Defining responders to therapies by a statistical modeling approach applied to randomized clinical trial data

Background: Personalized medicine is the tailoring of treatment to the individual characteristics of patients. Once a treatment has been tested in a clinical trial and its effect overall quantified, it would be of great value to be able to use the baseline patients' characteristics to identify patients with larger/lower benefits from treatment, for a more personalized approach to therapy. Methods: We show here a previously published statistical method, aimed at identifying patients' profiles associated to larger treatment benefits applied to three identical randomized clinical trials in multiple sclerosis, testing laquinimod vs placebo (ALLEGRO, BRAVO, and CONCERTO). We identified on the ALLEGRO patients' specific linear combinations of baseline variables, predicting heterogeneous response to treatment on disability progression. We choose the best score on the BRAVO, based on its ability to identify responders to treatment in this dataset. We finally got an external validation on the CONCERTO, testing on this new dataset the performance of the score in defining responders and non-responders. Results: The best response score defined on the ALLEGRO and the BRAVO was a linear combination of age, sex, previous relapses, brain volume, and MRI lesion activity. Splitting patients into responders and non-responders according to the score distribution, in the ALLEGRO, the hazard ratio (HR) for disability progression of laquinimod vs placebo was 0.38 for responders, HR = 1.31 for non-responders (interaction p = 0.0007). In the BRAVO, we had similar results: HR = 0.40 for responders and HR = 1.24 for non-responders (interaction p = 0.006). These findings were successfully replicated in the CONCERTO study, with HR = 0.44 for responders and HR=1.08 for non-responders (interaction p = 0.033). Conclusions: This study demonstrates the possibility to refine and personalize the treatment effect estimated in randomized studies by using the baseline demographic and clinical characteristics of the included patients. The method can be applied to any randomized trial in any medical condition to create a treatment-specific score associated to different levels of response to the treatment tested in the trial. This is an easy and affordable method toward therapy personalization, indicating patient profiles related to a larger benefit from a specific drug, which may have implications for taking clinical decisions in everyday clinical practice

Comparative utility of disability progression measures in PPMS: Analysis of the PROMiSe data set.

OBJECTIVE: To assess the comparative utility of disability progression measures in primary progressive MS (PPMS) using the PROMiSe trial data set. METHODS: Data for patients randomized to placebo (n = 316) in the PROMiSe trial were included in this analysis. Disability was assessed using change in single (Expanded Disability Status Scale [EDSS], timed 25-foot walk [T25FW], and 9-hole peg test [9HPT]) and composite disability measures (EDSS/T25FW, EDSS/9HPT, and EDSS/T25FW/9HPT). Cumulative and cross-sectional unconfirmed disability progression (UDP) and confirmed disability progression (CDP; sustained for 3 months) rates were assessed at 12 and 24 months. RESULTS: CDP rates defined by a ≥20% increase in T25FW were higher than those defined by EDSS score at 12 and 24 months. CDP rates defined by T25FW or EDSS score were higher than those defined by 9HPT score. The 3-part composite measure was associated with more CDP events (41.4% and 63.9% of patients at 12 and 24 months, respectively) than the 2-part measure (EDSS/T25FW [38.5% and 59.5%, respectively]) and any single measure. Cumulative UDP and CDP rates were higher than cross-sectional rates. CONCLUSIONS: The T25FW or composite measures of disability may be more sensitive to disability progression in patients with PPMS and should be considered as the primary endpoint for future studies of new therapies. CDP may be the preferred measure in classic randomized controlled trials in which cumulative disability progression rates are evaluated; UDP may be feasible for cross-sectional studies.This study was funded by Teva Pharmaceutical Industries

A randomized, placebo-controlled phase 2 trial of laquinimod in primary progressive multiple sclerosis

