Identifying Predictors of PASI100 Responses up to Month 12 in Patients with Moderate-to-severe Psoriasis Receiving Biologics in the Psoriasis Study of Health Outcomes (PSoHO).

Despite the abundance of data concerning biologic treatments for patients with psoriasis, clinicians are often challenged with discerning the optimal treatment for each patient. To inform this selection, this study explored whether a patient's baseline characteristics or disease profile could predict the likelihood of achieving complete skin clearance with biologic treatment. Machine-learning and other statistical methods were applied to the substantial data collected from patients with moderate-to-severe psoriasis in the ongoing, international, prospective, observational Psoriasis Study of Health Outcomes (PSoHO).

Incidence of type 2 diabetes, cardiovascular disease and chronic kidney disease in patients with multiple sclerosis initiating disease-modifying therapies: Retrospective cohort study using a frequentist model averaging statistical framework.

Researchers are increasingly using insights derived from large-scale, electronic healthcare data to inform drug development and provide human validation of novel treatment pathways and aid in drug repurposing/repositioning. The objective of this study was to determine whether treatment of patients with multiple sclerosis with dimethyl fumarate, an activator of the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway, results in a change in incidence of type 2 diabetes and its complications. This retrospective cohort study used administrative claims data to derive four cohorts of adults with multiple sclerosis initiating dimethyl fumarate, teriflunomide, glatiramer acetate or fingolimod between January 2013 and December 2018.

Comparative Effectiveness and Durability of Biologics in Clinical Practice: Month 12 Outcomes from the International, Observational Psoriasis Study of Health Outcomes (PSoHO).

Introduction: Given the chronic nature of psoriasis (PsO), more studies are needed that directly compare the effectiveness of different biologics over long observation periods. This study compares the effectiveness and durability through 12 months of anti-interleukin (IL)-17A biologics relative to other approved biologics in patients with moderate-to-severe psoriasis in a real-world setting.

Methods: The Psoriasis Study of Health Outcomes (PSoHO) is an ongoing 3-year, prospective, non-interventional cohort study of 1981 adults with chronic moderate-to-severe plaque psoriasis initiating or switching to a new biologic.

An Early Assessment of the Real-World Treatment Patterns of Type 2 Diabetes: A Comparison to the 2018 ADA/EASD Consensus Report Recommendations.

Introduction: Using the American Diabetes Association (ADA) Hyperglycemic Pharmacotherapy Guidelines for type 2 diabetes, we evaluated the medication use patterns in real-world patients with type 2 diabetes in the USA.

Methods: Health care claims among patients with type 2 diabetes were analyzed (IBM MarketScan 2007 to 2019 Commercial and Medicare Databases). Diabetes treatment patterns were evaluated for the total patient sample of 580,741 during the year 2019.

Type 2 diabetes pharmacotherapy trends in high-risk subgroups.

Medication use trends among patients with type 2 diabetes from 2015 to 2019 were investigated in relation to the clinical group-specific recommendations from the 2018 American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) consensus report. Data were drawn from a large health insurance claims database representing Commercial (total patient-year count: 2,379,704) and Medicare (total patient-year count: 845,823) insurance programmes (IBM® MarketScan®). The utilization of sodium-glucose co-transporter-2 inhibitors or glucagon-like peptide-1 receptor agonists increased over time but was lower in the Medicare cohort in every year evaluated.

Evaluating bias control strategies in observational studies using frequentist model averaging.

Estimating a treatment effect from observational data requires modeling treatment and outcome subject to uncertainty/misspecification. A previous research has shown that it is not possible to find a uniformly best strategy. In this article we propose a novel Frequentist Model Averaging (FMA) framework encompassing any estimation strategy and accounting for model uncertainty by computing a cross-validated estimate of Mean Squared Prediction Error (MSPE).

Practical recommendations on double score matching for estimating causal effects.

