise methods estimating disease prognosis in multiple sclerosis (MS). OBJECTIVE: Using advanced statistical modeling, we assessed the prognostic value of various clinical measures for disability progression. METHODS: Advanced models to assess baseline prognostic factors for disability progression over 2 years were applied to a pooled sample of patients from placebo arms in four different phase III clinical trials. least absolute shrinkage and selection operator (LASSO) and ridge regression, elastic nets, support vector machines, and unconditional and conditional random forests were applied to model time to clinical disability progression confirmed at 24 weeks. Sensitivity analyses for different definitions of a combined endpoint were carried out, and bootstrap was used to assess prediction model performance. RESULTS: A total of 1582 patients were included, of which 434 (27.4%) had disability progression in a combined endpoint over 2 years. Overall model discrimination performance was relatively poor (all C-indices ⩽ 0.65) across all models and across different definitions of progression. CONCLUSION: Inconsistency of prognostic factor importance ranking confirmed the relatively poor prediction ability of baseline factors in modeling disease progression in MS. Our findings underline the importance to explore alternative predictors as well as alternative definitions of commonly used endpoints.

A proof-of-concept application of a novel scoring approach for personalized medicine in multiple sclerosis.

BACKGROUND: Stratified medicine methodologies based on subgroup analyses are often insufficiently powered. More powerful personalized medicine approaches are based on continuous scores. OBJECTIVE: We deployed a patient-specific continuous score predicting treatment response in patients with relapsing-remitting multiple sclerosis (RRMS). METHODS: Data from two independent randomized controlled trials (RCTs) were used to build and validate an individual treatment response (ITR) score, regressing annualized relapse rates (ARRs) on a set of baseline predictors. RESULTS: The ITR score for the combined treatment groups versus placebo detected differential clinical response in both RCTs. High responders in one RCT had a cross-validated ARR ratio of 0.29 (95% confidence interval (CI) = 0.13-0.55) versus 0.62 (95% CI = 0.47-0.83) for all other responders (heterogeneity p = 0.038) and were validated in the other RCT, with the corresponding ARR ratios of 0.31 (95% CI = 0.18-0.56) and 0.61 (95% CI = 0.47-0.79; heterogeneity p = 0.036). The strongest treatment effect modifiers were the Short Form-36 Physical Component Summary, age, Visual Function Test 2.5%, prior MS treatment and Expanded Disability Status Scale. CONCLUSION: Our modelling strategy detects and validates an ITR score and opens up avenues for building treatment response calculators that are also applicable in routine clinical practice.

On the aggregation of published prognostic scores for causal inference in observational studies.

As real world evidence on drug efficacy involves nonrandomized studies, statistical methods adjusting for confounding are needed. In this context, prognostic score (PGS) analysis has recently been proposed as a method for causal inference. It aims to restore balance across the different treatment groups by identifying subjects with a similar prognosis for a given reference exposure ("control"). This requires the development of a multivariable prognostic model in the control arm of the study sample, which is then extrapolated to the different treatment arms. Unfortunately, large cohorts for developing prognostic models are not always available. Prognostic models are therefore subject to a dilemma between overfitting and parsimony; the latter being prone to a violation of the assumption of no unmeasured confounders when important covariates are ignored. Although it is possible to limit overfitting by using penalization strategies, an alternative approach is to adopt evidence synthesis. Aggregating previously published prognostic models may improve the generalizability of PGS, while taking account of a large set of covariates-even when limited individual participant data are available. In this article, we extend a method for prediction model aggregation to PGS analysis in nonrandomized studies. We conduct extensive simulations to assess the validity of model aggregation, compared with other methods of PGS analysis for estimating marginal treatment effects. We show that aggregating existing PGS into a "meta-score" is robust to misspecification, even when elementary scores wrongfully omit confounders or focus on different outcomes. We illustrate our methods in a setting of treatments for asthma.

The Long-Term Impact of Renin-Angiotensin System (RAS) Inhibition on Cardiorenal Outcomes (LIRICO): A Randomized, Controlled Trial.

