POP-REFINE: A Comprehensive Framework for Evaluating and Optimizing Representativeness in Clinical Trials.

Clinical research has historically failed to include representative levels of historically underrepresented populations and these inequities continue to persist. Ensuring representativeness in clinical trials is crucial for patients to receive clinically appropriate treatment and have equitable access to novel therapies; enhancing the generalizability of study results; and reducing the need for post-marketing commitments focused on underrepresented groups. As demonstrated by recent legislation and guidance documents, regulatory agencies have shown an increased interest in understanding how novel therapies will impact the patient population that will receive them.

Inverse Probability of Treatment Weighting and Confounder Missingness in Electronic Health Record-based Analyses: A Comparison of Approaches Using Plasmode Simulation.

Background: Electronic health record (EHR) data represent a critical resource for comparative effectiveness research, allowing investigators to study intervention effects in real-world settings with large patient samples. However, high levels of missingness in confounder variables is common, challenging the perceived validity of EHR-based investigations.

Methods: We investigated performance of multiple imputation and propensity score (PS) calibration when conducting inverse probability of treatment weights (IPTW)-based comparative effectiveness research using EHR data with missingness in confounder variables and outcome misclassification.

Telemedicine use among patients with metastatic breast cancer during the COVID-19 pandemic: Differences by race, age, and region.

Purpose: Our objective was to describe differences in telemedicine use among women with metastatic breast cancer (mBC) by race, age, and geographic region.

Methods: This was a retrospective cohort study of women with recurrent or de novo mBC treated in US community cancer practices that initiated a new line of therapy between March 2020 and February 2021. Multivariable modified Poisson regression models were used to calculate adjusted rate ratios (RR) and robust 95% confidence intervals (CI) associated with telemedicine visits within 90 days of therapy initiation.

Differential frequency in imaging-based outcome measurement: Bias in real-world oncology comparative-effectiveness studies.

Background: Comparative-effectiveness studies using real-world data (RWD) can be susceptible to surveillance bias. In solid tumor oncology studies, analyses of endpoints such as progression-free survival (PFS) are based on progression events detected by imaging assessments. This study aimed to evaluate the potential bias introduced by differential imaging assessment frequency when using electronic health record (EHR)-derived data to investigate the comparative effectiveness of cancer therapies.

Real-World Outcomes for Advanced Non-Small Cell Lung Cancer Patients Treated With a PD-L1 Inhibitor Beyond Progression.

Background: Clinical trials of anti-programmed cell death ligand 1 (PD-L1) inhibitor to treat advanced non-small-cell lung cancer (aNSCLC) have permitted treatment beyond progression (TBP). However, the outcomes of patients receiving TBP in routine clinical care are unknown.

Materials And Methods: The present retrospective, observational, multicenter analysis evaluated de-identified electronic health record-derived data from community-based clinics in the United States.

Characterizing the Feasibility and Performance of Real-World Tumor Progression End Points and Their Association With Overall Survival in a Large Advanced Non-Small-Cell Lung Cancer Data Set.

Purpose: Large, generalizable real-world data can enhance traditional clinical trial results. The current study evaluates reliability, clinical relevance, and large-scale feasibility for a previously documented method with which to characterize cancer progression outcomes in advanced non-small-cell lung cancer from electronic health record (EHR) data.

Methods: Patients who were diagnosed with advanced non-small-cell lung cancer between January 1, 2011, and February 28, 2018, with two or more EHR-documented visits and one or more systemic therapy line initiated were identified in Flatiron Health's longitudinal EHR-derived database.

Generating Real-World Tumor Burden Endpoints from Electronic Health Record Data: Comparison of RECIST, Radiology-Anchored, and Clinician-Anchored Approaches for Abstracting Real-World Progression in Non-Small Cell Lung Cancer.

Introduction: Real-world evidence derived from electronic health records (EHRs) is increasingly recognized as a supplement to evidence generated from traditional clinical trials. In oncology, tumor-based Response Evaluation Criteria in Solid Tumors (RECIST) endpoints are standard clinical trial metrics. The best approach for collecting similar endpoints from EHRs remains unknown.

