Validation Assessment of Privacy-Preserving Synthetic Electronic Health Record Data: Comparison of Original Versus Synthetic Data on Real-World COVID-19 Vaccine Effectiveness.

PURPOSE: To assess the validity of privacy-preserving synthetic data by comparing results from synthetic versus original EHR data analysis. METHODS: A published retrospective cohort study on real-world effectiveness of COVID-19 vaccines by Maccabi Healthcare Services in Israel was replicated using synthetic data generated from the same source, and the results were compared between synthetic versus original datasets. The endpoints included COVID-19 infection, symptomatic COVID-19 infection and hospitalization due to infection and were also assessed in several demographic and clinical subgroups. In comparing synthetic versus original data estimates, several metrices were utilized: standardized mean differences (SMD), decision agreement, estimate agreement, confidence interval overlap, and Wald test. Synthetic data were generated five times to assess the stability of results. RESULTS: The distribution of demographic and clinical characteristics demonstrated very small difference (< 0.01 SMD). In the comparison of vaccine effectiveness assessed in relative risk reduction between synthetic versus original data, there was a 100% decision agreement, 100% estimate agreement, and a high level of confidence interval overlap (88.7%-99.7%) in all five replicates across all subgroups. Similar findings were achieved in the assessment of vaccine effectiveness against symptomatic COVID-19 Infection. In the comparison of hazard ratios for COVID 19-related hospitalization and odds ratio for symptomatic COVID-19 Infection, the Wald tests suggested no significant difference between respective effect estimates in all five replicates for all patient subgroups but there were disagreements in estimate and decision metrices in some subgroups and replicates. CONCLUSIONS: Overall, comparison of synthetic versus original real-world data demonstrated good validity and reliability. Transparency on the process to generate high fidelity synthetic data and assurances of patient privacy are warranted.

The Comparison of Newly Diagnosed Invasive Breast Patient Cohorts in Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative (GENIE-BPC) and Other Real-World Databases.

BACKGROUND: Oncology databases that integrate genomic and clinical data have become valuable resources for precision medicine. However, the generalizability of these databases has not been comprehensively assessed. OBJECTIVES: To describe the demographics, clinical characteristics, treatments, and overall survival of breast cancer cohorts in GENIE-BPC and three other databases. METHODS: This study utilized GENIE-BPC, SEER, SEER-Medicare, and Merative MarketScan Research Databases. Women with invasive breast cancer were identified through EHR, cancer registries or ICD-9/10-CM codes. The ages were 18+ years or per database requirement. Treatments were based on EHR or HCPCS/NDC codes in claims. Overall survival was estimated as time from diagnosis to death. RESULTS: Of female breast cancer patients in GENIE-BPC (n = 775), SEER (n = 548 336), SEER-Medicare (n = 68 914), and Marketscan (n = 109 499) databases, the median ages at initial diagnosis were 44, 62, 74, and 57 years, respectively. A greater proportion of patients in GENIE-BPC, compared to SEER/SEER-Medicare, had higher nuclear grades (%III-%IV: 57% vs. 26%/24%), advanced disease stage (%IV: 25.3% vs. 5%/3.6%), percent of triple negative breast cancer (19.7% vs. 10.2%/8.5%), and receipt of chemotherapy (85.0% vs. NA/22.3%). The 1-, 3-, and 5-year overall survival rates were lower in GENIE-BPC (78.5%, 60.5%, 55.5%) than in SEER (95.8%, 89.5%, 85.5%) and SEER-Medicare (91.6%, 81.4%, 75.0%). CONCLUSION: Breast cancer patients in GENIE-BPC were younger, had more advanced disease, had a higher proportion of triple negative breast cancer and recipients of chemotherapy, and had poorer overall survival. Researchers must use statistical adjustment when extrapolating results (e.g., biomarker prevalence) from GENIE-BPC to the larger breast cancer population.

Overview of global real-world data sources for pediatric pharmacoepidemiologic research.