BACKGROUND: The comparative effectiveness of treatment with angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), or their combination in people with albuminuria and cardiovascular risk factors is unclear. METHODS: In a multicenter, randomized, open label, blinded end point trial, we evaluated the effectiveness on cardiovascular events of ACE or ARB monotherapy or combination therapy, targeting BP<130/80 in patients with moderate or severe albuminuria and diabetes or other cardiovascular risk factors. End points included a primary composite of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, and hospitalization for cardiovascular causes and a revised end point of all-cause mortality. Additional end points included ESRD, doubling of serum creatinine, albuminuria, eGFR, BP, and adverse events. RESULTS: Because of slow enrollment, the trial was modified and stopped 41% short of targeted enrollment of 2100 participants, corresponding to 35% power to detect a 25% reduced risk in the primary outcome. Our analysis included 1243 adults, with median follow-up of 2.7 years. Efficacy outcomes were similar between groups (ACE inhibitor versus ARB, ACE inhibitor versus combination, ARB versus combination) as were rates of serious adverse events. The rate of permanent discontinuation for ARB monotherapy (6.3%) was significantly lower than for ACE inhibitor monotherapy (15.7%) or combined therapy (18.3%). CONCLUSIONS: Patients may tolerate ARB monotherapy better than ACE inhibitor monotherapy. However, data from this trial and similar trials, although as yet inconclusive, show no trend suggesting differences in mortality and renal outcomes with ACE inhibitors or ARBs as dual or monotherapy in patients with albuminuria and diabetes or other cardiovascular risk factors.

Greater sensitivity to multiple sclerosis disability worsening and progression events using a roving versus a fixed reference value in a prospective cohort study.

BACKGROUND: Confirmed Expanded Disability Status Scale (EDSS) progression occurring after a fixed-study entry baseline is a common measure of disability increase in relapsing-remitting multiple sclerosis (RRMS) studies but may not detect all disability progression events, especially those unrelated to overt relapses. OBJECTIVE: To evaluate possible measures of disability progression unrelated to relapse using EDSS data over ≈5.5 years from the Tysabri® Observational Program (TOP). METHODS: TOP is an ongoing, prospective, open-label study in RRMS patients receiving intravenous 300 mg natalizumab every 4 weeks. Measures of increasing disability were assessed using as a reference either study baseline score or a "roving" system that resets the reference score after ⩾24- or ⩾48-week confirmation of a new score. RESULTS: This analysis included 5562 patients. Approximately 70% more EDSS progression events unrelated to relapse and 50% more EDSS worsening events overall were detected with a roving reference score (cumulative probability: 17.6% and 29.7%, respectively) than with a fixed reference baseline score (cumulative probability: 10.1% and 20.3%, respectively). CONCLUSION: In this long-term observational RRMS dataset, a roving EDSS reference value was more efficient than a study baseline EDSS reference in detecting progression/worsening events unrelated to relapses and thus the transition to secondary progressive disease.

Periodontitis and early mortality among adults treated with hemodialysis: a multinational propensity-matched cohort study.

BACKGROUND: Periodontitis is associated with cardiovascular mortality in the general population and adults with chronic diseases. However, it is unclear whether periodontitis predicts survival in the setting of kidney failure. METHODS: ORAL-D was a propensity matched analysis in 3338 dentate adults with end-stage kidney disease treated in a hemodialysis network in Europe and South America designed to examine the association between periodontitis and all-cause and cardiovascular-related mortality in people on long-term hemodialysis. Participants were matched 1:1 on their propensity score for moderate to severe periodontitis assessed using the World Health Organization Community Periodontal Index. A random-effects Cox proportional hazards model was fitted with shared frailty to account for clustering of mortality risk within countries. RESULTS: Among the 3338 dentate participants, 1355 (40.6%) had moderate to severe periodontitis at baseline. After using propensity score methods to generate a matched cohort of participants with periodontitis similar to those with none or mild periodontal disease, moderate to severe periodontitis was associated with a lower risk of all-cause (9.1 versus 13.0 per 100 person years, hazard ratio 0.74, 95% confidence interval 0.61 to 0.90) and cardiovascular (4.3 versus 6.9 per 100 person years, hazard ratio 0.67, 0.51 to 0.88) mortality. These associations were not changed substantially when participants were limited to those with 12 or more natural teeth and when accounting for competing causes of cardiovascular death. CONCLUSION: In contrast to the general population, periodontitis does not appear to be associated with an increased risk of early death in adults treated with hemodialysis.

