1,721,164 research outputs found
The Chilean Spanish version of the Juvenile Arthritis Multidimensional Assessment Report (JAMAR)
No full textThe Juvenile Arthritis Multidimensional Assessment Report (JAMAR) is a new parent/patient reported outcome measure that enables a thorough assessment of the disease status in children with juvenile idiopathic arthritis (JIA). We report the results of the cross-cultural adaptation and validation of the parent and patient versions of the JAMAR in the Chilean Spanish language. The reading comprehension of the questionnaire was tested in ten JIA parents and patients. Each participating centre was asked to collect demographic, clinical data and the JAMAR in 100 consecutive JIA patients or all consecutive patients seen in a 6-month period and to administer the JAMAR to 100 healthy children and their parents. The statistical validation phase explored descriptive statistics and the psychometric issues of the JAMAR: the three Likert assumptions, floor/ceiling effects, internal consistency, Cronbach’s alpha, interscale correlations, and construct validity (convergent and discriminant validity). A total of 49 JIA patients (12.2% systemic, 24.5% oligoarticular, 22.5% RF-negative polyarthritis, 40.8% other categories) and 70 healthy children, were enrolled. The JAMAR components discriminated well healthy subjects from JIA patients. All JAMAR components revealed good psychometric performances. In conclusion, the Chilean Spanish version of the JAMAR is a valid tool for the assessment of children with JIA and is suitable for use both in routine clinical practice and clinical research
Creating an automated tool for a consistent and repeatable evaluation of disability progression in clinical studies for multiple sclerosis
No full textBackground: The lack of standardized disability progression evaluation in multiple sclerosis (MS) hinders reproducibility of clinical study results, due to heterogeneous and poorly reported criteria.Objective: To demonstrate the impact of using different parameters when evaluating MS progression, and to introduce an automated tool for reproducible outcome computation.Methods: Re-analyzing BRAVO clinical trial data (NCT00605215), we examined the fluctuations in computed treatment effect on confirmed disability progression (CDP) and progression independent of relapse activity (PIRA) when varying different parameters. These analyses were conducted using the msprog package for R, which we developed as a tool for CDP assessment from longitudinal data, given a set of criteria that can be specified by the user.Results: The BRAVO study reported a hazard ratio (HR) of 0.69 (95% confidence interval (CI): 0.46-1.02) for CDP. Using the different parameter configurations, the resulting treatment effect on CDP varied considerably, with HRs ranging from 0.59 (95% CI: 0.41-0.86) to 0.72 (95% CI: 0.48-1.07). The treatment effect on PIRA varied from an HR = 0.62 (95% CI: 0.41-0.93) to an HR = 0.65 (95% CI: 0.40-1.04).Conclusions: The adoption of an open-access tool validated by the research community, with clear parameter specification and standardized output, could greatly reduce heterogeneity in CDP estimation and promote repeatability of study results
Algorithm vs. clinical experience: controlled ovarian stimulations with follitropin-delta and individualised doses of follitropin-alpha/beta
No full textIn the registrational trials, follitropin delta was compared with a fixed dose of 150 UI of follitropin alpha/beta, finding higher chances to reach a target response of 8-14 oocytes compared to controls. For this reason, follitropin delta is marketed as particularly useful in expected hyper-responder patients. The main outcome of this study is to report if comparable results are reached in a real-life scenario with follitropin alpha/beta personalized doses, based on patients' characteristics. This is a retrospective study performed in two public fertility centres. All first cycles from January 2020 to June 2022 with either follitropin delta (cases) or alpha/beta (controls) in patients with antiMüllerian hormone >2.5 ng/ml were compared by an inverse probability weighting approach based on propensity score. The follitropin total dose was higher in controls (1179.06 ± 344.93 vs. 1668.67 ± 555.22 IU, p<0.001). The target response of 8-14 oocytes was reached by 40.2% of cases and 40.7% of controls (odds ratio (OR) 0.99, 95% confidence interval (CI) 0.65-1.53, p=0.98). Fewer than 8 oocytes were collected in 24.1% of cases and 22% of controls (OR 1.10, 95% CI 0.71-1.69, p=0.67); more than 14 oocytes in 35.7% of cases and 37.3% of controls (OR 0.83, 95% CI 0.54-1.28, p=0.40). Our experience did not find worse results in term of proportion of patients who reached the target response with an algorithm-chosen dose of follitropin delta compared to a personalised starting dose of follitropin alpha/beta, with follitropin delta having the advantage of objectivity. Larger numbers are needed to confirm these results
Therapeutic lag: Is treatment effect delayed in progressive MS?
