Two Phase 3 Trials of Gantenerumab in Early Alzheimer's Disease.

BACKGROUND: Monoclonal antibodies that target amyloid-beta (Aß) have the potential to slow cognitive and functional decline in persons with early Alzheimer's disease. Gantenerumab is a subcutaneously administered, fully human, anti-Aß IgG1 monoclonal antibody with highest affinity for aggregated Aß that has been tested for the treatment of Alzheimer's disease. METHODS: We conducted two phase 3 trials (GRADUATE I and II) involving participants 50 to 90 years of age with mild cognitive impairment or mild dementia due to Alzheimer's disease and evidence of amyloid plaques on positron-emission tomography (PET) or cerebrospinal fluid (CSF) testing. Participants were randomly assigned to receive gantenerumab or placebo every 2 weeks. The primary outcome was the change from baseline in the score on the Clinical Dementia Rating scale-Sum of Boxes (CDR-SB; range, 0 to 18, with higher scores indicating greater cognitive impairment) at week 116. RESULTS: A total of 985 and 980 participants were enrolled in the GRADUATE I and II trials, respectively. The baseline CDR-SB score was 3.7 in the GRADUATE I trial and 3.6 in the GRADUATE II trial. The change from baseline in the CDR-SB score at week 116 was 3.35 with gantenerumab and 3.65 with placebo in the GRADUATE I trial (difference, -0.31; 95% confidence interval [CI], -0.66 to 0.05; P = 0.10) and was 2.82 with gantenerumab and 3.01 with placebo in the GRADUATE II trial (difference, -0.19; 95% CI, -0.55 to 0.17; P = 0.30). At week 116, the difference in the amyloid level on PET between the gantenerumab group and the placebo group was -66.44 and -56.46 centiloids in the GRADUATE I and II trials, respectively, and amyloid-negative status was attained in 28.0% and 26.8% of the participants receiving gantenerumab in the two trials. Across both trials, participants receiving gantenerumab had lower CSF levels of phosphorylated tau 181 and higher levels of Aß42 than those receiving placebo; the accumulation of aggregated tau on PET was similar in the two groups. Amyloid-related imaging abnormalities with edema (ARIA-E) occurred in 24.9% of the participants receiving gantenerumab, and symptomatic ARIA-E occurred in 5.0%. CONCLUSIONS: Among persons with early Alzheimer's disease, the use of gantenerumab led to a lower amyloid plaque burden than placebo at 116 weeks but was not associated with slower clinical decline. (Funded by F. Hoffmann-La Roche; GRADUATE I and II ClinicalTrials.gov numbers, NCT03444870 and NCT03443973, respectively.).

Care partner-informed meaningful change thresholds for the Clinical Dementia Rating-Sum of Boxes for trials of early Alzheimer's disease.

INTRODUCTION: Consensus definitions of meaningful within-patient change (MWPC) on the Clinical Dementia Rating-Sum of Boxes (CDR-SB) are needed. Existing estimates use clinician-rated anchors in clinically diagnosed Alzheimer's disease (AD) populations. Incorporating the care partner perspective offers important insights, and evaluating biomarker-confirmed cohorts aligns estimates with ongoing trials. METHODS: Anchor-based analyses were conducted to evaluate MWPC on the CDR-SB in early AD (Tauriel; NCT03289143) using Caregiver Global Impression of Change in memory or daily activities. RESULTS: Across time points and anchors, mean CDR-SB changes associated with the "somewhat worse" category ranged from 1.50 to 2.12 in early AD, 1.07 to 2.06 in mild cognitive impairment-AD, and 1.79 to 2.25 in mild AD. DISCUSSION: The proposed ranges are appropriate to define meaningful progression on the CDR-SB in similar cohorts and support the interpretation of treatment benefit through MWPC analyses. Thresholds should be calibrated to the context of use; lower/higher thresholds may be applicable in studies of earlier/later disease over shorter/longer durations. HIGHLIGHTS: Within-patient CDR-SB change thresholds are provided using caregiver-rated anchors. 1.5 to 2.5 points may be an appropriate range in early AD trials of similar durations. Cumulative distribution function plots illustrate the benefit of a given treatment. When selecting thresholds, the target population and study design should be considered.

Statistical considerations when estimating time-saving treatment effects in Alzheimer's disease clinical trials.

