Examples of ADE Surveillance Systems MedDRA ® Processing of Adverse Event Reports in ADE Surveillance Systems Amarilys Vega, M.D, M.P.H., Sonja Brajovic,

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Presentation transcript:

Examples of ADE Surveillance Systems MedDRA ® Processing of Adverse Event Reports in ADE Surveillance Systems Amarilys Vega, M.D, M.P.H., Sonja Brajovic, M.D., Jung Lee, RPh, Mark Vieder, RPh., Bane Bradic, M.D., PSI International, Inc., USA Data Coding and Coding Quality Control  Develop and implement coding and quality control guidelines Safety Signal Generation  Reconcile and compare clinical trials and postmarketing safety data  Search organization’s safety data and data from other sources for potential signals (i.e., data mining) Safety Signal Evaluation Actions  Assess clinical relevance of safety signal  Take the necessary steps to improve drug safety Descriptive Epidemiology  Describe and summarize all available information pertaining to the adverse event of interest and the suspect product Objective: To describe the application of the Medical Dictionary for Regulatory Activities terminology (MedDRA ® ) in the drug safety surveillance process by providing an overview of the different phases of this process and examples of surveillance systems that employ MedDRA ®. Analytic Epidemiology  Verify identified safety signals by means of observational and/or experimental epidemiological studies Data Collection, Entry, and Storage  Collect, enter, and store in database detailed safety data obtained from all possible venues VHA PBM ADE Program ( Veterans Health Administration Pharmacy Benefits Management Adverse Drug Event Database) Passive surveillance system which collects spontaneous adverse event data from all VA medical centers and is managed by the PBM VHA office Coding Guidelines and Coding Practices: Impact on the Accuracy, Consistency & Uniformity in MedDRA ® Coding Example of an Adverse Event Narrative A patient started a new antibiotic for the treatment of a complicated urinary tract infection 3 days ago. He took a double dose last night by mistake. Today he reports markedly increased blood glucose with high urinary glucose. Prior to this, the patient has been stable on once daily oral anti-diabetics. Coding * by Organization A 1. LLT Incorrect dose administered PT Incorrect dose administered SOC Injury, Poisoning and Procedural Complications 2. LLT Loss of control of blood sugar PT Diabetes mellitus inadequate control SOC Endocrine Disorders/ SOC Metabolism and Nutrition Disorders 1. LLT Incorrect dose administered PT Incorrect dose administered SOC Injury, Poisoning and Procedural Complications 2. LLT Blood glucose increased PT Blood glucose increased SOC Investigations 3. LLT Glucose urine high PT Glucose urine present SOC Investigations 4. LLT Medication Error PT Medication Error SOC Injury, Poisoning and Procedural Complications 1. LLT Incorrect dose administered PT Incorrect dose administered SOC Injury, Poisoning and Procedural Complications 2. LLT Diabetes mellitus aggravated PT Diabetes mellitus SOC Endocrine Disorders/ SOC Metabolism and Nutrition Disorders Coded in Other Terminologies MedDRA ® Conversion Clinical Trials Data Clinical Trials Data MedDRA® Coded Data Organization’s Postmarketing Safety Data Compare data from these sources and determine which combination of MedDRA® terms suggest a potential safety signal for a particular product Other Sources of Safety Data + NEISS-CADES (National Electronic Injury Surveillance System -Cooperative Adverse Drug Event Surveillance)* Active surveillance system which collects adverse reaction data from patients’ records in a nationally representative sample of hospital emergency rooms. Case 1Case 2Case 3Case 4Case n Create a Case Series Create a “Case Definition” Using MedDRA ® Terms Identify cases of interest in large external databases (other standard terminologies are bridged to MedDRA ® ) Observational Studies Experimental Studies Verify Safety Signal At each participating hospital emergency room, Center for Disease Control and Prevention (CDC)/Consumer Product Safety Commission (CPSC) trained coders review all patient records in search for adverse drug events. Data on relevant cases, including codes for injuries and mechanisms of injury, are entered into a standardized database and subsequently processed by a contractor who codes this information using MedDRA ® (MMWR, April 22, 2005 / 54(15); ; Ann Emerg Med. 2005;45: ). Coding guidelines developed based on MedDRA ® Term Selection: Points to Consider document and VA’s specific objectives. The