Unlike in randomized clinical trials (RCTs), confounding control is critical for estimating the causal effects from observational studies due to the lack of treatment randomization. Under the unconfoundedness assumption, matching methods are popular because they can be used to emulate an RCT that is hidden in the observational study. To ensure the key assumption hold, the effort is often made to collect a large number of possible confounders, rendering dimension reduction imperative in matching.

Predicting optimal treatment regimens for patients with HR+/HER2- breast cancer using machine learning based on electronic health records.

To predict optimal treatments maximizing overall survival (OS) and time to treatment discontinuation (TTD) for patients with metastatic breast cancer (MBC) using machine learning methods on electronic health records. Adult females with HR+/HER2- MBC on first- or second-line systemic therapy were eligible. Random survival forest (RSF) models were used to predict optimal regimen classes for individual patients and each line of therapy based on baseline characteristics.

Multilevel network meta-regression for population-adjusted treatment comparisons.

Standard network meta-analysis (NMA) and indirect comparisons combine aggregate data from multiple studies on treatments of interest, assuming that any effect modifiers are balanced across populations. Population adjustment methods relax this assumption using individual patient data from one or more studies. However, current matching-adjusted indirect comparison and simulated treatment comparison methods are limited to pairwise indirect comparisons and cannot predict into a specified target population.

Comparative effectiveness of improvement in pain and physical function for baricitinib versus adalimumab, tocilizumab and tofacitinib monotherapies in rheumatoid arthritis patients who are naïve to treatment with biologic or conventional synthetic disease-modifying antirheumatic drugs: a matching-adjusted indirect comparison.

Objective: To compare improvement in pain and physical function for patients treated with baricitinib, adalimumab, tocilizumab and tofacitinib monotherapy from randomised, methotrexate (MTX)-controlled trials in conventional synthetic disease-modifying antirheumatic drugs (csDMARDs)/biologic (bDMARD)-naïve RA patients using matching-adjusted indirect comparisons (MAICs).

Methods: Data were from Phase III trials on patients receiving monotherapy baricitinib, tocilizumab, adalimumab, tofacitinib or MTX. Pain was assessed using a visual analogue scale (0-100 mm) and physical function using the Health Assessment Questionnaire-Disability Index (HAQ-DI).

Stated Preferences for Attributes of a Pharmacogenetic Test Among the General Population Presented with a Hypothetical Acute Coronary Syndrome Scenario.

Background: Pharmacogenetic (PGx) testing identifies pharmacotherapeutic risks to permit personalized therapy. Identifying the genetic profile of patients with acute coronary syndrome (ACS) who are considered for therapy with clopidogrel (P2Y receptor blockers) and acetylsalicylic acid (ASA) contributes to the treatment paradigm. Patient preferences would inform a collaborative framework and by extension inform healthcare policy formulation.

Combination of several matching adjusted indirect comparisons (MAICs) with an application in psoriasis.

In health technology assessment (HTA), beside network meta-analysis (NMA), indirect comparisons (IC) have become an important tool used to provide evidence between two treatments when no head-to-head data are available. Researchers may use the adjusted indirect comparison based on the Bucher method (AIC) or the matching-adjusted indirect comparison (MAIC). While the Bucher method may provide biased results when included trials differ in baseline characteristics that influence the treatment outcome (treatment effect modifier), this issue may be addressed by applying the MAIC method if individual patient data (IPD) for at least one part of the AIC is available.

Alternative Weighting Approaches for Anchored Matching-Adjusted Indirect Comparisons via a Common Comparator.

Background: Adjusted indirect comparisons (anchored via a common comparator) are an integral part of health technology assessment. These methods are challenged when differences between studies exist, including inclusion/exclusion criteria, outcome definitions, patient characteristics, as well as ensuring the choice of a common comparator.

Objectives: Matching-adjusted indirect comparison (MAIC) can address these challenges, but the appropriate application of MAICs is uncertain.