Patterns of oral disease in adults with chronic kidney disease treated with hemodialysis.

BACKGROUND: Oral disease is a potentially treatable determinant of mortality and quality of life. No comprehensive multinational study to quantify oral disease burden and to identify candidate preventative strategies has been performed in the dialysis setting. METHODS: The ORAL disease in hemoDialysis (ORALD) study was a prospective study in adults treated with hemodialysis in Europe (France, Hungary, Italy, Poland, Portugal and Spain) and Argentina. Oral disease was assessed using standardized WHO methods. Participants self-reported oral health practices and symptoms. Sociodemographic and clinical factors associated with oral diseases were determined and assessed within nation states. RESULTS: Of 4726 eligible adults, 4205 (88.9%) participated. Overall, 20.6% were edentulous [95% confidence interval (CI), 19.4-21.8]. Participants had on average 22 (95% CI 21.7-22.2) decayed, missing or filled teeth, while moderate to severe periodontitis affected 40.6% (95% CI 38.9-42.3). Oral disease patterns varied markedly across countries, independent of participant demographics, comorbidity and health practices. Participants in Spain, Poland, Italy and Hungary had the highest mean adjusted odds of edentulousness (2.31, 1.90, 1.90 and 1.54, respectively), while those in Poland, Hungary, Spain and Argentina had the highest odds of ≥14 decayed, missing or filled teeth (23.2, 12.5, 8.14 and 5.23, respectively). Compared with Argentina, adjusted odds ratios for periodontitis were 58.8, 58.3, 27.7, 12.1 and 6.30 for Portugal, Italy, Hungary, France and Poland, respectively. National levels of tobacco consumption, diabetes and child poverty were associated with edentulousness within countries. CONCLUSIONS: Oral disease in adults on hemodialysis is very common, frequently severe and highly variable among countries, with much of the variability unexplained by participant characteristics or healthcare. Given the national variation and high burden of disease, strategies to improve oral health in hemodialysis patients will require implementation at a country level rather than at the level of individuals.

The Multidimensional Prognostic Index predicts in-hospital length of stay in older patients: a multicentre prospective study.

BACKGROUND: prediction of length of stay (LOS) may be useful to optimise care plans to reduce the negative outcomes related to hospitalisation. OBJECTIVE: to evaluate whether the Multidimensional Prognostic Index (MPI), based on a Comprehensive Geriatric Assessment (CGA), may predict LOS in hospitalised older patients. DESIGN: prospective multicentre cohort study. SETTING: twenty Geriatrics Units. PARTICIPANTS: patients aged 65 and older consecutively admitted to Geriatrics Units. MEASUREMENT: at admission, the CGA-based MPI was calculated by using a validated algorithm that included information on basal and instrumental activities of daily living, cognitive status, nutritional status, the risk of pressures sores, co-morbidity, number of drugs and co-habitation status. According to validated cut-offs, subjects were divided into three groups of risk, i.e. MPI-1 low risk (value ≤0.33), MPI-2 moderate risk (value 0.34-0.66) and MPI-3 severe risk of mortality (value ≥0.67). RESULTS: two thousand and thirty-three patients were included; 1,159 were women (57.0%). Age- and sex-adjusted mean LOS in patients divided according to the MPI grade was MPI-1 = 10.1 (95% CI 8.6-11.8), MPI-2 = 12.47 (95% CI 10.7-14.68) and MPI-3 = 13.41 (95% CI 11.5-15.7) days (P for trend <0.001). The overall accuracy of the MPI to predict LOS was good (C-statistic 0.74, 95% CI 0.72-0.76). Moreover, a statistically significant trend of LOS means was found even in patients stratified according to their International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) main diagnosis. CONCLUSIONS: the MPI is an accurate predictor of LOS in older patients hospitalised with the most frequent diseases.