goal is to capture in MedDRA ® terms adverse event data as close to the reporter’s verbatim as possible. MedDRA ® coding is applied to the stated Indications for Treatment, Medical History, Adverse Events, and Laboratory results not represented by the Diagnosis and Medical History. In process of developing standardized methods to process and evaluate aggregate safety data. Currently undergoing further development and evaluation to determine extent of use as a tool in drug safety surveillance. Organization's Specific Coding Guidelines This process should be guided by the ICH endorsed MedDRA ® Term Selection: Points to Consider document and the organization’s specific objectives Coding * by Organization B Coding * by Organization C Drug Safety Surveillance Process Overview MedDRA ® Application and Challenges FDA AERS (Food and Drug Administration Adverse Event Reporting System) Passive surveillance system which collects spontaneous adverse event data submitted by manufacturers and directly by consumers and health professionals. Coding guidelines developed based on ICH endorsed MedDRA ® Term Selection: Points to Consider document and FDA’s coding principles. The goal is to capture medical concepts described in the narrative and translate them into suitable MedDRA ® terms. Coding guidelines and practices are regularly reevaluated and modified according to FDA’s needs and requirements. MedDRA ® coding accuracy is monitored by a continuous quality assurance process. Safety data collected during clinical trials are incorporated into the product’s approved label. FDA reviewers monitor products’ safety profiles. They search for safety signals by reviewing AERS data, case reports found in medical literature, and data from other passive and active surveillance systems. Most of these data are coded in MedDRA ®. One of the tools employed by the FDA to identify safety signals is data mining. In-depth knowledge of MedDRA ® required for effective data mining. Reviewers: Create a case definition using MedDRA ® terms that describe the clinical process of interest and create a search group containing all possible names given to the suspect product. Create a case series by retrieving from AERS all cases fulfilling case and product definitions. Add literature cases to case series. Evaluate raw data from individual case reports and extract all relevant case data stratifying information as necessary. Provide a clinical assessment of the findings based on the nature of the disease under treatment and adverse event characteristics. Collected data must be as complete and detailed as possible to facilitate clinical interpretation, MedDRA ® coding, and data retrieval and analysis. Duplicate reports and follow up data must be carefully handled. Employ information technology tools that will support this phase as well as other phases of the Drug Safety Surveillance process. Clinical Trials Data + + Organization’s Safety Data Data Retrieval Other Sources of Safety Data (i.e., medical literature, WHO) Clinical assessment Summarize all case information Obtain adverse event’s typical characteristics data Enhance dataset by abstracting additional information Obtain disease natural history data When possible, code in MedDRA ® Descriptive Epidemiology Studies In-depth analysis Currently undergoing further development and evaluation to determine extent of use as a tool in drug safety surveillance. Regulatory actions Develop product- specific Risk Management plan Assess safety issue’s impact on patient support and disease management programs Assess impact on product marketing Make recommendations on how to improve MedDRA® Terminology Scientists from within FDA and from other organizations conduct experimental and observational studies (large population- based databases). Use of MedDRA ® depends on the characteristics of the study database and the existence of terminology bridges between MedDRA ® and study database’s particular terminology (ICD, SNOMED, etc.). FDA provides: Continuous assessment of new safety data and it’s impact on patient safety. Drug safety surveillance process guidelines. MedDRA ® terminology improvement recommendations. In process of developing standardized methods to process and evaluate aggregate safety data. Additional MedDRA ® encoded data facilitates search for potential safety signals and their interpretation. In process of developing standardized methods to evaluate aggregate safety data. * MedDRA version 8.0 ** A Center for Disease Control and Prevention (CDC), Consumer Product Safety Commission (CPSC), and Food and Drug Administration (FDA) joint project