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Author: Dima, Alexandra L. ; Carney, Robert M ; Doyle, Frank ; Dima, Alexandra L ; Guerin, Suzanne ; Kathuria, Bishember ; Freedland, Kenneth E ; Brannick, Susan ; Boland, Fiona ; Hevey, David ; Carney, Robert M. ; McDarby, Vincent ; Freedland, Kenneth E. ; Byrne, David ; Cuijpers, Pim ; Wallace, Emma ; Ghoshal, Arunangshu

BACKGROUNDThe 10-item Montgomery-Åsberg Depression Rating Scale (MADRS) is a commonly used measure of depression in antidepressant clinical trials. Numerous studies have adopted classical test theory perspectives to assess the psychometric properties of this scale, finding generally positive results. However, its network configural structure and stability is unexplored across different time-points and treatment groups.AIMSTo assess the network structure and stability of the MADRS in clinical settings pre- and post-treatment, and to determine a configurally invariant and stable model across time-points and treatment groups (placebo and intervention).METHODIndividual participant data for 6440 participants from 14 clinical trials of major depressive disorder was obtained from the data repository Vivli.org. Exploratory Graphical Analysis (EGA) was used to identify empirical models pre-treatment (baseline) and post-treatment (8-week outcome). Bootstrapping techniques were applied to obtain optimised configurally invariant models.RESULTSEmpirical models presented with performance issues at baseline and for the placebo group at outcome. An abbreviated 8-item single-community model was found to be stable and configurally invariant across time-points and treatment groups. Symptoms such as low mood and lassitude showed most centrality across all models.LIMITATIONSMetric invariance could not be explored due to research environment limitations.CONCLUSIONSAn 8-item one-community variant of the MADRS may provide optimal performance when conducting network analyses of antidepressant clinical trial outcomes. Findings suggest that interventions targeting low mood and lassitude might be most efficacious in treating depression among clinical trial participants. Further considerations of the potential impact on trial design and analysis should be explored.

01 Oct 2024·Dermatology and Therapy

Comprehensive Codified Algorithms to Identify the Underestimated Burden of Hidradenitis Suppurativa in the United States

Article

Author: Garg, Amit ; Geissbühler, Yvonne ; Richardson, Craig ; Darcy, John ; Gaffney, Alex ; McConnon, Aine ; Ingram, John R ; Foley, Stephen

INTRODUCTIONHidradenitis suppurativa (HS) is a painful, inflammatory skin disease associated with a high disease burden and long diagnostic delay. Prevalence estimates of HS vary widely in the literature owing to differing estimation methodologies. This study aimed to apply stepwise algorithms to estimate the prevalence of possible/diagnosed cases of HS in the US.METHODSThis was a retrospective cohort study in adult and pediatric patients with HS which utilized data from four US databases (MarketScan [Medicare and Medicaid] and Optum [electronic health record (EHR) and Clinformatics Data Mart (CDM)]). Patients with possible/diagnosed HS were identified using two algorithms (termed Algorithm 1 and Algorithm 2), which assessed symptoms such as multiple skin boils in site-specific areas based on international classification of disease (ICD) codes. Patients with diagnosed HS were defined as having ≥ 2 outpatient or ≥ 1 inpatient diagnosis codes of HS. In each database, patients with continuous medical and pharmacy benefits in the 365 days pre-index and 0-365 days post-index periods were eligible for inclusion.RESULTSAcross all databases, Algorithm 2 (MarketScan Medicare [N = 309,916]; MarketScan Medicaid [N = 188,783]; Optum EHR [N = 366,158]; Optum CDM [N = 173,812]) identified more patients with possible/diagnosed HS than Algorithm 1 (MarketScan Medicare [N = 194,353]; MarketScan Medicaid [N = 99,276]; Optum EHR [N = 177,957]; Optum CDM [N = 112,244]). Based on ICD-9/10 codes, the 5-year period prevalence of HS ranged from 0.06% to 0.12% across all databases, while for Algorithm 1 and Algorithm 2, this ranged from 0.27% to 0.41% and 0.49% to 0.78%, respectively. Adults and females generally had a higher 5-year period prevalence versus pediatric patients and males, respectively.CONCLUSIONThis real-world study highlights that HS diagnosis codes alone may be insufficient to estimate the prevalence of HS, demonstrating the value of employing algorithms in practice which assess for parameters such as multiple skin boils in site-specific areas. Integrating robust methods to identify the prevalence of HS may improve the diagnostic delay observed in HS and improve treatment outcomes.

01 Sep 2024·Psychiatry Research

Evaluating the psychometric structure of the Hamilton Rating Scale for Depression pre- and post-treatment in antidepressant randomised trials: Secondary analysis of 6843 individual participants from 20 trials

Article

Author: Boland, Fiona ; Guerin, Suzanne ; Dima, Alexandra L ; Hevey, David ; Wallace, Emma ; Kathuria, Bishember ; Carney, Robert M ; Freedland, Kenneth ; Doyle, Frank ; Byrne, David ; Brannick, Susan ; Cuijpers, Pim

BACKGROUNDThe 17-item Hamilton Rating Scale for Depression (HRSD-17) is the most popular depression measure in antidepressant clinical trials. Prior evidence indicates poor replicability and inconsistent factorial structure. This has not been studied in pooled randomised trial data, nor has a psychometrically optimal model been developed.AIMSTo examine the psychometric properties of the HRSD-17 for pre-treatment and post-treatment clinical trial data in a large pooled database of antidepressant randomised controlled trial participants, and to determine an optimal abbreviated version.METHODData for 6843 participants were obtained from the data repository Vivli.org and randomly split into groups for exploratory (n = 3421) and confirmatory (n = 3422) factor analysis. Invariance methods were used to assess potential sex differences.RESULTSThe HRSD-17 was psychometrically sub-optimal and non-invariant for all models. High item variances and low variance explained suggested redundancy in each model. EFA failed at baseline and produced four item models for outcome groups (five for placebo-outcome), which were metric but not scalar invariant.CONCLUSIONSIn antidepressant trial data, the HRSD-17 was psychometrically inadequate and scores were not sex invariant. Neither full nor abbreviated HRSD models are suitable for use in clinical trial settings and the HRSD's status as the gold standard should be reconsidered.

100 Deals associated with Novartis Ireland Ltd.

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100 Translational Medicine associated with Novartis Ireland Ltd.

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Pipeline

Pipeline Snapshot as of 07 Nov 2024

The statistics for drugs in the Pipeline is the current organization and its subsidiaries are counted as organizations,Early Phase 1 is incorporated into Phase 1, Phase 1/2 is incorporated into phase 2, and phase 2/3 is incorporated into phase 3

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