The long-term effects of stillbirth on women with and without gestational diabetes: a population-based cohort study.

AIMS/HYPOTHESIS: The aim of this study was to estimate the incidence of type 2 diabetes (primary objective) and hospitalisation for cardiovascular events (secondary objective) in women with previous gestational diabetes mellitus (GDM) and in those with normal glucose tolerance (NGT) in pregnancy, and to evaluate the role of stillbirth in differentiating the risks. METHODS: This was a population-based cohort study using administrative data and involving 12 local health authorities. Women with GDM (n = 3,851) during the index period from 2002 to 2010 were propensity matched with women with NGT (n = 11,553). Information was collected on type 2 diabetes development and hospitalisation for cardiovascular events. RESULTS: During a median follow-up of 5.4 years, the incidence rate per 1,000 person-years of type 2 diabetes was 2.1 (95% CI 1.8, 2.5) in women without GDM and 54.0 (95% CI 50.2, 58.0) among women with GDM and pregnancy at term (incidence rate ratio [IRR] 26.9; 95% CI 22.1, 32.7 compared with NGT and pregnancy at term). A history of stillbirth increased the risk of type 2 diabetes development by about twofold, irrespective of GDM status. No significant interaction between stillbirth and GDM on type 2 diabetes risk was found. GDM was associated with a significantly higher risk of cardiovascular events compared with NGT (IRR 2.4; 95% CI 1.5, 3.8). CONCLUSIONS/INTERPRETATION: Pregnancy complicated by GDM and ending in stillbirth represents an important contributory factor in determining type 2 diabetes development. Women with GDM are at a high risk of future cardiovascular events. Women with pregnancy complicated by GDM and stillbirth deserve careful follow-up.

Liverpool Care Pathway for patients with cancer in hospital: a cluster randomised trial.

BACKGROUND: The quality of care provided to patients with cancer who are dying in hospital and their families is suboptimum. The UK Liverpool Care Pathway (LCP) for patients who are dying was developed with the aim of transferring the best practice of hospices to hospitals. We therefore assessed the effectiveness of LCP in the Italian context (LCP-I) in improving the quality of end-of-life care for patients with cancer in hospitals and for their family. METHODS: In this pragmatic cluster randomised trial, 16 Italian general medicine hospital wards were randomly assigned to implement the LCP-I programme or standard health-care practice. For each ward, we identified all patients who died from cancer in the 3 months before randomisation (preintervention) and in the 6 months after the completion of the LCP-I training programme. The primary endpoint was the overall quality of care toolkit scale. Analysis was by intention to treat. This study is registered with ClinicalTrials.gov, number NCT01081899. FINDINGS: During the postintervention assessment, data were gathered for 308 patients who died from cancer (147 in LCP-I programme wards and 161 in control wards). 232 (75%) of 308 family members were interviewed, 119 (81%) of 147 with relatives cared for in the LCP-I wards (mean cluster size 14·9 [range eight to 22]) and 113 (70%) of 161 in the control wards (14·1 [eight to 22]). After implementation of the LCP-I programme, no significant difference was noted in the distribution of the overall quality of care toolkit scores between the wards in which the LCP-I programme was implemented and the control wards (score 70·5 of 100 vs 63·0 of 100; cluster-adjusted mean difference 7·6 [95% CI -3·6 to 18·7]; p=0·186). INTERPRETATION: The effect of the LCP-I programme in our study is less than the effects noted in earlier phase 2 trials. However, if the programme is implemented well it has the potential to reduce the gap in quality of care between hospices and hospitals. Further research is needed to ascertain what components of the LCP-I programme might be effective and to develop and assess a wider range of approaches to quality improvement in hospital care for people at the end of their lives and for their families. FUNDING: Italian Ministry of Health and Maruzza Lefebvre D'Ovidio Foundation-Onlus.

Dental Health and Mortality in People With End-Stage Kidney Disease Treated With Hemodialysis: A Multinational Cohort Study.