OBJECTIVE: To evaluate efficacy, safety, and tolerability of laquinimod in patients with primary progressive multiple sclerosis (PPMS). METHODS: In the randomized, double-blind, placebo-controlled, phase 2 study ARPEGGIO (A Randomized Placebo-controlled trial Evaluating laquinimod in PPMS, Gauging Gradations In MRI and clinical Outcomes), eligible PPMS patients were randomized 1:1:1 to receive once-daily oral laquinimod 0.6 mg or 1.5 mg or matching placebo. Percentage brain volume change (PBVC; primary endpoint) from baseline to week 48 was assessed by MRI. Secondary and exploratory endpoints included clinical and MRI measures. Efficacy endpoints were evaluated using a predefined, hierarchical statistical testing procedure. Safety was monitored throughout the study. The laquinimod 1.5 mg dose arm was discontinued on January 1, 2016 due to findings of cardiovascular events. RESULTS: 374 patients were randomized to laquinimod 0.6 mg (n = 139) or 1.5 mg (n = 95) or placebo (n = 140). ARPEGGIO did not meet the primary endpoint of significant treatment effect with laquinimod 0.6 mg versus placebo on PBVC from baseline to week 48 (adjusted mean difference = 0.016%, p = 0.903). Laquinimod 0.6 mg reduced the number of new T2 brain lesions at week 48 (risk ratio = 0.4; 95% confidence interval, 0.26-0.69; p = 0.001). Incidence of adverse events was higher among patients treated with laquinimod 0.6 mg (83%) versus laquinimod 1.5 mg (66%) and placebo (78%). CONCLUSIONS: Laquinimod 0.6 mg did not demonstrate a statistically significant effect on brain volume loss in PPMS at week 48

S100A7, a Novel Alzheimer's Disease Biomarker with Non-Amyloidogenic α-Secretase Activity Acts via Selective Promotion of ADAM-10

Alzheimer's disease (AD) is the most common cause of dementia among older people. At present, there is no cure for the disease and as of now there are no early diagnostic tests for AD. There is an urgency to develop a novel promising biomarker for early diagnosis of AD. Using surface-enhanced laser desorption ionization-mass spectrometry SELDI-(MS) proteomic technology, we identified and purified a novel 11.7-kDa metal- binding protein biomarker whose content is increased in the cerebrospinal fluid (CSF) and in the brain of AD dementia subjects as a function of clinical dementia. Following purification and protein-sequence analysis, we identified and classified this biomarker as S100A7, a protein known to be involved in immune responses. Using an adenoviral-S100A7 expression system, we continued to examine the potential role of S100A7 in AD amyloid neuropathology in in vitro model of AD. We found that the expression of exogenous S100A7 in primary cortico-hippocampal neuron cultures derived from Tg2576 transgenic embryos inhibits the generation of β-amyloid (Aβ)1–42 and Aβ1–40 peptides, coincidental with a selective promotion of “non- amyloidogenic” α-secretase activity via promotion of ADAM (a disintegrin and metalloproteinase)-10. Finally, a selective expression of human S100A7 in the brain of transgenic mice results in significant promotion of α-secretase activity. Our study for the first time suggests that S100A7 may be a novel biomarker of AD dementia and supports the hypothesis that promotion of S100A7 expression in the brain may selectively promote α-secretase activity in the brain of AD precluding the generation of amyloidogenic peptides. If in the future we find that S1000A7 protein content in CSF is sensitive to drug intervention experimentally and eventually in the clinical setting, S100A7 might be developed as novel surrogate index (biomarker) of therapeutic efficacy in the characterization of novel drug agents for the treatment of AD

RNA Oxidation Adducts 8-OHG and 8-OHA Change with Aβ42 Levels in Late-Stage Alzheimer's Disease

While research supports amyloid-β (Aβ) as the etiologic agent of Alzheimer's disease (AD), the mechanism of action remains unclear. Evidence indicates that adducts of RNA caused by oxidation also represent an early phenomenon in AD. It is currently unknown what type of influence these two observations have on each other, if any. We quantified five RNA adducts by gas chromatography/mass spectroscopy across five brain regions from AD cases and age-matched controls. We then used a reductive directed analysis to compare the RNA adducts to common indices of AD neuropathology and various pools of Aβ. Using data from four disease-affected brain regions (Brodmann's Area 9, hippocampus, inferior parietal lobule, and the superior and middle temporal gyri), we found that the RNA adduct 8-hydroxyguanine (8-OHG) decreased, while 8-hydroxyadenine (8-OHA) increased in AD. The cerebellum, which is generally spared in AD, did not show disease related changes, and no RNA adducts correlated with the number of plaques or tangles. Multiple regression analysis revealed that SDS-soluble Aβ42 was the best predictor of changes in 8-OHG, while formic acid-soluble Aβ42 was the best predictor of changes in 8-OHA. This study indicates that although there is a connection between AD related neuropathology and RNA oxidation, this relationship is not straightforward