MedDRA Safety Data Analysis and SMQs

Transcription

1 MedDRA Safety Data Analysis and SMQs

2 MedDRA: Safety Data Analysis and SMQs MedDRA was developed under the auspices of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH). The activities of the MedDRA Maintenance and Support Services Organization (MSSO) are overseen by an ICH MedDRA Management Board, which is composed of the six ICH parties (EU, EFPIA, MHLW, JPMA, FDA, PhRMA), the Medicines and Healthcare products Regulatory Agency (MHRA) of the UK, Health Canada, and the WHO (as Observer)

3 Disclaimer and Copyright Notice This presentation is protected by copyright and may be used, reproduced, incorporated into other works, adapted, modified, translated or distributed under a public license provided that ICH's copyright in the presentation is acknowledged at all times. In case of any adaption, modification or translation of the presentation, reasonable steps must be taken to clearly label, demarcate or otherwise identify that changes were made to or based on the original presentation. Any impression that the adaption, modification or translation of the original presentation is endorsed or sponsored by the ICH must be avoided. The presentation is provided "as is" without warranty of any kind. In no event shall the ICH or the authors of the original presentation be liable for any claim, damages or other liability arising from the use of the presentation. The above-mentioned permissions do not apply to content supplied by third parties. Therefore, for documents where the copyright vests in a third party, permission for reproduction must be obtained from this copyright holder Course Overview In this course, we will cover: MedDRA overview MedDRA Data Retrieval and Presentation: Points to Consider document Developing queries using MedDRA Examples and hands-on exercises

4 Course Overview (cont) In this course, we will cover (cont): SMQ background and definition SMQs development status SMQ data characteristics SMQ testing and production maintenance SMQ versioning SMQ applications Customized searches MedDRA Overview 3

5 MedDRA Definition MedDRA is a clinically-validated international medical terminology used by regulatory authorities and the regulated biopharmaceutical industry. The terminology is used through the entire regulatory process, from pre-marketing to post-marketing, and for data entry, retrieval, evaluation, and presentation Where MedDRA is Used Regulatory Authority and Industry Databases Individual Case Safety Reports and Safety Summaries Clinical Study Reports Investigators Brochures Core Company Safety Information Marketing Applications Publications Prescribing Information Advertising

6 Regulatory Status US FDA Used in several databases including FAERS (drugs and biologics), VAERS (vaccines), and CAERS (foods, dietary supplements, cosmetics) Recommended terminology for adverse event reporting in several Proposed Rules and Guidances Effective June 2015, electronic submission required for postmarketing safety reports for drugs, biologics, and vaccines (relies upon ICH standards) Japanese Ministry of Health, Labour and Welfare Mandatory use in electronic reporting Regulatory Status (cont) European Union EudraVigilance database Clinical trial SUSARs (Suspected Unexpected Serious Adverse Reactions) Post-authorization Individual Case Safety Reports (ICSRs) Requires current version of MedDRA or the one previous to it Good pharmacovigilance practices (GVP) specifically mention MedDRA Pharmacovigilance legislation covers suspected adverse reactions from: Use inside and outside terms of marketing authorization Overdose, misuse, abuse, and medication errors Occupational exposures

7 Regulatory Status (cont) European Union (cont) Used in interface between EudraVigilance and EU Risk Management Plan Used throughout Summary of Product Characteristics (labeling) ICH M4E Guideline on Common Technical Document Recommended in adverse event summary tables Canada Used in Canada Vigilance database Recommended/preferred terminology for adverse reaction reporting and Product Monograph (labeling) Electronic reporting via Gateway requires current version of MedDRA Scope of MedDRA Not a drug dictionary Patient demographic terms Clinical trial study design terms OUT IN Medical conditions Indications Investigations (tests, results) Medical and surgical procedures Medical, social, family history Medication errors Product quality issues Device-related issues Product use issues Pharmacogenetic terms Toxicologic issues Standardized queries Frequency qualifiers Numerical values for results Severity descriptors Not an equipment, device, diagnostic product dictionary

8 MedDRA Structure System Organ Class (SOC) (27) High Level Group Term (HLGT) (337) High Level Term (HLT) (1,738) Preferred Term (PT) (22,499) Lowest Level Term (LLT) (77,248) MedDRA Version MedDRA Codes Each MedDRA term assigned an 8-digit numeric code starting with 1 The code is non-expressive Codes can fulfill a data field in various electronic submission types (e.g., E2B) New terms are assigned sequentially