PURPOSE: Given limited information available on real-world data (RWD) sources with pediatric populations, this study describes features of globally available RWD sources for pediatric pharmacoepidemiologic research. METHODS: An online questionnaire about pediatric RWD sources and their attributes and capabilities was completed by members and affiliates of the International Society for Pharmacoepidemiology and representatives of nominated databases. All responses were verified by database representatives and summarized. RESULTS: Of 93 RWD sources identified, 55 unique pediatric RWD sources were verified, including data from Europe (47%), United States (38%), multiregion (7%), Asia-Pacific (5%), and South America (2%). Most databases had nationwide coverage (82%), contained electronic health/medical records (47%) and/or administrative claims data (42%) and were linkable to other databases (65%). Most (71%) had limited outside access (e.g., by approval or through local collaborators); only 10 (18%) databases were publicly available. Six databases (11%) reported having >20 million pediatric observations. Most (91%) included children of all ages (birth until 18th birthday) and contained outpatient medication data (93%), while half (49%) contained inpatient medication data. Many databases captured vaccine information for children (71%), and one-third had regularly updated data on pediatric height (31%) and weight (33%). Other pediatric data attributes captured include diagnoses and comorbidities (89%), lab results (58%), vital signs (55%), devices (55%), imaging results (42%), narrative patient histories (35%), and genetic/biomarker data (22%). CONCLUSIONS: This study provides an overview with key details about diverse databases that allow researchers to identify fit-for-purpose RWD sources suitable for pediatric pharmacoepidemiologic research.

Describing diversity of real world data sources in pharmacoepidemiologic studies: The DIVERSE scoping review.

PURPOSE: Real-world evidence (RWE) is increasingly used for medical regulatory decisions, yet concerns persist regarding its reproducibility and hence validity. This study addresses reproducibility challenges associated with diversity across real-world data sources (RWDS) repurposed for secondary use in pharmacoepidemiologic studies. Our aims were to identify, describe and characterize practices, recommendations and tools for collecting and reporting diversity across RWDSs, and explore how leveraging diversity could improve the quality of evidence. METHODS: In a preliminary phase, keywords for a literature search and selection tool were designed using a set of documents considered to be key by the coauthors. Next, a systematic search was conducted up to December 2021. The resulting documents were screened based on titles and abstracts, then based on full texts using the selection tool. Selected documents were reviewed to extract information on topics related to collecting and reporting RWDS diversity. A content analysis of the topics identified explicit and latent themes. RESULTS: Across the 91 selected documents, 12 topics were identified: 9 dimensions used to describe RWDS (organization accessing the data source, data originator, prompt, inclusion of population, content, data dictionary, time span, healthcare system and culture, and data quality), tools to summarize such dimensions, challenges, and opportunities arising from diversity. Thirty-six themes were identified within the dimensions. Opportunities arising from data diversity included multiple imputation and standardization. CONCLUSIONS: The dimensions identified across a large number of publications lay the foundation for formal guidance on reporting diversity of data sources to facilitate interpretation and enhance replicability and validity of RWE.

Assessing Heterogeneity of Treatment Effect in Real-World Data.

Increasing availability of real-world data (RWD) generated from patient care enables the generation of evidence to inform clinical decisions for subpopulations of patients and perhaps even individuals. There is growing opportunity to identify important heterogeneity of treatment effects (HTE) in these subgroups. Thus, HTE is relevant to all with interest in patients' responses to interventions, including regulators who must make decisions about products when signals of harms arise postapproval and payers who make coverage decisions based on expected net benefit to their beneficiaries. Prior work discussed HTE in randomized studies. Here, we address methodological considerations when investigating HTE in observational studies. We propose 4 primary goals of HTE analyses and the corresponding approaches in the context of RWD: to confirm subgroup effects, to describe the magnitude of HTE, to discover clinically important subgroups, and to predict individual effects. We discuss other possible goals including exploring prognostic score- and propensity score-based treatment effects, and testing the transportability of trial results to populations different from trial participants. Finally, we outline methodological needs for enhancing real-world HTE analysis.

Enhancing Patient Centricity of Real-World Data Research: An Exploratory Analysis Using the Patient Experience Mapping Toolbox.

OBJECTIVES: There is an increasing expectation that medical product development and assessment be guided by patient input captured through patient engagement. Recently published consensus guidelines describe how qualitative patient experience data (PED) can guide the design, conduct, and translation of real-world research that reflects patients' lived experience. The objective of this exploratory analysis is to examine how researchers could leverage PED captured through the Patient Experience Mapping Toolbox (PEMT) to guide real-world data (RWD) research designs. METHODS: This exploratory analysis included a thematic analysis of interview transcripts collected while pilot testing the PEMT followed by a qualitative analysis of the emerging themes aligned with stages listed in the patient-centered real-world evidence, Real-World Research Design Framework. RESULTS: PED collected using the PEMT include information about symptomology, interactions with the healthcare system, information-seeking behavior, misdiagnoses, lifestyle changes, treatments, side effects, and comorbidities. This information can be leveraged at key study design decisions, including (1) identifying study cohorts and subgroups, (2) identifying exposures, (3) informing covariates and potential confounders; and (4) refining study periods. Additionally, participants described where they seek information about treatments and diseases, which should inform dissemination strategies. CONCLUSIONS: We identified opportunities for PED collected using the PEMT to inform RWD study designs. The PED described in this exploratory analysis stem from pilot testing of the PEMT across a variety of conditions. In the next phase of development in this area, researchers should evaluate how data collected using the PEMT can be applied to RWD research for a specific disease.