No full textBackground: Randomized clinical trials (RCTs) in progressive multiple sclerosis (MS) often revealed non-significant treatment effects on disability progression. Objectives: To investigate whether the failure to detect a significant benefit from treatment may be motivated by a delay in treatment effect, possibly related to baseline characteristics. Methods: We re-analyzed data from two RCTs testing interferon-beta and glatiramer-acetate versus placebo in progressive MS with no significant effect on EDSS progression. We first designed a time-dependent Cox model with no treatment effect up to time = t0, and constant hazard ratio (HR) after time = t0. We selected the best-fitting t0 from 0 (standard Cox model) to 2.5 years. Furthermore, we modeled the delay as a function of baseline EDSS and fitted the resulting Cox model to the merged dataset. Results: The time-dependent Cox model revealed a significant benefit of treatment delayed by t0 = 2.5 years for the SPECTRIMS study (HR = 0.65 (0.43-0.98), p = 0.041), and delayed by t0 = 2 years for the PROMISE study (HR = 0.65, (0.42-0.99), p = 0.044). In the merged dataset, the HR for the EDSS-dependent delayed effect was 0.68 (0.56, 0.82), p < 0.001. Conclusion: The assumption of a delayed treatment effect improved the fit to the data of the two examined RCTs, uncovering a significant, although shifted, benefit of treatment
Validating the use of brain volume cutoffs to identify clinically relevant atrophy in RRMS
No full textBackground: Baseline brain volume (BV) is predictive at a group level but is difficult to interpret at the single patient level. Objective: To validate BV cutoffs able to identify clinically relevant atrophy in relapsing–remitting multiple sclerosis (RRMS) patients. Methods: The expected normalized brain volume (NBV) for each patient was calculated using RRMS patients from two phase III clinical trials, applying a linear formula developed on the baseline variable of an independent data set. The difference between these expected NBV values and those actually observed was calculated and used to categorize the patients in the low-NBV, medium-NBV, and high-NBV groups. Results: The 2-year probability of 3-month confirmed disability worsening was significantly associated with the NBV categorization (p = 0.006), after adjusting for treatment effect. Taking the high-NBV group as a reference, the hazard ratios for the medium-NBV and low-NBV groups were 1.22 (95% confidence interval (CI): 0.85–1.76, p = 0.27) and 1.69 (95% CI: 1.11–2.57, p = 0.01), respectively. Conclusion: This study validates the use of BV cutoffs to identify clinically relevant atrophy in RRMS study by showing that the three groups classified according to the baseline NBV adjusted for the other prognostic variables have a significant prognostic impact on the risk of disability progression
Long-term impact of interferon or Glatiramer acetate in multiple sclerosis: A systematic review and meta-analysis
No full textIn recent years the impact of disease-modifying drugs on long-term progression in multiple sclerosis (MS) was assessed both in observational studies and in extension of randomized controlled trial (RCT). Aim of this work was to quantitatively summarize by a meta-analysis the long-term impact of immunomodulatory drugs (Interferon-Beta (IFN-β) or Glatiramer Acetate (GA)) in relapsing-remitting (RR) MS patients. Methods We collected all published observational studies reporting the long-term efficacy of IFN-β or GA in RRMS patients. The primary outcome was the treatment effect on progression to a sustained EDSS score of 6 or to the Secondary Progressive (SP) phase. A non-parametric approach was adopted to test the overall treatment effect significance, while a random effect model was used to obtain a pooled quantitative estimate of the treatment benefit, in terms of hazard-ratios (HR) or Relative Risks, with their 95% confidence interval (CI). Results Fourteen studies, on a total of 13,238 RRMS patients, were included in the meta-analysis. All studies but two reported a consistent effect of immunomodulatory treatment on long-term disease progression; the pooled effect on progression to EDSS 6 or SP was significant (p<0.01) when tested by the non-parametric test. The quantitative estimate of the treatment effect in reducing progression to EDSS 6 in the subset of studies reporting this outcome was HRpooled=0.49 (95% CI: 0.34-0.69), p<0.001. Conclusions Treatment with immunomodulators seems to reduce long-term probability of disability progression. Additional well-designed observational studies could help to confirm these findings
Reinterpreting Clinical Trials in Children With Multiple Sclerosis Using a Bayesian Approach
No full textPersonalized Treatment Response in Progressive MS: Can the Patient's Profile Influence the Outcome?
No full textBackground: Evidence from clinical trials providing average effects in populations is often used to forecast individualized patient outcomes similar to the trial patients. Multiple sclerosis (MS), known for notable heterogeneity in outcomes, makes the evaluation of potential heterogeneity of treatment effect (HTE) significant. Identifying factors that predict individual treatment response is crucial for optimizing patient care, and this study aimed to demonstrate the feasibility (proof of concept) of applying a statistical method to predict individual treatment response in MS trials. Methods: We developed an individualized response score (RS) to predict treatment response in patients with active secondary progressive MS (SPMS). The RS was a continuous combination of baseline clinical characteristics, including age, sex, previous relapses, EDSS, and disease duration. We used data from the EXPAND trial to train and validate the RS. A training dataset (70% of the data) was used to identify optimal response thresholds for four key outcomes: Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk (T25FW), 9-Hole Peg Test (9HP), and the Symbol Digit Modalities Test (SDMT). The remaining 30% of the data served as a validation set to assess the RS's predictive performance. The continuous RS was binarized (into responder and non-responder) based on the threshold representing the top 25% versus the bottom 75% of the continuous score distribution. Results: Using baseline profiles, SPMS patients exhibiting varying benefits from Siponimod across different outcomes were successfully categorized as responders or non-responders. The overall effect of Siponimod on the EDSS was HR = 0.79 (95% CI: 0.65-0.95), while responders’ demonstrated a HR = 0.64 (95% CI: 0.49-0.84) versus a HR = 0.97 (95% CI: 0.74-1.27) for non-responders’, interaction p = 0.027. Siponimod's overall effect on SDMT progression was HR = 0.75 (95% CI: 0.63-0.88). Responders' demonstrated a HR = 0.59 (95% CI: 0.43-0.80) vs a HR = 1.00 (95% CI: 0.69-1.44) for non-responders, interaction p = 0.031. On the entire dataset, Siponimod exhibited a non-significant effect on 9HPT (HR = 0.86, 95% CI: 0.66-1.10) and on T25FW (HR = 0.95, 95% CI: 0.81-1.12), whereas responders’ demonstrated a HR = 0.68 (95% CI: 0.47-0.97) on 9HPT and a HR = 0.77 (95% CI: 0.60-0.98) for T25FW. Conclusions: This analysis demonstrated the ability to define responders to a therapy based on their baseline profile and evaluate the treatment effect on multiple endpoints, showing that the benefit on different outcomes can vary across patients
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