9 Codes and Languages System Organ Classes Blood and lymphatic system disorders Cardiac disorders Congenital, familial and genetic disorders Ear and labyrinth disorders Endocrine disorders Eye disorders Gastrointestinal disorders General disorders and administration site conditions Hepatobiliary disorders Immune system disorders Infections and infestations Injury, poisoning and procedural complications Investigations Metabolism and nutrition disorders Musculoskeletal and connective tissue disorders Neoplasms benign, malignant and unspecified (incl cysts and polyps) Nervous system disorders Pregnancy, puerperium and perinatal conditions Product issues Psychiatric disorders Renal and urinary disorders Reproductive system and breast disorders Respiratory, thoracic and mediastinal disorders Skin and subcutaneous tissue disorders Social circumstances Surgical and medical procedures Vascular disorders

10 A Multi-Axial Terminology Multi-axial = the representation of a medical concept in multiple SOCs Allows grouping by different classifications Allows retrieval and presentation via different data sets All PTs assigned a primary SOC Determines which SOC will represent a PT during cumulative data outputs Prevents double counting Supports standardized data presentation Pre-defined allocations should not be changed by users A Multi-Axial Terminology (cont) SOC = Respiratory, thoracic and mediastinal disorders (Secondary SOC) SOC = Infections and infestations (Primary SOC) HLGT = Respiratory tract infections HLGT = Viral infectious disorders HLT = Viral upper respiratory tract infections HLT = Influenza viral infections PT = Influenza

11 Rules for Primary SOC Allocation PTs represented in only one SOC are automatically assigned that SOC as primary PTs for diseases, signs and symptoms are assigned to prime manifestation site SOC Congenital and hereditary anomalies terms have SOC Congenital, familial and genetic disorders as Primary SOC Neoplasms terms have SOC Neoplasms benign, malignant and unspecified (incl cysts and polyps) as Primary SOC Exception: Cysts and polyps have prime manifestation site SOC as Primary SOC Infections and infestations terms have SOC Infections and infestations as Primary SOC Primary SOC Priority If a PT links to more than one of the exceptions, the following priority will be used to determine primary SOC: 1 st : Congenital, familial and genetic disorders 2 nd : Neoplasms benign, malignant and unspecified (incl cysts and polyps) 3 rd : Infections and infestations

12 A Multi-Axial Terminology (cont) PTs in the following SOCs only appear in that particular SOC and not in others, i.e., they are not multi-axial Investigations Surgical and medical procedures Social circumstances MSSO s MedDRA Browsers MedDRA Desktop Browser (MDB) Download MDB and release files from MedDRA website MedDRA Web-Based Browser (WBB) Features Both require MedDRA ID and password View/search MedDRA and SMQs Support for all MedDRA languages Language specific interface Ability to export search results and Research Bin to local file system

13 Browser Demonstration SOC View MedDRA Data Retrieval and Presentation: Points to Consider 12

14 MedDRA Data Retrieval and Presentation: Points to Consider Provides data retrieval and presentation options for industry or regulatory purposes Most effective when used in conjunction with MedDRA Term Selection: PTC document Recommended to be used as basis for individual organization s own data retrieval conventions MedDRA Data Retrieval and Presentation: Points to Consider (cont) Developed by a working group of the ICH Steering Committee Regulators and industry representatives from EU, Japan, and USA Canadian and Korean regulatory authorities WHO MSSO and JMO Updated twice yearly with each MedDRA release Available on MedDRA and JMO websites English and Japanese Word ( clean and redlined ), PDF, HTML formats Redlined document identifies changes made from previous to current release of document

15 Data Retrieval PTC Points Addressed General Principles Quality of Source Data Documentation of Data Retrieval and Presentation Practices Do Not Alter MedDRA Organisation-Specific Data Characteristics Characteristics of MedDRA that Impact Data Retrieval and Analysis MedDRA Versioning General Queries and Retrieval Standardised MedDRA Queries Customised Searches Quality of Source Data High quality data output is dependent on maintaining quality of original information reported by using consistent and appropriate term selection (Refer to MedDRA Term Selection: Points to Consider document) Method of conversion of data into MedDRA might impact retrieval and presentation - legacy data conversion using verbatims or coded terms