Developing Patient-Centered Real-World Evidence: Emerging Methods Recommendations From a Consensus Process.

OBJECTIVES: The Joint ISPOR-ISPE Special Task Force on Real-World Evidence included patient/stakeholder engagement as a recommended good procedural practice when designing, conducting, and disseminating real-world evidence (RWE). However, there are no guidelines describing how patient experience data (PED) can be applied when designing real-world data (RWD) studies. This article describes development of consensus recommendations to guide researchers in applying PED to develop patient-centered RWE. METHODS: A multidisciplinary advisory board, identified through recommendations of collaborators, was established to guide development of recommendations. Semistructured interviews were conducted to identify how experienced RWD researchers (n = 15) would apply PED when designing a hypothetical RWD study. Transcripts were analyzed and emerging themes developed into preliminary methods recommendations. An eDelphi survey (n = 26) was conducted to refine/develop consensus on the draft recommendations. RESULTS: We identified 13 recommendations for incorporating PED throughout the design, conduct, and translation of RWE. The recommendations encompass themes related to the development of a patient-centered research question, designing a study, disseminating RWE, and general considerations. For example, consider how patient input can inform population/subgroups, comparators, and study period. Researchers can leverage existing information describing PED and may be able to apply those insights to studies relying on traditional RWD sources and/or patient registries. CONCLUSIONS: Applying these emerging recommendations may improve the patient centricity of RWE through improved relevance of RWE to patient communities of interest and foster greater multidisciplinary participation and transparency in RWD research. As researchers gather experience by applying the methods recommendations, further refinement of these consensus recommendations may lead to "best practices."

Molecular analysis and favorable clinical outcomes in real-world patients with metastatic renal cell carcinoma.

BACKGROUND: Prior biomarker studies have mainly been restricted to advanced RCC patients treated in clinical trials or have had limited integration of immunotherapy features such as programmed death ligand (PD-L)-1 with gene expression signatures intended to capture other canonical pathways to confirm their prognostic value. MATERIAL AND METHODS: PD-L1 and PD-L2 by immunohistochemistry (IHC), PD-L2 messenger RNA (mRNA), and 10 gene expression profile (GEP) signatures targeting immune, angiogenesis and canonical pathways were analyzed in nephrectomy specimens from 227 advanced clear cell RCC (ccRCC) and 42 non-clear cell RCC (nccRCC) patients treated with targeted therapies including VEGF and mTOR inhibitors. Biomarker association with best overall response (BOR), progression-free survival (PFS), and overall survival (OS) were evaluated using multivariable modeling. Except for PD-L1 IHC and angiogenesis, tested with a nominal p-value of .05, multiplicity control was applied with a 0.1 significance level given limited experience in this setting. RESULTS: The strongest biomarker correlations were observed for hypoxia inducible factor (HIF)-2a and angiogenesis signatures (rho = 0.860 [ccRCC], 0.819 [nccRCC]); hypoxia and glycolysis signatures (rho = 0.943 [ccRCC], 0.973 [nccRCC]); PD-L2 mRNA and T-cell-inflamed GEP signatures (rho = 0.764 [ccRCC], 0.897 [nccRCC]); and PD-L2 mRNA and monocytic myeloid-derived suppressor cell signature (rho = 0.787 [ccRCC], 0.815 [nccRCC]). For ccRCC, higher angiogenesis expression was associated with improved BOR (OR:2.85 [95%CI:1.37, 5.93]), longer PFS (HR:0.61 [95%CI:0.45, 0.82]) and OS (HR:0.74 [95%CI:0.54, 1.00]); higher PD-L1 expression with shorter OS (HR:1.44 [95%CI:1.01, 2.07]). For nccRCC, there was more than a two-fold increased risk with longer OS associated with lower angiogenesis (HR:2.43 [95%CI:1.04, 5.68]), glycolysis (HR:7.03 [95%CI:1.51, 32.76]) and hypoxia (HR:8.83 [95%CI:1.69, 46.05]) gene signature expression. CONCLUSION: Data pointed at PD-L1 IHC and angiogenesis expression in ccRCC and hypoxia, glycolysis, and angiogenesis expression in nccRCC as potential prognostic factors. These findings may have implications for the design and interpretation of advanced RCC trials and to identify potential targets for combination therapy strategies.