BACKGROUND: Dental disease is more extensive in adults with chronic kidney disease, but whether dental health and behaviors are associated with survival in the setting of hemodialysis is unknown. STUDY DESIGN: Prospective multinational cohort. SETTING & PARTICIPANTS: 4,205 adults treated with long-term hemodialysis, 2010 to 2012 (Oral Diseases in Hemodialysis [ORAL-D] Study). PREDICTORS: Dental health as assessed by a standardized dental examination using World Health Organization guidelines and personal oral care, including edentulousness; decayed, missing, and filled teeth index; teeth brushing and flossing; and dental health consultation. OUTCOMES: All-cause and cardiovascular mortality at 12 months after dental assessment. MEASUREMENTS: Multivariable-adjusted Cox proportional hazards regression models fitted with shared frailty to account for clustering of mortality risk within countries. RESULTS: During a mean follow-up of 22.1 months, 942 deaths occurred, including 477 cardiovascular deaths. Edentulousness (adjusted HR, 1.29; 95% CI, 1.10-1.51) and decayed, missing, or filled teeth score ≥ 14 (adjusted HR, 1.70; 95% CI, 1.33-2.17) were associated with early all-cause mortality, while dental flossing, using mouthwash, brushing teeth daily, spending at least 2 minutes on oral hygiene daily, changing a toothbrush at least every 3 months, and visiting a dentist within the past 6 months (adjusted HRs of 0.52 [95% CI, 0.32-0.85], 0.79 [95% CI, 0.64-0.97], 0.76 [95% CI, 0.58-0.99], 0.84 [95% CI, 0.71-0.99], 0.79 [95% CI, 0.65-0.95], and 0.79 [95% CI, 0.65-0.96], respectively) were associated with better survival. Results for cardiovascular mortality were similar. LIMITATIONS: Convenience sample of clinics. CONCLUSIONS: In adults treated with hemodialysis, poorer dental health was associated with early death, whereas preventive dental health practices were associated with longer survival.

Nuclear receptors expression chart in peripheral blood mononuclear cells identifies patients with Metabolic Syndrome.

BACKGROUND: Nuclear receptors are a class of 48 ligand-activated transcription factors identified as key players of metabolic and developmental processes. Most of these receptors are potential targets for pharmacological strategies in the Metabolic Syndrome. In the present study, we analyzed changes in the mRNA expression of nuclear receptors in the peripheral blood mononuclear cells of patients with Metabolic Syndrome, in order to identify novel biomarkers of disease and candidate targets for putative therapeutical approaches. METHODS AND RESULTS: We enrolled thirty healthy controls (14 M:16 F) and thirty naïve patients (16 M: 14 F; >3 criteria for Metabolic Syndrome upon Adult Treatment Panel III) without organ damage. Using quantitative real-time PCR, we assessed the expression patterns of nuclear receptors in peripheral blood mononuclear cells. 33/48 nuclear receptors were expressed in peripheral blood mononuclear cells. In patients with Metabolic Syndrome, we found a significant down-regulation of the entire PPAR, NR4A and RAR families, together with a repression of RXRα, VDR, and Rev-Erbα. Furthermore, we performed a novel statistical analysis with classification trees, which allowed us to depict a predictive core of nuclear receptor expression patterns characterizing subjects with Metabolic Syndrome. Random Forest Analysis identified NOR1 and PPARδ, which were both reduced in peripheral blood mononuclear cells and specifically in CD14(+) cells (mostly monocytes), as classifiers of Metabolic Syndrome, with high specificity and sensitivity. CONCLUSIONS: Our results point to the use of PPAR and NR4A mRNA levels in the overall peripheral blood mononuclear cells as biomarkers of Metabolic Syndrome and bona fide putative targets of pharmacological therapy.

Evaluation of microRNA-10b prognostic significance in a prospective cohort of breast cancer patients.

