Dataset Information

Real-world Overall Survival Using Oncology Electronic Health Record Data: Friends of Cancer Research Pilot.

ABSTRACT: In prior work, Friends of Cancer Research convened multiple data partners to establish standardized definitions for oncology real-world end points derived from electronic health records (EHRs) and claims data. Here, we assessed the performance of real-world overall survival (rwOS) from data sets sourced from EHRs by evaluating the ability of the end point to reflect expected differences from a previous randomized controlled trial across five data sources, after applying inclusion/exclusion criteria. The KEYNOTE-189 clinical trial protocol of platinum doublet chemotherapy (chemotherapy) vs. programmed cell death protein 1 (PD-1) in combination with platinum doublet chemotherapy (PD-1 combination) in first-line nonsquamous metastatic non-small cell lung cancer guided retrospective cohort selection. The Kaplan-Meier product limit estimator was used to calculate 12-month rwOS with 95% confidence intervals (CIs) in each data source. Cox proportional hazards models estimated hazard ratios (HRs) and associated 95% CIs, controlled for prognostic factors. Once the inclusion/exclusion criteria were applied, the five resulting data sets included 155 to 1,501 patients in the chemotherapy cohort and 36 to 405 patients in the PD-1 combination cohort. Twelve-month rwOS ranged from 45% to 58% in the chemotherapy cohort and 44% to 68% in the PD-1 combination cohort. The adjusted HR for death ranged from 0.80 (95% CI: 0.69, 0.93) to 1.15 (95% CI: 0.71, 1.85), controlling for age, gender, performance status, and smoking status. This study yielded insights regarding data capture, including ability of real-world data to precisely identify patient populations and the impact of criteria on end points. Sensitivity analyses could elucidate data set-specific factors that drive results.

SUBMITTER: Lasiter L

PROVIDER: S-EPMC9298266 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Real-world Overall Survival Using Oncology Electronic Health Record Data: Friends of Cancer Research Pilot.

Lasiter Laura L Tymejczyk Olga O Garrett-Mayer Elizabeth E Baxi Shrujal S Belli Andrew J AJ Boyd Marley M Christian Jennifer B JB Cohen Aaron B AB Espirito Janet L JL Hansen Eric E Sweetnam Connor C Robert Nicholas J NJ Small Mackenzie M Stewart Mark D MD Izano Monika A MA Wagner Joseph J Natanzon Yanina Y Rivera Donna R DR Allen Jeff J

Clinical pharmacology and therapeutics 20211102 2

In prior work, Friends of Cancer Research convened multiple data partners to establish standardized definitions for oncology real-world end points derived from electronic health records (EHRs) and claims data. Here, we assessed the performance of real-world overall survival (rwOS) from data sets sourced from EHRs by evaluating the ability of the end point to reflect expected differences from a previous randomized controlled trial across five data sources, after applying inclusion/exclusion crite ...[more]

PMID: 34655228

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Project description:PurposeNeuroBlu is a real-world data (RWD) repository that contains deidentified electronic health record (EHR) data from US mental healthcare providers operating the MindLinc EHR system. NeuroBlu enables users to perform statistical analysis through a secure web-based interface. Structured data are available for sociodemographic characteristics, mental health service contacts, hospital admissions, International Classification of Diseases ICD-9/ICD-10 diagnosis, prescribed medications, family history of mental disorders, Clinical Global Impression-Severity and Improvement (CGI-S/CGI-I) and Global Assessment of Functioning (GAF). To further enhance the data set, natural language processing (NLP) tools have been applied to obtain mental state examination (MSE) and social/environmental data. This paper describes the development and implementation of NeuroBlu, the procedures to safeguard data integrity and security and how the data set supports the generation of real-world evidence (RWE) in mental health.ParticipantsAs of 31 July 2021, 562 940 individuals (48.9% men) were present in the data set with a mean age of 33.4 years (SD: 18.4 years). The most frequently recorded diagnoses were substance use disorders (1 52 790 patients), major depressive disorder (1 29 120 patients) and anxiety disorders (1 03 923 patients). The median duration of follow-up was 7 months (IQR: 1.3 to 24.4 months).Findings to dateThe data set has supported epidemiological studies demonstrating increased risk of psychiatric hospitalisation and reduced antidepressant treatment effectiveness among people with comorbid substance use disorders. It has also been used to develop data visualisation tools to support clinical decision-making, evaluate comparative effectiveness of medications, derive models to predict treatment response and develop NLP applications to obtain clinical information from unstructured EHR data.Future plansThe NeuroBlu data set will be further analysed to better understand factors related to poor clinical outcome, treatment responsiveness and the development of predictive analytic tools that may be incorporated into the source EHR system to support real-time clinical decision-making in the delivery of mental healthcare services.

Project description:IntroductionHyperkalemia is often managed in the emergency department (ED) and it is important to understand how ED management and post-discharge outcomes vary by hyperkalemia severity. This study was conducted to characterize ED management and post-discharge outcomes across hyperkalemia severities.MethodsAdults with an ED visit with hyperkalemia (at least one serum potassium lab measure above 5.0 mEq/L) were selected from US electronic medical record data (2012-2018). Patient characteristics, potassium levels, treatments, and monitoring prior to and during the ED visit were compared by hyperkalemia severity (mild [> 5.0-5.5 mEq/L], moderate [> 5.5-6.0], severe [> 6.0]) using unadjusted analyses. Death, immediate inpatient admission, 30-day hyperkalemia recurrence, and 30-day inpatient admission were also assessed by severity.ResultsOf 6222 patients included, 4432 (71.2%) had mild hyperkalemia, 1085 (17.4%) had moderate, and 705 (11.3%) had severe hyperkalemia. Chronic kidney disease (39.9-50.1%) and heart failure (21.6-24.3%) were common. In the ED, electrocardiograms (mild, 56.5%; moderate, 69.6%; severe, 81.0%) and patients with at least two potassium laboratory values increased with severity (15.0%; 40.4%; 75.5%). Among patients with at least two potassium laboratory values, over half of patients (60.4%) had potassium levels ≤ 5.0 mEq/L prior to discharge. Use of potassium-binding treatments (sodium polystyrene sulfonate: mild = 4.1%; moderate = 17.1%; severe = 27.4%), temporizing agents (5.6%; 15.5%; 31.6%), or dialysis (0.4%; 0.8%; 3.0%) increased with severity; treatment at discharge was not common. Death (1.1%; 3.7%; 10.6%), immediate admission to inpatient care (5.8%; 8.7%; 12.7%), 30-day hyperkalemia recurrence (2.9%; 19.0%; 32.5%), 30-day inpatient admission with hyperkalemia (6.5%; 7.9%; 9.3%) also increased with severity.ConclusionPatients with moderate and severe hyperkalemia experienced elevated risk of hyperkalemia recurrence and hyperkalemia-related inpatient readmission following discharge from the ED from a descriptive analysis. Future research to assess strategies to reduce hyperkalemia recurrence and inpatient admission in this patient population would be beneficial.

Dataset Information

Real-world Overall Survival Using Oncology Electronic Health Record Data: Friends of Cancer Research Pilot.

Publications

Real-world Overall Survival Using Oncology Electronic Health Record Data: Friends of Cancer Research Pilot.

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