Real-world evidence to support regulatory decision-making for medicines: Considerations for external control arms.

Randomized clinical trials (RCTs) are the gold standard in producing clinical evidence of efficacy and safety of medical interventions. More recently, a new paradigm is emerging-specifically within the context of preauthorization regulatory decision-making-for some novel uses of real-world evidence (RWE) from a variety of real-world data (RWD) sources to answer certain clinical questions. Traditionally reserved for rare diseases and other special circumstances, external controls (eg, historical controls) are recognized as a possible type of control arm for single-arm trials. However, creating and analyzing an external control arm using RWD can be challenging since design and analytics may not fully control for all systematic differences (biases). Nonetheless, certain biases can be attenuated using appropriate design and analytical approaches. The main objective of this paper is to improve the scientific rigor in the generation of external control arms using RWD. Here we (a) discuss the rationale and regulatory circumstances appropriate for external control arms, (b) define different types of external control arms, and (c) describe study design elements and approaches to mitigate certain biases in external control arms. This manuscript received endorsement from the International Society for Pharmacoepidemiology (ISPE).

Hispanic Residential Isolation, ADHD Diagnosis and Stimulant Treatment among Medicaid-Insured Youth.

OBJECTIVE: This study aimed to evaluate a conceptual framework that assessed the effect of Hispanic residential isolation on Attention Deficit Hyperactivity Disorder (ADHD) health service utilization among 2.2 million publicly insured youth. DESIGN: Cross-sectional. SETTING: Medicaid administrative claims data for ambulatory care services from a US Pacific state linked with US census data. PARTICIPANTS: Youth, aged 2-17 years, continuously enrolled in 2009. MAIN OUTCOME MEASURES: The percent annual prevalence and odds of ADHD diagnosis and stimulant use according to two measures of racial/ethnic residential isolation: 1) the county-level Hispanic isolation index (HI) defined as the population density of Hispanic residents in relation to other racial/ethnic groups in a county (<.5; .5-.64; ≥.65); and 2) the proportion of Hispanic residents in a ZIP code tabulation area (<25%; 25%-50%; >50%). RESULTS: Among the 47,364 youth with a clinician-reported ADHD diagnosis, 60% received a stimulant treatment (N = 28,334). As the county level HI increased, Hispanic residents of ethnically isolated locales were significantly less likely to receive an ADHD diagnosis (adjusted odds ratio [AOR]=.92 [95% CI=.88-.96]) and stimulant use (AOR=.61 [95% CI=.59-.64]) compared with Hispanic youth in less isolated areas. At the ZIP code level, a similar pattern of reduced ADHD diagnosis (AOR=.81 [95% CI=.77-.86]) and reduced stimulant use (AOR=.65 [95% CI=.61-.69]) was observed as Hispanic residential isolation increased from the least isolated to the most isolated ZIP code areas. CONCLUSIONS: These findings highlight the opportunity for Big Data to advance mental health research on strategies to reduce racial/ethnic health disparities, particularly for poor and vulnerable youth. Further exploration of racial/ethnic residential isolation in other large data sources is needed to guide future policy development and to target culturally sensitive interventions.

Antipsychotic prescribing for behavioral disorders in US youth: physician specialty, insurance coverage, and complex regimens.