16 Documentation of Data Retrieval and Presentation Practices Organisation-specific guidelines Consistent with Points to Consider documents Coding conventions Data retrieval and output strategies (including SMQs) Quality assurance procedures MedDRA version used for search Search strategy methods Version update processes Processes for customised MedDRA queries Do Not Alter MedDRA MedDRA is a standardized terminology with a pre-defined term hierarchy Users must not make ad hoc structural alterations, including changing the primary SOC allocation If terms are incorrectly placed, submit a change request to the MSSO

17 Organisation-Specific Data Characteristics Database structure (storage and use of hierarchy) Data storage (level of term, synonym/reported term) Data conversion (if applicable) Coding practices over time Limitations/restrictions (inability to view secondary SOCs) Term selection principles More than one term selected increases counts Diagnosis term only selected reduces counts Impact of MedDRA s Characteristics Grouping Terms HLGTs and HLTs provide clinically relevant groupings HLGT Cardiac arrhythmias HLT Cardiac conduction disorders HLT Rate and rhythm disorders NEC HLT Supraventricular arrhythmias HLT Ventricular arrhythmias and cardiac arrest

18 Impact of MedDRA s Characteristics Grouping Terms (cont) Caution - ensure all terms are relevant to output HLT Vascular tests NEC (incl blood pressure) PT Blood pressure decreased PT Blood pressure increased Caution - related PTs in different locations in SOC HLT Bullous conditions PT Stevens-Johnson syndrome HLT Exfoliative conditions PT Dermatitis exfoliative Adverse Event (MedDRA v18.0) Which Level? SOC Investigations 25 mg MyDrug (N=44) Placebo (N=15) SOC Investigations 13 (29.5%) 2 (13.3%) PT Aspartate aminotransferase increased 6 0 PT Alanine aminotransferase increased 5 0 PT Gamma-glutamyltransferase increased 4 0 PT Blood creatine phosphokinase increased 2 1 PT Blood alkaline phosphatase increased 2 0 PT Blood glucose increased 1 1 PT Blood lactate dehydrogenase increased 2 0 PT Lipase increased 2 0 PT White blood cell count decreased 2 0 PT Amylase increased 1 0 PT Faecal fat increased 0 1 Patients may have more than one event reported

19 Which Level? SOC Investigations (cont) Adverse Event (MedDRA v18.0) 25 mg MyDrug (N=44) Placebo (N=15) SOC Investigations 13 (29.5%) 2 (13.3%) PT Blood pressure increased 1 0 PT Blood urea increased 1 0 PT Occult blood positive 1 0 PT Liver function test abnormal 1 0 PT Monocyte count decreased 1 0 PT Protein urine present 1 0 Patients may have more than one event reported Adverse Event (MedDRA v18.0) Which Level? SOC Investigations (cont) 25 mg MyDrug (N=44) Placebo (N=15) SOC Investigations 13 (29.5%) 2 (13.3%) HLT Liver function analyses 16 0 HLT Tissue enzyme analyses NEC 4 0 HLT Digestive enzymes 3 0 HLT White blood cell analyses 3 0 HLT Skeletal and cardiac muscle analyses 2 1 HLT Carbohydrate tolerance analyses (incl diabetes) 1 1 HLT Faecal analyses NEC 1 1 HLT Vascular tests NEC (incl blood pressure) 1 0 HLT Renal function analyses 1 0 HLT Urinalysis NEC 1 0 Patients may have more than one event reported

20 Multi-Axiality Primary SOC allocation rules affect the way data are distributed across the terminology Impact on frequencies of medical condition of interest should be considered Example: for hepatic abnormality search in SOC Hepatobiliary disorders, SOC Investigations (laboratory test terms), SOC Surgical and medical procedures (e.g., PT Liver transplant) Multi-Axiality (cont) Main presentation is by Primary SOC Secondary SOCs used for alternate views and presentation of data