INTRODUCTION: Estimating treatment effects as time savings in disease progression may be more easily interpretable than assessing the absolute difference or a percentage reduction. In this study, we investigate the statistical considerations of the existing method for estimating time savings and propose alternative complementary methods. METHODS: We propose five alternative methods to estimate the time savings from different perspectives. These methods are applied to simulated clinical trial data that mimic or modify the Clinical Dementia Rating Sum of Boxes progression trajectories observed in the Clarity AD lecanemab trial. RESULTS: Our study demonstrates that the proposed methods can generate more precise estimates by considering two crucial factors: (1) the absolute difference between treatment arms, and (2) the observed progression rate in the treatment arm. DISCUSSION: Quantifying treatment effects as time savings in disease progression offers distinct advantages. To provide comprehensive estimations, it is important to use various methods. HIGHLIGHTS: We explore the statistical considerations of the current method for estimating time savings. We proposed alternative methods that provide time savings estimations based on the observed absolute differences. By using various methods, a more comprehensive estimation of time savings can be achieved.

Examining amyloid reduction as a surrogate endpoint through latent class analysis using clinical trial data for dominantly inherited Alzheimer's disease.

INTRODUCTION: Increasing evidence suggests that amyloid reduction could serve as a plausible surrogate endpoint for clinical and cognitive efficacy. The double-blind phase 3 DIAN-TU-001 trial tested clinical and cognitive declines with increasing doses of solanezumab or gantenerumab. METHODS: We used latent class (LC) analysis on data from the Dominantly Inherited Alzheimer Network Trials Unit 001 trial to test amyloid positron emission tomography (PET) reduction as a potential surrogate biomarker. RESULTS: LC analysis categorized participants into three classes: amyloid no change, amyloid reduction, and amyloid growth, based on longitudinal amyloid Pittsburgh compound B PET standardized uptake value ratio data. The amyloid-no-change class was at an earlier disease stage for amyloid amounts and dementia. Despite similar baseline characteristics, the amyloid-reduction class exhibited reductions in the annual decline rates compared to the amyloid-growth class across multiple biomarker, clinical, and cognitive outcomes. DISCUSSION: LC analysis indicates that amyloid reduction is associated with improved clinical outcomes and supports its use as a surrogate biomarker in clinical trials. HIGHLIGHTS: We used latent class (LC) analysis to test amyloid reduction as a surrogate biomarker. Despite similar baseline characteristics, the amyloid-reduction class exhibited remarkably better outcomes compared to the amyloid-growth class across multiple measures. LC analysis proves valuable in testing amyloid reduction as a surrogate biomarker in clinical trials lacking significant treatment effects.

Standard and reference-based conditional mean imputation.

Clinical trials with longitudinal outcomes typically include missing data due to missed assessments or structural missingness of outcomes after intercurrent events handled with a hypothetical strategy. Approaches based on Bayesian random multiple imputation and Rubin's rules for pooling results across multiple imputed data sets are increasingly used in order to align the analysis of these trials with the targeted estimand. We propose and justify deterministic conditional mean imputation combined with the jackknife for inference as an alternative approach. The method is applicable to imputations under a missing-at-random assumption as well as for reference-based imputation approaches. In an application and a simulation study, we demonstrate that it provides consistent treatment effect estimates with the Bayesian approach and reliable frequentist inference with accurate standard error estimation and type I error control. A further advantage of the method is that it does not rely on random sampling and is therefore replicable and unaffected by Monte Carlo error.

A model for predicting effect of treatment on progression-free survival using MRD as a surrogate end point in CLL.

Our objective was to evaluate minimal residual disease (MRD) at the end of induction treatment with chemoimmunotherapy as a surrogate end point for progression-free survival (PFS) in chronic lymphocytic leukemia (CLL) based on 3 randomized, phase 3 clinical trials (ClinicalTrials.gov identifiers NCT00281918, NCT00769522, and NCT02053610). MRD was measured in peripheral blood (PB) from treatment-naïve patients in the CLL8, CLL10, and CLL11 clinical trials, and quantified by 4-color flow cytometry or allele-specific oligonucleotide real-time quantitative polymerase chain reaction. A meta-regression model was developed to predict treatment effect on PFS using treatment effect on PB-MRD. PB-MRD levels were measured in 393, 337, and 474 patients from CLL8, CLL10, and CLL11, respectively. The model demonstrated a statistically significant relationship between treatment effect on PB-MRD and treatment effect on PFS. As the difference between treatment arms in PB-MRD response rates increased, a reduction in the risk of progression or death was observed; for each unit increase in the (log) ratio of MRD- rates between arms, the log of the PFS hazard ratio decreased by -0.188 (95% confidence interval, -0.321 to -0.055; P = .008). External model validation on the REACH trial and sensitivity analyses confirm the robustness and applicability of the surrogacy model. Our surrogacy model supports use of PB-MRD as a primary end point in randomized clinical trials of chemoimmunotherapy in CLL. Additional CLL trial data are required to establish a more precise quantitative relationship between MRD and PFS, and to support general applicability of MRD surrogacy for PFS across diverse patient characteristics, treatment regimens, and different treatment mechanisms of action.