An evaluation of the impact of missing deaths on overall survival analyses of advanced non-small cell lung cancer patients conducted in an electronic health records database.

Purpose: The aim of this study was to assess the impact of missing death data on survival analyses conducted in an oncology EHR-derived database.

Methods: The study was conducted using the Flatiron Health oncology database and the National Death Index (NDI) as a gold standard. Three analytic frameworks were evaluated in advanced non-small cell lung cancer (aNSCLC) patients: median overall survival [mOS]), relative risk estimates conducted within the EHR-derived database, and "external control arm" analyses comparing an experimental group augmented with mortality data from the gold standard to a control group from the EHR-derived database only.

Development and Validation of a High-Quality Composite Real-World Mortality Endpoint.

Objective: To create a high-quality electronic health record (EHR)-derived mortality dataset for retrospective and prospective real-world evidence generation.

Data Sources/study Setting: Oncology EHR data, supplemented with external commercial and US Social Security Death Index data, benchmarked to the National Death Index (NDI).

Study Design: We developed a recent, linkable, high-quality mortality variable amalgamated from multiple data sources to supplement EHR data, benchmarked against the highest completeness U.

Prevalence and Predictors of Depression Among Patients With Epilepsy, Stroke, and Multiple Sclerosis Using the Cleveland Clinic Knowledge Program Within the Neurological Institute.

Background: Neurological conditions carry a high risk of depression. Given this risk, the Neurological Institute (NI) at Cleveland Clinic has initiated systematic screening for depression using the 9-item Patient Health Questionnaire-9 (PHQ-9) embedded within its electronic medical record and its data capture system, the Knowledge Program (KP).

Objective: We sought to (1) estimate the prevalence of depression among patients with epilepsy, stroke, and multiple sclerosis (MS); (2) identify risk factors for depression within each disease; and (3) determine differential risks and predictors across neurological disorders.

Scale Linking to Enable Patient-Reported Outcome Performance Measures Assessed with Different Patient-Reported Outcome Measures.

Background: Patient-reported outcome performance measures (PRO-PMs) incorporate outcomes from the patient's perspective into performance measures and may have great potential to impact health care. The various patient-reported outcome measures (PROMs) used to assess the same outcome challenge widespread use of PRO-PMs. A potential solution is to statistically link PROMs to provide equivalent PRO-PM conclusions to be drawn regardless of which PROM was used.

Proximity and gravity: modeling heaped self-reports.

Self-reported daily cigarette counts typically exhibit a preponderance of round numbers, a phenomenon known as heaping or digit preference. Heaping can be a substantial nuisance, as scientific interest lies in the distribution of the underlying true values rather than that of the heaped data. In principle, we can estimate parameters of the underlying distribution from heaped data if we know the conditional distribution of the heaped count given the true count, denoted the heaping mechanism (analogous to the missingness mechanism for missing data).

The role of very high high-sensitivity C-reactive protein levels on mortality after stroke.

Unlabelled: High-sensitivity C-reaction protein (hsCRP) levels are correlated with risk of vascular disease. The clinical implications of markedly elevated hsCRP levels in the setting of acute stroke are less understood.

Objective: To determine the association of very high admission hsCRP levels (≥10mg/L) on all-cause mortality in patients with acute stroke.

Impact of Sleep-Disordered Breathing Treatment on Patient Reported Outcomes in a Clinic-Based Cohort of Hypertensive Patients.

Study Objectives: We hypothesized that patient reported outcomes (PROs) improve with positive airway pressure (PAP) in patients with sleep-disordered breathing (SDB) and hypertension (HTN).

Methods: Questionnaire-based PROs (sleepiness [Epworth Sleepiness Scale, (ESS)], depression [Patient Health Questionnaire-9 (PHQ-9)], and fatigue [Fatigue Severity Scale (FSS)]) were retrospectively examined in patients with SDB and HTN at baseline and within a year following PAP initiation. PRO changes were estimated using multivariable linear mixed-effect models adjusted for baseline age, sex, race, body mass index, resistant hypertension (RHTN) status, cardiac and diabetes history, and correlation between repeated measurements.