21 Adverse Event (MedDRA v19.0) Primary SOC Analysis SOC Infections and infestations 25 mg MyDrug (N=44) Placebo (N=15) SOC Infections and infestations 14 (31.8%) 4 (26.7%) PT Upper respiratory tract infection 5 2 PT Sinusitis 3 0 PT Urinary tract infection 2 1 PT Ear infection 2 0 PT Viral infection 2 0 PT Bronchitis 1 0 PT Influenza 1 0 PT Localised infection 0 1 PT Lower respiratory tract infection 1 0 PT Pneumonia 1 0 PT Tooth abscess 1 0 Patients may have more than one event reported Adverse Event (MedDRA v19.0) SOC Respiratory, thoracic and mediastinal disorders Secondary SOC Analysis SOC Infections and infestations 25 mg MyDrug (N=44) Placebo (N=15) PT Upper respiratory tract infection 5 2 PT Sinusitis 3 0 PT Bronchitis 1 0 PT Influenza 1 0 PT Lower respiratory tract infection 1 0 PT Pneumonia 1 0 SOC Infections and infestations PT Viral infection 2 0 PT Localised infection 0 1 Patients may have more than one event reported

22 Secondary SOC Analysis SOC Infections and infestations (cont) Adverse Event (MedDRA v19.0) SOC Renal and urinary disorders 25 mg MyDrug (N=44) Placebo (N=15) PT Urinary tract infection 2 1 SOC Ear and labyrinth disorders PT Ear infection 2 0 SOC Gastrointestinal disorders PT Tooth abscess 1 0 Patients may have more than one event reported MedDRA Versioning MedDRA is updated twice a year 1 March X.0 release (all levels) 1 September X.1 release (LLT and PT levels only) Version used in data retrieval and presentation should be documented Resources: What s New document Version report MedDRA Version Analysis Tool (MVAT) Terms used for queries should be in same version as data being queried

23 MedDRA Versioning (cont): Effect of PT Demotion MedDRA Version 18.1 Number of Events at PT Level Metastatic pain (PT) 15 Cancer pain 5 MedDRA Version 19.0 Number of Events at PT Level Metastatic pain (no longer a PT) 0 Cancer pain MedDRA Versioning (cont): Effect of Primary SOC Change MedDRA Version 18.0 Number of Events SOC Vascular disorders PT Intra-abdominal haematoma 20 MedDRA Version 18.1 Number of Events SOC Vascular disorders 0 SOC Gastrointestinal disorders PT Intra-abdominal haematoma

24 MedDRA Version Analysis Tool (MVAT) Web-based ( Free to all users Features Version Report Generator (produces exportable report comparing any two versions) Data Impact Report (identifies changes to a specific set of MedDRA terms or codes uploaded to MVAT) Search Term Change (identifies changes to a single MedDRA term or code) User interface and report output available in all MedDRA languages Exercise

25 How Many Cases of Autoimmune Diseases? Adverse Event (MedDRA v18.0) No. of cases SOC Blood and lymphatic system disorders PT Anaemia 5 PT Autoimmune neutropenia 5 PT Evans syndrome 1 PT Platelet anisocytosis 1 PT Platelet toxicity 2 SOC Cardiac disorders PT Autoimmune myocarditis 4 PT Myocardial infarction 1 PT Myocarditis How Many Cases of Autoimmune Diseases? (cont) Adverse Event (MedDRA v18.0) No. of cases SOC Endocrine disorders PT Polyglandular autoimmune syndrome type I 2 PT Thyroid disorder 1 SOC Eye disorders PT Birdshot chorioretinopathy 2 PT Autoimmune uveitis 3 SOC Hepatobiliary disorders PT Biliary cirrhosis primary 3 PT Hepatitis toxic 1 PT Hepatocellular injury

26 How Many Cases of Autoimmune Diseases? (cont) Adverse Event (MedDRA v18.0) No. of cases SOC Immune system disorders PT Autoimmune disorder 4 SOC Musculoskeletal and connective tissue disorders PT Arthritis 1 PT Muscular weakness 2 PT Polymyalgia rheumatica 1 PT Rheumatoid arthritis 3 SOC Skin and subcutaneous tissue disorders PT Alopecia 1 PT Skin haemorrhage 1 PT Vitiligo Adverse Event (MedDRA v18.0) SOC Immune system disorders Secondary SOC Analysis and Use of a Grouping Term No. of cases HLGT Autoimmune disorders 30 PT Autoimmune disorder 4 PT Autoimmune myocarditis 4 PT Autoimmune neutropenia 5 PT Biliary cirrhosis primary 3 PT Birdshot chorioretinopathy 2 PT Evans syndrome 1 PT Polyglandular autoimmune syndrome type I 2 PT Polymyalgia rheumatica 1 PT Rheumatoid arthritis 3 PT Autoimmune uveitis 3 PT Vitiligo