PURPOSE: To assess antipsychotic prescribing patterns according to insurance coverage type and physician specialty in the outpatient treatment of behavioral disorders (BD) in US youth. METHODS: We used 2003-2010 National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey data to compare antipsychotic prescribing in the outpatient treatment of BD in youth (6-19 years) according to insurance coverage (public vs. private) and physician specialty (psychiatrist vs. non-psychiatrist) using population-weighted Chi-square and multivariable analyses. Also, we examined co-prescribing of antipsychotics with other psychotropic medication classes. Subgroup analyses were conducted in BD visits with no other clinician-reported psychiatric diagnosis (non-comorbid BD visits). RESULTS: A large majority (71.0%) of BD visits were provided by non-psychiatrists. However, psychiatrists prescribed antipsychotics far more frequently than non-psychiatrists (24.2% vs. 4.6%; adjusted odds ratio (AOR) = 5.1 [95% confidence interval (CI), 2.8-9.2]) in total BD visits as well as in non-comorbid BD visits (18.6% vs. 3.6%; AOR = 5.8 [95% CI, 3.2-10.5]). Antipsychotic prescribing was nearly two-fold greater in visits by publicly insured 6-12 year olds (11.3% vs. 5.8%; AOR = 1.9 [95% CI, 1.1-3.5]) and 13-19 year olds (16.2% vs. 8.9%; AOR = 2.0 [95% CI, 1.1-3.6]) compared with their privately insured counterparts. In more than one-third of antipsychotic-prescribed BD visits, antipsychotics were prescribed concomitantly with ≥2 psychotropic medication classes regardless of age group, insurance coverage, or even in the absence of psychiatric comorbidities. CONCLUSION: In outpatient visits by youth for BD, antipsychotics were primarily prescribed by psychiatrists, concomitantly, and for the publicly insured. These treatment patterns merit further investigation.

Construct validity and factor structure of survey-based assessment of cost-related medication burden.

BACKGROUND: Millions of Americans are burdened by out-of-pocket prescription costs. Although many survey measures have been developed to assess this burden, the construct validity and the factor structure of these instruments have not been rigorously assessed. OBJECTIVES: To characterize the factor structure and the construct validity of items assessing cost-related medication burden. METHODS: We applied exploratory factor and confirmatory factor analyses to the 2009 Medicare Current Beneficiary Survey, focusing on 10 items assessing cost-related mediation burden among a nationally representative sample of community-dwelling Medicare beneficiaries. The fit of competing models was compared using several indices. RESULTS: The study population (N=8777) was predominantly aged over 65 years (83.3%), female (54.4%), and white (84.3%). Two distinct factors were present for the medication cost-reduction strategies: (1) cost-related medication nonadherence and (2) drug-shopping behaviors, not directly impacting medication compliance. The two factors were moderately correlated (r=0.55), highlighting the presence of a 2 distinct but related constructs for cost-related medication burden. An item assessing the use of mail or internet pharmacies did not load well on either factor and may not necessarily measure medication-related cost burden. An item assessing reduced spending on basic needs loaded strongly on the same factor with the cost-related medication nonadherence items, suggesting they together may represent extreme compensatory behaviors that may adversely affect health outcomes. CONCLUSIONS: Two distinct constructs were derived from these items examining cost-related medication burden. Although cost-related medication burden is often associated with nonadherence, drug-shopping behaviors that do not directly impact adherence are also important measure of this burden.

Real-world evidence to support regulatory submissions: A landscape review and assessment of use cases.

Real-world evidence (RWE) has an increasing role in preapproval settings to support the approval of new medicines and indications. The main objectives of this study were to identify and characterize regulatory use cases that utilized RWE and other related observational approaches through targeted review of publications and regulatory review documents. After screening and inclusion/exclusion, the review characterized 85 regulatory applications with RWE. A total of 31 were in oncology and 54 were in non-oncology therapeutic areas. Most were for indications in adults only (N = 42, 49.4%), while 13 were in pediatrics only (15.3%), and 30 were in both (35.3%). In terms of regulatory context, 59 cases (69.4%) were for an original marketing application, 24 (28.2%) were for label expansion, and 2 (2.4%) were for label modification. Most also received special regulatory designations (e.g., orphan indication, breakthrough therapy, fast track, conditional, and accelerated approvals). There were 42 cases that utilized RWE to support single-arm trials. External data to support single-arm trials were utilized in various ways across use cases, including direct matching, benchmarking, natural history studies as well as literature or previous trials. A variety of data sources were utilized, including electronic health records, claims, registries, site-based charts. Endpoints in oncology use cases commonly included overall survival, progression-free survival. In 13 use cases, RWE was not considered supportive/definitive in regulatory decision-making due to design issues (e.g., small sample size, selection bias, missing data). Overall, RWE is utilized in regulatory approval processes for new indications/label expansion across various therapeutic areas with wide range of approaches. Multifaceted cross-sector efforts are needed to further improve the quality and utility of RWE in regulatory decision-making.