Initiation of symptomatic medication in Alzheimer's disease clinical trials: Hypothetical versus treatment policy approach.

In clinical trials in populations with mild cognitive impairment, it is common for participants to initiate concurrent symptomatic medications for Alzheimer's disease after randomization to the experimental therapy. One strategy for addressing this occurrence is to exclude any observations that occur after the concurrent medication is initiated. The rationale for this approach is that these observations might reflect a symptomatic benefit of the concurrent medication that would adversely bias efficacy estimates for an effective experimental therapy. We interrogate the assumptions underlying such an approach by estimating the effect of newly prescribed concurrent medications in an observational study, the Alzheimer's Disease Neuroimaging Initiative.

A novel cognitive disease progression model for clinical trials in autosomal-dominant Alzheimer's disease.

Clinical trial outcomes for Alzheimer's disease are typically analyzed by using the mixed model for repeated measures (MMRM) or similar models that compare an efficacy scale change from baseline between treatment arms with or without participants' disease stage as a covariate. The MMRM focuses on a single-point fixed follow-up duration regardless of the exposure for each participant. In contrast to these typical models, we have developed a novel semiparametric cognitive disease progression model (DPM) for autosomal dominant Alzheimer's disease based on the Dominantly Inherited Alzheimer Network (DIAN) observational study. This model includes 3 novel features, in which the DPM (1) aligns and compares participants by disease stage, (2) uses a proportional treatment effect similar to the concept of the Cox proportional hazard ratio, and (3) incorporates extended follow-up data from participants with different follow-up durations using all data until last participant visit. We present the DPM model developed by using the DIAN observational study data and demonstrate through simulation that the cognitive DPM used in hypothetical intervention clinical trials produces substantial gains in power compared with the MMRM.

Use of a historical control group in a noninferiority trial assessing a new antibacterial treatment: A case study and discussion of practical implementation aspects.

When recruitment into a clinical trial is limited due to rarity of the disease of interest, or when recruitment to the control arm is limited due to ethical reasons (eg, pediatric studies or important unmet medical need), exploiting historical controls to augment the prospectively collected database can be an attractive option. Statistical methods for combining historical data with randomized data, while accounting for the incompatibility between the two, have been recently proposed and remain an active field of research. The current literature is lacking a rigorous comparison between methods but also guidelines about their use in practice. In this paper, we compare the existing methods based on a confirmatory phase III study design exercise done for a new antibacterial therapy with a binary endpoint and a single historical dataset. A procedure to assess the relative performance of the different methods for borrowing information from historical control data is proposed, and practical questions related to the selection and implementation of methods are discussed. Based on our examination, we found that the methods have a comparable performance, but we recommend the robust mixture prior for its ease of implementation.

Genetic markers of bevacizumab-induced hypertension.

PURPOSE: There are currently no validated biomarkers predicting bevacizumab treatment outcome or toxicity. We combined biomarker data from six phase III trials of bevacizumab to assess whether genetic variation in vascular endothelial growth factor-A (VEGF-A) pathway or hypertension-related genes are associated with bevacizumab-induced hypertension. EXPERIMENTAL DESIGN: Germline DNA was available from 1,631 patients receiving bevacizumab-containing therapy for advanced solid tumors. Overall, 194 white patients had grade 1-4 bevacizumab-induced hypertension. In total, 236 single nucleotide polymorphisms (SNPs) located in VEGF-A, VEGF-A receptors (FLT1 and KDR), and other genes were selected using a SNP tagging approach and genotyped. A logistic regression on individual patient data was performed after adjustment for cancer type and five other covariates. RESULTS: Ten SNPs were associated with bevacizumab-induced hypertension (P ≤ 0.05), but none surpassed the threshold adjusted for multiple testing (P < 0.0002). The most significant VEGF-A pathway SNP was rs1680695 in EGLN3 [allelic odds ratio (OR) 1.50 [95 % confidence interval (Cl) 1.09-2.07], P = 0.012]. Two additional SNPs, rs4444903 in EGF and rs2305949 in KDR, were associated with hypertension (allelic OR 1.57 [95 % CI 1.17-2.11], P = 0.0025; allelic OR 0.62 [95 % CI 0.42-0.93], P = 0.020, respectively) and closely linked to nearby functional variants. Consistent with previous reports, rs11064560 in WNK1 was also associated with bevacizumab-induced hypertension (OR 1.41 [95 % CI 1.04-1.92], P = 0.028). CONCLUSIONS: The genes described in this large genetic analysis using pooled datasets warrant further functional investigation regarding their role in mediating bevacizumab-induced hypertension.

Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy.

BACKGROUND: Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified. METHODS: We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome. RESULTS: The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene. CONCLUSIONS: This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.

VEGF pathway genetic variants as biomarkers of treatment outcome with bevacizumab: an analysis of data from the AViTA and AVOREN randomised trials.

BACKGROUND: No biomarkers that could guide patient selection for treatment with the anti-VEGF monoclonal antibody bevacizumab have been identified. We assessed whether genetic variants in the VEGF pathway could act as biomarkers for bevacizumab treatment outcome. METHODS: We investigated DNA from white patients from two phase 3 randomised studies. In AViTA, patients with metastatic pancreatic adenocarcinoma were randomly assigned to receive gemcitabine and erlotinib plus either bevacizumab or placebo. In AVOREN, patients with metastatic renal-cell carcinoma were randomly assigned to receive interferon alfa-2a plus either bevacizumab or placebo. We assessed the correlation of 138 SNPs in the VEGF pathway with progression-free survival and overall survival in a subpopulation of patients from AViTA. Significant findings were confirmed in a subpopulation of patients from AVOREN and functionally studied at the molecular level. FINDINGS: We investigated DNA of 154 patients from AViTA, of whom 77 received bevacizumab, and 110 patients from AVOREN, of whom 59 received bevacizumab. Only rs9582036, a SNP in VEGF receptor 1 (VEGFR1 or FLT1), was significantly associated with overall survival in the bevacizumab group of AViTA after correction for multiplicity (per-allele hazard ratio [HR] 2·1, 95% CI 1·45-3·06, p=0·00014). This SNP was also associated with progression-free survival (per-allele HR 1·89, 1·31-2·71, p=0·00081) in bevacizumab-treated patients from AViTA. AC and CC carriers of this SNP exhibited HRs for overall survival of 2·0 (1·19-3·36; p=0·0091) and 4·72 (2·08-10·68; p=0·0002) relative to AA carriers. No effects were seen in placebo-treated patients and a significant genotype by treatment interaction (p=0·041) was recorded, indicating that the VEGFR1 locus containing this SNP serves as a predictive marker for bevacizumab treatment outcome in AViTA. Fine-mapping experiments of this locus identified rs7993418, a synonymous SNP affecting tyrosine 1213 in the VEGFR1 tyrosine-kinase domain, as the functional variant underlying the association. This SNP causes a shift in codon usage, leading to increased VEGFR1 expression and downstream VEGFR1 signalling. This VEGFR1 locus correlated significantly with progression-free survival (HR 1·81, 1·08-3·05; p=0·033) but not overall survival (HR 0·91, 0·45-1·82, p=0·78) in the bevacizumab group in AVOREN. INTERPRETATION: A locus in VEGFR1 correlates with increased VEGFR1 expression and poor outcome of bevacizumab treatment. Prospective assessment is underway to validate the predictive value of this novel biomarker. FUNDING: F Hoffmann-La Roche.

In silico exploration of amyloid-related imaging abnormalities in the gantenerumab open-label extension trials using a semi-mechanistic model.

Introduction: Amyloid-related imaging abnormalities with edema/effusion (ARIA-E) are commonly observed with anti-amyloid therapies in Alzheimer's disease. We developed a semi-mechanistic, in silico model to understand the time course of ARIA-E and its dose dependency. Methods: Dynamic and statistical analyses of data from 112 individuals that experienced ARIA-E in the open-label extension of SCarlet RoAD (a study of gantenerumab in participants with prodromal Alzheimer's disease) and Marguerite RoAD (as study of Gantenerumab in participants with mild Alzheimer's disease) studies were used for model building. Gantenerumab pharmacokinetics, local amyloid removal, disturbance and repair of the vascular wall, and ARIA-E magnitude were represented in the novel vascular wall disturbance (VWD) model of ARIA-E. Results: The modeled individual-level profiles provided a good representation of the observed pharmacokinetics and time course of ARIA-E magnitude. ARIA-E dynamics were shown to depend on the interplay between drug-mediated amyloid removal and intrinsic vascular repair processes. Discussion: Upon further refinement and validation, the VWD model could inform strategies for dosing and ARIA monitoring in individuals with an ARIA-E history.

Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease.

Introduction: Clinical trials for sporadic Alzheimer's disease generally use mixed models for repeated measures (MMRM) or, to a lesser degree, constrained longitudinal data analysis models (cLDA) as the analysis model with time since baseline as a categorical variable. Inferences using MMRM/cLDA focus on the between-group contrast at the pre-determined, end-of-study assessments, thus are less efficient (eg, less power). Methods: The proportional cLDA (PcLDA) and proportional MMRM (pMMRM) with time as a categorical variable are proposed to use all the post-baseline data without the linearity assumption on disease progression. Results: Compared with the traditional cLDA/MMRM models, PcLDA or pMMRM lead to greater gain in power (up to 20% to 30%) while maintaining type I error control. Discussion: The PcLDA framework offers a variety of possibilities to model longitudinal data such as proportional MMRM (pMMRM) and two-part pMMRM which can model heterogeneous cohorts more efficiently and model co-primary endpoints simultaneously.

Comparing ARIA-E severity scales and effects of treatment management thresholds.

Introduction: Amyloid-related imaging abnormalities-edema (ARIA-E) is associated with anti-amyloid beta monoclonal antibody treatment. ARIA-E severity may be assessed using the Barkhof Grand Total Scale (BGTS) or the 3- or 5-point Severity Scales of ARIA-E (SSAE-3/SSAE-5). We assessed inter- and intra-reader correlations between SSAE-3/5 and BGTS. Methods: Magnetic resonance imaging scans were collected from 75 participants in the SCarlet RoAD and Marguerite RoAD studies. Three neuroradiologists reviewed scans at baseline and at follow-up. Concordance in dichotomized ARIA-E ratings was assessed for a range of BGTS thresholds. Results: SSAE-3/5 scores correlated with BGTS scores, with high inter-reader intraclass correlation coefficients across all scales. There was high agreement in dichotomized ratings for SSAE-3 > 1 versus BGTS > 3 for all readers (accuracy 0.85-0.93) and between pairs of readers. Discussion: SSAE-3/5 showed high degrees of correlation with BGTS, potentially allowing seamless transition from the BGTS to SSAE-3/5 for ARIA-E management.

Evaluation of dose-dependent treatment effects after mid-trial dose escalation in biomarker, clinical, and cognitive outcomes for gantenerumab or solanezumab in dominantly inherited Alzheimer's disease.

Introduction: While the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) was ongoing, external data suggested higher doses were needed to achieve targeted effects; therefore, doses of gantenerumab were increased 5-fold, and solanezumab was increased 4-fold. We evaluated to what extent mid-trial dose increases produced a dose-dependent treatment effect. Methods: Using generalized linear mixed effects (LME) models, we estimated the annual low- and high-dose treatment effects in clinical, cognitive, and biomarker outcomes. Results: Both gantenerumab and solanezumab demonstrated dose-dependent treatment effects (significant for gantenerumab, non-significant for solanezumab) in their respective target amyloid biomarkers (Pittsburgh compound B positron emission tomography standardized uptake value ratio and cerebrospinal fluid amyloid beta 42), with gantenerumab demonstrating additional treatment effects in some downstream biomarkers. No dose-dependent treatment effects were observed in clinical or cognitive outcomes. Conclusions: Mid-trial dose escalation can be implemented as a remedy for an insufficient initial dose and can be more cost effective and less burdensome to participants than starting a new trial with higher doses, especially in rare diseases. Highlights: We evaluated the dose-dependent treatment effect of two different amyloid-specific immunotherapies.Dose-dependent treatment effects were observed in some biomarkers.No dose-dependent treatment effects were observed in clinical/cognitive outcomes, potentially due to the fact that the modified study may not have been powered to detect such treatment effects in symptomatic subjects at a mild stage of disease exposed to high (or maximal) doses of medication for prolonged durations.

A statistician's perspective on biomarkers in drug development.