Evaluating different strategies for estimating treatment effects in observational studies.

Since the introduction of the propensity score (PS), methods for estimating treatment effects with observational data have received growing attention in the literature. Recent research has added substantially to the number of available statistical approaches for controlling confounding in such analyses. However, researchers need guidance to decide on the optimal analytic strategy for any given scenario.

The epidemiology and burden of Alzheimer's disease in Taiwan utilizing data from the National Health Insurance Research Database.

Purpose: The objectives of this study were to estimate the incidence, cumulative incidence, and economic burden of Alzheimer's disease (AD) in Taiwan, using data from the National Health Insurance Research Database (NHIRD).

Materials And Methods: This was a retrospective, longitudinal, observational study using data from the Longitudinal Health Insurance Database of the NHIRD. Patients were included in this study if they were 50 years of age or older and their records included a primary or secondary diagnosis of AD.

Propensity score matching and subclassification in observational studies with multi-level treatments.

In this article, we develop new methods for estimating average treatment effects in observational studies, in settings with more than two treatment levels, assuming unconfoundedness given pretreatment variables. We emphasize propensity score subclassification and matching methods which have been among the most popular methods in the binary treatment literature. Whereas the literature has suggested that these particular propensity-based methods do not naturally extend to the multi-level treatment case, we show, using the concept of weak unconfoundedness and the notion of the generalized propensity score, that adjusting for a scalar function of the pretreatment variables removes all biases associated with observed pretreatment variables.

Increasing body mass index identifies Chinese patients with type 2 diabetes mellitus at risk of poor outcomes.

Aims: Association between body mass index (BMI) and glycemic control, comorbidities/complications, and health-related quality of life (HRQoL) was assessed in Chinese patients with type 2 diabetes mellitus (T2DM) enrolled in the Diabetes Disease Specific Programme.

Methods: Surveys of 200 physicians and 2052 patients with T2DM captured demographic, clinical, and HRQoL information. Adjusted and unadjusted analyses were conducted across 3 BMI groups; normal (18.

Correlation between changes in quality of life and symptomatic improvement in Chinese patients switched from typical antipsychotics to olanzapine.

Purpose: The aim of this study was to investigate the correlation between changes in symptoms and changes in self-reported quality of life among Chinese patients with schizophrenia who were switched from a typical antipsychotic to olanzapine during usual outpatient care.

Patients And Methods: This post hoc analysis was conducted using data from the Chinese subgroup (n=475) of a multicountry, 12-month, prospective, noninterventional, observational study. The primary publication previously reported the efficacy, safety, and quality of life among patients who switched from a typical antipsychotic to olanzapine.

Does participation in a weight control program also improve clinical and functional outcomes for Chinese patients with schizophrenia treated with olanzapine?

Objectives: This study examined whether participation in a weight control program (WCP) by patients with schizophrenia treated with olanzapine was also associated with improvements in clinical and functional outcomes.

Methods: A post-hoc analysis was conducted using data from the Chinese subgroup (n=330) of a multi-country, 6-month, prospective, observational study of outpatients with schizophrenia who initiated or switched to oral olanzapine. At study entry and monthly visits, participants were assessed with the Clinical Global Impression of Severity, and measures of patient insight, social activities, and work impairment.

Prognostic factors for patients with advanced non-small cell lung cancer treated with gemcitabine-platinum as first-line therapy in an observational setting in China.

Background: This study examined the prognostic factors associated with survival in advanced non-small cell lung cancer (NSCLC) patients receiving gemcitabine-platinum regimens as first-line therapy in real-world clinical settings in China.

Methods: Data was analyzed from a multinational, prospective, non-interventional, observational study of individuals receiving gemcitabine-platinum regimens as first-line therapy for NSCLC, focusing on 300 patients from mainland China. A Cox regression model was used to determine the association of 38 prognostic factors, including patient smoking characteristics, with overall survival.