Real-world prevalence of homologous recombination repair mutations in advanced prostate cancer: an analysis of two clinico-genomic databases.

BACKGROUND: Homologous recombination repair mutation (HRRm) status may guide risk-stratification and treatment decisions, including polyadenosine diphosphate-ribose polymerase inhibitor use, in advanced prostate cancer. Although HRRm prevalence has been reported in single-institution studies or clinical trials, real-world HRRm prevalence in diverse populations is unknown. We describe HRRm in the clinical setting using two real-world clinicogenomic databases: the Flatiron Health and Foundation Medicine, Inc. Clinico-Genomic Database (CGDB), a national electronic health record-derived database, and the American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange (GENIE). METHODS: This cross-sectional analysis included 3757 individuals diagnosed with prostate cancer who had next generation sequencing (NGS) as standard of care. The CGDB included men with advanced/metastatic prostate cancer and genetic data included both germline and somatic pathogenic mutations. The GENIE analysis included men with prostate cancer whose received NGS as standard of care, but the data were filtered to include somatic mutations only. Due to key differences among databases, direct comparisons were not possible. Overall prevalence of HRRm was calculated and stratified by demographic and clinical characteristics. RESULTS: HRRm prevalence (combined germline and somatic) in CGDB (n = 487) was 24.6% (95% CI 20.9-28.7%), with no major differences across demographic and disease characteristic subgroups. HRRm prevalence (somatic) in GENIE (n = 3270) was 11.0% (95% CI 10.0-12.1%), which varied between 9.5% and 18.4% across treatment centers. CONCLUSIONS: Approximately one-quarter of patients with advanced/metastatic prostate cancer in the CGDB had germline and/or somatic HRRm, which is consistent with clinical trials such as the PROfound study that used a similar NGS platform and algorithm to define HRRm. In the GENIE database, HRRm prevalence varied by treatment center or NGS platform. More research is needed to understand real-world HRRm prevalence variations.

Temporal changes in treatment patterns by age group and functional status before and after PD-1/L1 inhibitor approvals in advanced urothelial carcinoma.

Introduction: Metastatic urothelial carcinoma (mUC) has poor prognosis. A high unmet need exists for novel treatment for those who are unfit for platinum-based chemotherapy. Methods: We aimed to describe real-world temporal changes in patient characteristics and 1L treatment selection for mUC patients in the United States following the approval of anti-PD-1/L1 treatments. This study was a retrospective, observational study using anonymized and structured oncology electronic medical record (EMR) data from IQVIA and the US Oncology Network iKnowMed (USON). Results: After approval of 1L anti-PD-1/L1 treatment for mUC, there is a marked increase in the use of 1L anti-PD-1/L1 monotherapies, accompanied by a proportional decrease in 1L platinum-based treatments and non-guideline-based therapy; particularly among the elderly (> 75 years) and those with poor ECOG performance status (ECOG PS 2+). Discussion: Anti-PD-1/L1 monotherapies fulfill the prior unmet need of frail mUC patients who are ineligible for platinum-based therapies.

Noninterventional studies in the COVID-19 era: methodological considerations for study design and analysis.

The global COVID-19 pandemic has generated enormous morbidity and mortality, as well as large health system disruptions including changes in use of prescription medications, outpatient encounters, emergency department admissions, and hospitalizations. These pandemic-related disruptions are reflected in real-world data derived from electronic medical records, administrative claims, disease or medication registries, and mobile devices. We discuss how pandemic-related disruptions in healthcare utilization may impact the conduct of noninterventional studies designed to characterize the utilization and estimate the effects of medical interventions on health-related outcomes. Using hypothetical studies, we highlight consequences that the pandemic may have on study design elements including participant selection and ascertainment of exposures, outcomes, and covariates. We discuss the implications of these pandemic-related disruptions on possible threats to external validity (participant selection) and internal validity (for example, confounding, selection bias, missing data bias). These concerns may be amplified in populations disproportionately impacted by COVID-19, such as racial/ethnic minorities, rural residents, or people experiencing poverty. We propose a general framework for researchers to carefully consider during the design and analysis of noninterventional studies that use real-world data from the COVID-19 era.

A Framework for Extension Studies Using Real-World Data to Examine Long-Term Safety and Effectiveness.