27 General Queries and Retrieval Document search strategy Highlight overall distribution of ADRs/AEs Identify areas for indepth analysis (focused searches) Overview by Primary SOC Use Internationally Agreed Order of SOCs when applicable, e.g., the EU SPC guideline See MedDRA Introductory Guide, ASCII files Consider use of HLTs and HLGTs Line listings, tables, graphs Benefits - Broad overview, PTs displayed only once Limitations - Incomplete groupings due to SOC allocation rules, lengthy output

28 Primary SOC Graphical Display Example Primary SOC Output Listing Example SOC Nervous system disorders 8 HLGT Mental impairment disorders HLT Mental impairment (excl dementia and memory loss) PT Disturbance in attention 1 HLGT Movement disorders (incl Parkinsonism) HLT Dyskinesias and movement disorders NEC PT Psychomotor hyperactivity 2 HLT Tremor (excl congenital) PT Tremor 3 HLGT Neurological disorders NEC HLT Disturbances in consciousness NEC PT Somnolence 1 HLT Neurological signs and symptoms NEC PT Dizziness

29 Focused Searches Useful when further investigating concepts of interest Secondary SOC assignments Programming required if database does not allow automated output by secondary SOC Benefits - more comprehensive view of medically related events Limitations - display by primary and secondary SOC could lead to double counting Grouping terms (HLGT/HLT) SMQ Customized search Modified SMQ Ad hoc query Secondary SOC Output Listing Example Example as of MedDRA Version

30 Use of MedDRA at FDA Acknowledgement: Dr. Chuck Cooper, Office of Translational Sciences, CDER, FDA 57 Use of MedDRA at EMA Higher level of hierarchy SMQs Screening at PT MedDRA embedded Disproportionality Acknowledgement: Dr. Aniello Santoro, EMA 58 29

31 Use of MedDRA at EMA: Impact of Multi-axiality Secondary SOC assignments included Acute coronary syndrome Acute myocardial infarction Acute pulmonary oedema Angina pectoris Angina unstable Arrhythmia Atrial fibrillation Atrial flutter Atrial tachycardia Atrioventricular block Cardiac arrest Cardiac disorder Cardiac failure Cardiac failure acute Cardiac failure congestive Cardiac flutter Cardio-respiratory arrest Cardiomyopathy Cardiovascular insufficiency Chest discomfort Chest pain Congestive cardiomyopathy Cyanosis Dizziness Dyspnoea Dyspnoea at rest Dyspnoea exertional Haemoptysis Myocardial infarction Nocturnal dyspnoea Oedema peripheral Palpitations Pericarditis Pulmonary oedema Sinus tachycardia Sudden cardiac death Sudden death Supraventricular tachycardia Syncope Tachycardia Ventricular arrhythmia Ventricular extrasystoles Ventricular fibrillation Ventricular tachycardia Primary SOC overview Acute coronary syndrome Acute myocardial infarction Angina pectoris Angina unstable Arrhythmia Atrial fibrillation Atrial flutter Atrial tachycardia Atrioventricular block Cardiac arrest Cardiac disorder Cardiac failure Cardiac failure acute Cardiac failure congestive Cardiac flutter Cardio-respiratory arrest Cardiomyopathy Cardiovascular insufficiency Congestive cardiomyopathy Cyanosis Myocardial infarction Palpitations Pericarditis Sinus tachycardia Supraventricular tachycardia Tachycardia Ventricular arrhythmia Ventricular extrasystoles Ventricular fibrillation Ventricular tachycardia Acknowledgement: Dr. Aniello Santoro, EMA Signal: Cardiac toxicity Drug A Analysis at SOC Cardiac disorders level Primary SOC assignments : Total number of cases: 122 If secondary SOC assignments included: Total number of cases: additional PTs Assess if additional PTs (cases) are of relevance 59 Developing Queries Using MedDRA