The PROMIS physical function scale: A promising scale for use in patients with ischemic stroke.

Objective: To evaluate the performance of the Patient Reported Outcomes Measurement Information System (PROMIS) physical function (PF) scale compared to the validated Stroke Impact Scale-16 (SIS-16) in ischemic stroke patients seen in an ambulatory cerebrovascular clinic.

Methods: This was a retrospective cohort study. PROMIS PF (computer adaptive testing version) and SIS-16 measures were electronically collected on 1,946 ischemic stroke patients seen in a cerebrovascular clinic using an electronic platform from September 12, 2012, to June 16, 2015.

Electronic Stroke CarePath: Integrated Approach to Stroke Care.

We describe the development, implementation, and outcomes of the first 2 years of the Electronic Stroke CarePath, an initiative developed for management of ischemic stroke patients in an effort to improve efficiency and quality of care for patients. The CarePath consists of care pathways for ischemic stroke that are integrated within the electronic health record. Patient-reported outcomes are collected using an external software platform.

Longitudinal Effect of CPAP on BP in Resistant and Nonresistant Hypertension in a Large Clinic-Based Cohort.

Background: Clinic-based effectiveness studies of sleep-disordered breathing (SDB) treatment in reducing BP in resistant hypertension (RHTN) vs non-RHTN are sparse. We hypothesize that CPAP use in SDB reduces BP significantly in RHTN and non-RHTN in a large clinic-based cohort.

Methods: Electronic medical records were reviewed in patients with SDB and comorbid RHTN and non-RHTN for CPAP therapy initiation (baseline) and subsequent visits.

National Incidence of Medication Error in Surgical Patients Before and After Accreditation Council for Graduate Medical Education Duty-Hour Reform.

Objective: The Accreditation Council for Graduate Medical Education (ACGME) established duty-hour regulations for accredited residency programs on July 1, 2003. It is unclear what changes occurred in the national incidence of medication errors in surgical patients before and after ACGME regulations.

Design: Patient and hospital characteristics for pre- and post-duty-hour reform were evaluated, comparing teaching and nonteaching hospitals.

Model-based imputation of latent cigarette counts using data from a calibration study.

In addition to dichotomous measures of abstinence, smoking studies may use daily cigarette consumption as an outcome variable. These counts hold the promise of more efficient and detailed analyses than dichotomous measures, but present serious quality issues - measurement error and heaping - if obtained by retrospective recall. A doubly-coded dataset with a retrospective recall measurement (timeline followback, TLFB) and a more precise instantaneous measurement (ecological momentary assessment, EMA) serves as a calibration dataset, allowing us to predict EMA given TLFB and baseline factors.

National Trends and In-hospital Complication Rates in More Than 1600 Hemispherectomies From 1988 to 2010: A Nationwide Inpatient Sample Study.

Background: Anatomic and functional hemispherectomies are relatively infrequent and technically challenging. The literature is limited by small samples and single institution data.

Objective: We used the Nationwide Inpatient Sample (NIS) database to report on a large population of hemispherectomy patients and their in-hospital complication rates over a 23-year period.

A new Elixhauser-based comorbidity summary measure to predict in-hospital mortality.

Background: Recently, van Walraven developed a weighted summary score (VW) based on the 30 comorbidities from the Elixhauser comorbidity system. One of the 30 comorbidities, cardiac arrhythmia, is currently excluded as a comorbidity indicator in administrative datasets such as the Nationwide Inpatient Sample (NIS), prompting us to examine the validity of the VW score and its use in the NIS.

Methods: Using data from the 2009 Maryland State Inpatient Database, we derived weighted summary scores to predict in-hospital mortality based on the full (30) and reduced (29) set of comorbidities and compared model performance of these and other comorbidity summaries in 2009 NIS data.

Nonopioid substance use disorders and opioid dose predict therapeutic opioid addiction.

Unlabelled: Limited research examines the risk of therapeutic opioid addiction (TOA) in patients with chronic noncancer pain. This study examined TOA among 199 patients undergoing long-term opioid therapy at the time of admission to a pain rehabilitation program. It was hypothesized that nonopioid substance use disorders and opioid dosage would predict TOA.