Understanding the long-term benefits and risks of treatments, devices, and vaccines is critically important for individual- and population-level healthcare decision-making. Extension studies, or 'roll-over studies,' are studies that allow for patients participating in a parent clinical trial to 'roll-over' into a subsequent related study to continue to observe and measure long-term safety, tolerability, and/or effectiveness. These designs are not new and are often used as an approach to satisfy regulatory post-approval safety requirements. However, designs using traditional clinical trial infrastructure can be expensive and burdensome to conduct, particularly, when following patients for many years post trial completion. Given the increasing availability and access of real-world data (RWD) sources, direct-to-patient technologies, and novel real-world study designs, there are more cost-efficient approaches to conducting extension studies while assessing important long-term outcomes. Here, we describe various fit-for-purpose design options for extension studies, discuss related methodological considerations, and provide scientific and operational guidance on practices when planning to conduct an extension study using RWD. This manuscript is endorsed by the International Society for Pharmacoepidemiology (ISPE).

Regulator-Requested Non-Interventional Postauthorization Safety and Effectiveness Studies for Oncology Drugs: A Systematic Review.

There has been a growing number of oncology drug approvals. Non-interventional postauthorization safety/effectives studies (PASSs/PAESs) aim to provide real-world evidence on the safety/effectiveness of oncology drugs postapproval. To understand the current landscape, a comprehensive search as of March 1, 2021, was conducted in major register/databases. We found that requested studies increased from 1 in 2006-2010 to 47 in 2016-2020. Of 78 total studies identified, 50 focused on safety/risk assessment (64.1%), 6 on effectiveness (7.7%), 3 on drug utilization (3.8%), 1 on disease epidemiology (1.3%), and 18 on effectiveness of additional risk minimization measures (23.1%). For safety/risk assessment studies, 58.9% focused on nonspecific end points (e.g., frequency of adverse events). For effectiveness studies, the leading primary outcome was overall survival. Overall, safety/risk assessment studies concerning nonspecific end points for vascular endothelial growth factor (receptor) inhibitors were most requested. Regarding data sources, though a majority (71.8%) used primary data collection, a growing proportion utilized secondary data sources. Among 23 studies with information available on study design, 10 (43.5%) were single-arm cohort studies, 9 (39.1%) were cross-sectional studies, 3 (13.1%) were comparative cohort studies, and 1 (4.3%) was a nested-case-control study. In conclusion, there was an increasing number of oncology-specific non-interventional PASSs/PAESs, with a majority on safety/risk assessment. Although most utilized primary data collection, there was an increasing use of secondary real-world data sources. Few conducted comparative analyses, and most used single-arm designs. Future efforts are needed to assess how findings of these studies would impact regulatory decisions and improve knowledge of toxicity for clinical/translational development.

Pim-1 kinase protects P-glycoprotein from degradation and enables its glycosylation and cell surface expression.

The oncogenic serine/threonine kinase Pim-1 phosphorylates and activates the ATP-binding cassette transporter breast cancer resistance protein (ABCG2). The ABC transporter P-glycoprotein (Pgp; ABCB1) also contains a Pim-1 phosphorylation consensus sequence, and we hypothesized that Pim-1 also regulates Pgp. Pgp is exported from the endoplasmic reticulum (ER) as a 150-kDa species that is glycosylated to 170-kDa Pgp, translocates to the cell surface, and mediates drug efflux; alternatively, 150-kDa Pgp is cleaved to a 130-kDa proteolytic product by ER proteases or undergoes ubiquitination and proteasomal degradation. Pim-1 and Pgp interaction was studied in GST pull-down and phosphorylation in in vitro kinase assays. Pim-1 knockdown and inhibition effects on Pgp expression were studied by immunoblotting and flow cytometry and on Pgp stability by immunoblotting after cycloheximide treatment. Pim-1 directly interacted with and phosphorylated Pgp in intact cells and in vitro. Pim-1 knockdown or inhibition decreased cellular and cell surface 170-kDa Pgp, in association with both transient increase in 130-kDa Pgp and increased Pgp ubiquitination and proteasomal degradation. Pim-1 inhibition also decreased expression of 150-kDa Pgp in the presence of the glycosylation inhibitor 2-deoxy-d-glucose. Finally, Pim-1 inhibition sensitized Pgp-overexpressing cells to doxorubicin. Thus, Pim-1 regulates Pgp expression by protecting 150-kDa Pgp from proteolytic and proteasomal degradation and enabling Pgp glycosylation and cell surface translocation and thus Pgp-mediated drug efflux. Pim-1 inhibitors are entering clinical trials and may provide a novel approach to abrogating drug resistance.