Biomarkers play an increasingly important role in many aspects of pharmaceutical discovery and development, including personalized medicine and the assessment of safety data, with heavy reliance being placed on their delivery. Statisticians have a fundamental role to play in ensuring that biomarkers and the data they generate are used appropriately and to address relevant objectives such as the estimation of biological effects or the forecast of outcomes so that claims of predictivity or surrogacy are only made based upon sound scientific arguments. This includes ensuring that studies are designed to answer specific and pertinent questions, that the analyses performed account for all levels and sources of variability and that the conclusions drawn are robust in the presence of multiplicity and confounding factors, especially as many biomarkers are multidimensional or may be an indirect measure of the clinical outcome. In all of these areas, as in any area of drug development, statistical best practice incorporating both scientific rigor and a practical understanding of the situation should be followed. This article is intended as an introduction for statisticians embarking upon biomarker-based work and discusses these issues from a practising statistician's perspective with reference to examples.

Classification, Prediction, and Concordance of Cognitive and Functional Progression in Patients with Mild Cognitive Impairment in the United States: A Latent Class Analysis.

BACKGROUND: Progression trajectories of patients with mild cognitive impairment (MCI) are currently not well understood. OBJECTIVE: To classify patients with incident MCI into different latent classes of progression and identify predictors of progression class. METHODS: Participants with incident MCI were identified from the US National Alzheimer's Coordinating Center Uniform Data Set (09/2005-02/2019). Clinical Dementia Rating (CDR®) Dementia Staging Instrument-Sum of Boxes (CDR-SB), Functional Activities Questionnaire (FAQ), and Mini-Mental State Examination (MMSE) score longitudinal trajectories from MCI diagnosis were fitted using growth mixture models. Predictors of progression class were identified using multivariate multinomial logistic regression models; odds ratios (ORs) and 95% confidence intervals (CIs) were reported. RESULTS: In total, 21%, 22%, and 57% of participants (N = 830) experienced fast, slow, and no progression on CDR-SB, respectively; for FAQ, these figures were 14%, 23%, and 64%, respectively. CDR-SB and FAQ class membership was concordant for most participants (77%). Older age (≥86 versus≤70 years, OR [95% CI] = 5.26 [1.78-15.54]), one copy of APOE ɛ4 (1.94 [1.08-3.47]), higher baseline CDR-SB (2.46 [1.56-3.88]), lower baseline MMSE (0.85 [0.75-0.97]), and higher baseline FAQ (1.13 [1.02-1.26]) scores were significant predictors of fast progression versus no progression based on CDR-SB (all p < 0.05). Predictors of FAQ class membership were largely similar. CONCLUSION: Approximately a third of participants experienced progression based on CDR-SB or FAQ during the  4-year follow-up period. CDR-SB and FAQ class assignment were concordant for the vast majority of participants. Identified predictors may help the selection of patients at higher risk of progression in future trials.

Changes in transcriptome after in vivo exposure to ionising radiation reveal a highly specialised liver response.

PURPOSE: To identify transcriptional gene-networks involved in the early in vivo response of liver cells to radiation exposure and improve our understanding of the molecular processes responsible for tissue radiosensitivity. MATERIALS AND METHODS: Transcriptome variations of liver RNA samples were measured 3 hours post-irradiation using microarray technology. The results were confirmed and extended using real-time polymerase-chain-reaction (RT-PCR). RESULTS: We identified quantitative changes in the expression of 126 genes, most of which were observed for the first time. We show that some modifications, such as the upregulation of the cyclin-dependent kinase inhibitor 1A (Cdkn1A) gene, persisted for at least two months after the initial exposure. Other genes regulated by the transformation-related protein 53 (Trp53/p53) such as Bcl2-associated X protein (Bax) or etoposide-induced-2.4 (Ei24/PIG8) were not upregulated. Grouping differentially expressed genes into functional categories revealed that the primary response of liver cells to radiation exposure was the enhancement of oxidoreductase activity and inhibition of cell proliferation, involving cell cycle progression and apoptosis-related genes. CONCLUSIONS: The data provides evidence of gene expression modifications associated with the hepatic response to radiation exposure. One of the main differences observed with radiation-sensitive tissues such as the spleen was cell proliferation. The comparison of our data with transcriptome modifications in different biological models enabled the identification of networks of genes that might be co-regulated. Overall, our expression data revealed genes and cellular pathways that might help to improve our understanding of the molecular basis underlying tissue radiosensitivity and to identify possible targets for novel therapeutic strategies.