32 What is a Query? Query Define the condition Query Strategy Tips Develop inclusion/exclusion criteria Good browser is key component Search non multi-axial and other/support SOCs Search a term s neighbors, including secondary locations Use grouping terms where applicable Avoid using LLTs (Exception: species information at LLT level in SOC Infections and infestations) Store for future use Review for impact of new MedDRA versions

33 Complete the Circle (Connect the DOTSSS!) Diagnosis/disease terms Support SOCs (Other ) Operations (Surgical and medical procedures) Signs & symptoms Tests (Investigations) Social circumstances Example and Hands-on Exercises

34 Example Cardiac arrhythmias Example Cardiac Arrhythmias Obvious starting point HLGT Cardiac arrhythmias ( Top-down search) Also use Arrhythmia terms as starting point of Bottom-up search What about non-multi-axial SOCs?

35 Example Cardiac Arrhythmias (cont) SOC Investigations PTs subordinate to HLT ECG investigations and HLT Heart rate and pulse investigations should be reviewed Example: PT Heart rate irregular Example Cardiac Arrhythmias (cont) SOC Surgical and medical procedures Important to review: PTs subordinate to HLT Cardiac device therapeutic procedures* Example: PT Implantable defibrillator insertion PTs subordinate to HLT Cardiac therapeutic procedures NEC* Example: PT Cardioversion *Note: Pacemaker and other cardiac therapeutic procedure terms were not included in SMQ Cardiac arrhythmias

36 Example Cardiac Arrhythmias (cont) Because arrhythmias may produce various signs and symptoms, you may wish to review PTs subordinate to the following HLTs: HLT Disturbances in consciousness NEC HLT Neurological signs and symptoms NEC HLT Cardiac disorders NEC HLT Cardiac signs and symptoms NEC HLT Dyspnoeas Example Cardiac Arrhythmias (cont) Lastly PTs subordinate to HLT Death and sudden death (under SOC General disorders and administration site conditions) should be reviewed Example: PT Cardiac death

37 Cardiac Arrhythmias Identifying Cases Patient ID Patient Events (PTs) MedDRA v Nausea Vomiting Primary SOC Case of interest? Unlikely 02 Sudden death General disorders and administration site conditions Potential case. Needs review. 03 Electrocardiogram abnormal Dyspnoea Cardio-respiratory arrest 04 Breast cancer Postmenopause 05 Syncope Palpitations 06 Pacemaker generated arrhythmia 07 Atrial fibrillation Cardioversion Investigations Respiratory, thoracic and mediastinal disorders Cardiac disorders Nervous system disorders Cardiac disorders General disorders and administration site conditions Cardiac disorders Surgical and medical procedures Potential case. Needs review. Unlikely Potential case. Needs review. Potential case. Needs review. Potential case. Needs review. 08 Long QT syndrome congenital Congenital, familial and genetic disorders Potential case. Needs review. 09 Cerebrovascular accident Prostate cancer Unlikely 10 Cardiac assistance device user Social circumstances Potential case. Needs review Exercise Topic: Cardiac failure Build a query with a set of PTs relevant to this condition Consider: Diagnosis terms Signs and symptoms Investigations Surgical and medical procedures Other. Can you identify cases of interest in a dataset?

38 Alcoholic liver disease Hypoglycemia Depression Osteonecrosis Abuse liability Query Development Exercises Falls Obesity Prostate cancer Parkinson s disease Hearing loss Before starting Develop a definition of the condition Develop inclusion/exclusion criteria (etiologies and risk factors are typically excluded) Note the main SOCs, HLGTs and HLTs used in your query, as well as examples of specific PTs Developing Queries Lessons Learned MedDRA is a potentially powerful tool for data retrieval, BUT it requires: Solid medical knowledge Solid MedDRA knowledge Size and complexity of MedDRA overcome lack of specificity of other terminologies, but may require a more creative approach to data retrieval WELL WORTH THE EFFORT to develop, share, and store in-house queries