BACKGROUND: MicroRNA-10b (miR-10b) has a prominent role in regulating tumor invasion and metastasis by targeting the HOXD10 transcriptional repressor and has been found up-regulated in several tumor types. METHODS: We evaluated the expression of miR-10b in paired tumor and normal specimens obtained from a prospective cohort of breast cancer patients with at least 36 months follow-up enrolled according to the REMARK guidelines (n = 150). RNA quality was measured and only samples with RNA Integrity Number (RIN) ≥7.0 were analyzed. RESULTS: The relative expression of miR-10b in tumor as compared to its normal counterpart (RER) was determined by RT-qPCR. miR-10b RERs were higher in the subgroup of patients with synchronous metastases (n = 11, Median 0.25; IQR 0.11-1.02) as compared with patients without metastases (n = 90, Median 0.09; IQR 0.04-0.29) (p = 0.028). In the subgroup of patients without synchronous metastases (n = 90), higher miR-10b RERs were associated with increased risk of disease progression and death in both univariable (HR 1.16, p = 0.021 and HR 1.20, p = 0.015 respectively for 0.10 unitary increase of miR-10b RERs levels) and multivariable (HR1.30, p < 0.001, and HR 1.31, p = 0.003 respectively for 0.10 unitary increase of miR-10b RERs levels) Cox regression models. The addition of miR-10b RERs to the Nottingham Prognostic Index (NPI) provided an improvement in discrimination power and risk reclassification abilities for the clinical outcomes at 36 months. Survival C-indices significantly increased from 0.849 to 0.889 (p = 0.009) for OS and from 0.735 to 0.767 (p = 0.050) for DFS. CONCLUSIONS: Our results provide evidences that the addition of miR-10b RERs to the prognostic factors used in clinical routine could improve the prediction abilities for both overall mortality and disease progression in breast cancer patients.

Modeling interactions between Human Equilibrative Nucleoside Transporter-1 and other factors involved in the response to gemcitabine treatment to predict clinical outcomes in pancreatic ductal adenocarcinoma patients.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy, characterized by largely unsatisfactory responses to the currently available therapeutic strategies. In this study we evaluated the expression of genes involved in gemcitabine uptake in a selected cohort of patients with PDAC, with well-defined clinical-pathological features. METHODS: mRNA levels of hENT1, CHOP, MRP1 and DCK were evaluated by means of qRT-PCR in matched pairs of tumor and adjacent normal tissue samples collected from PDAC patients treated with gemcitabine after surgical tumor resection. To detect possible interaction between gene expression levels and to identify subgroups of patients at different mortality/progression risk, the RECursive Partitioning and Amalgamation (RECPAM) method was used. RESULTS: RECPAM analysis showed that DCK and CHOP were most relevant variables for the identification of patients with different mortality risk, while hENT1 and CHOP were able to identify subgroups of patients with different disease progression risk. CONCLUSION: hENT1, CHOP, MRP1 and DCK appear correlated to PDAC, and this interaction might influence disease behavior.

Immunosuppression for acquired hemophilia A: results from the European Acquired Haemophilia Registry (EACH2).

Acquired hemophilia A (AHA) is an autoimmune disease caused by an autoantibody to factor VIII. Patients are at risk of severe and fatal hemorrhage until the inhibitor is eradicated, and guidelines recommend immunosuppression as soon as the diagnosis has been made. The optimal immunosuppressive regimen is unclear; therefore, data from 331 patients entered into the prospective EACH2 registry were analyzed. Steroids combined with cyclophosphamide resulted in more stable complete remission (70%), defined as inhibitor undetectable, factor VIII more than 70 IU/dL and immunosuppression stopped, than steroids alone (48%) or rituximab-based regimens (59%). Propensity score-matched analysis controlling for age, sex, factor VIII level, inhibitor titer, and underlying etiology confirmed that stable remission was more likely with steroids and cyclophosphamide than steroids alone (odds ratio = 3.25; 95% CI, 1.51-6.96; P < .003). The median time to complete remission was approximately 5 weeks for steroids with or without cyclophosphamide; rituximab-based regimens required approximately twice as long. Immunoglobulin administration did not improve outcome. Second-line therapy was successful in approximately 60% of cases that failed first-line therapy. Outcome was not affected by the choice of first-line therapy. The likelihood of achieving stable remission was not affected by underlying etiology but was influenced by the presenting inhibitor titer and FVIII level.