39 Standardised MedDRA Queries (SMQs) Standardised MedDRA Queries (SMQs) Result of cooperative effort between CIOMS (Council for International Organizations of Medical Sciences) and ICH (MSSO) Groupings of terms from one or more MedDRA System Organ Classes (SOCs) related to defined medical condition or area of interest Included terms may relate to signs, symptoms, diagnoses, syndromes, physical findings, laboratory and other physiologic test data, etc., related to medical condition or area of interest Intended to aid in case identification

40 SMQ Development and Oversight CIOMS SMQ Working Group Senior scientists (as members or observers) from several drug regulatory authorities and other organizations Senior scientists from many pharmaceutical companies MSSO and JMO ICH Advisory Panel Representatives from industry and regulators from the three ICH regions, MHRA, Health Canada and WHO (as an observer) SMQ Benefits and Limitations Benefits Application across multiple therapeutic areas Validated reusable search logic Standardized communication of safety information Consistent data retrieval Maintenance by MSSO/JMO Limitations Do not cover all medical topics or safety issues Will evolve and undergo further refinement even though they have been tested during development

41 SMQs in Production - Examples As of Version 20.0, a total of 101 level 1 SMQs in production Agranulocytosis Anaphylactic reaction Cerebrovascular disorders Convulsions Depression and suicide/self-injury Hepatic disorders Hypersensitivity Ischaemic heart disease Lack of efficacy/effect Medication errors Osteonecrosis Peripheral neuropathy Pregnancy and neonatal topics Pseudomembranous colitis Rhabdomyolysis/myopathy Severe cutaneous adverse reactions Systemic lupus erythematosus SMQ Data Characteristics

42 SMQ Data Characteristics MedDRA term inclusion SMQ naming convention Broad/narrow Algorithms Hierarchy SMQ status/term status within an SMQ Term versioning in an SMQ Text data included in SMQ MedDRA Term Inclusion SMQs are constructed at MedDRA PT level LLTs that are subordinate to an included PT are also included

43 SMQ Naming Convention SMQ titles have (SMQ) appended to the end to ensure there is no name conflict with existing MedDRA terms E.g., Agranulocytosis (SMQ) Each SMQ has a unique 8-digit code starting with Narrow and Broad Searches Narrow scope specificity (cases highly likely to be condition of interest) Broad scope sensitivity (all possible cases) Broad search = All broad + all narrow terms

44 Narrow vs. Broad Example SMQ Lactic acidosis Algorithmic SMQs Some SMQs are designed to utilize algorithms Better case identification among broad search terms may result if cases are selected by a defined combination of selected terms

45 Algorithmic SMQ Example Anaphylactic reaction (SMQ): A case with any of the following PTs: Anaphylactic reaction Anaphylactic shock Anaphylactic transfusion reaction Anaphylactoid reaction Anaphylactoid shock Circulatory collapse Dialysis membrane reaction Kounis syndrome Shock Shock symptom Type I hypersensitivity (Narrow search terms = Category A) Category B Upper airway/respiratory Acute respiratory failure Algorithmic SMQ Example (cont) Category C Angioedema/ Urticaria, etc. Allergic oedema Category D Cardiovascular/ Hypotension Blood pressure decreased Asthma Angioedema Blood pressure diastolic decreased Bronchial oedema Erythema Blood pressure systolic decreased Case = A (Narrow terms) Or Term from Category B and term from Category C Or Term from either Category B or Category C plus Term from Category D

46 Hierarchical SMQs Some SMQs may develop as set of queries related to one another in a hierarchical relationship Not related to MedDRA standard hierarchy One or more subordinate SMQs combined to create a superordinate, more inclusive SMQ Hierarchical SMQ Example Haematopoietic cytopenias Haematopoietic cytopenias affecting more than one type of blood cell Haematopoietic erythropenia Haematopoietic leukopenia Haematopoietic thrombocytopenia

47 SMQ Status/Term Status Each SMQ has a status (Active/Inactive) Similar in concept to MedDRA currency Terms assigned to an SMQ also have a status flag Once a term is added to an SMQ, it will always be included in the SMQ but the status may be inactive Term Versioning in an SMQ Each term included in an SMQ has version fields Term addition version of MedDRA when the term was added to the SMQ Term last modified version of MedDRA when a change was made to the term in the SMQ (e.g. status, scope) Allows user to know the maintenance history of the SMQ

48 Text Data Included in SMQ Description field Additional information about each SMQ (from SMQ Introductory Guide) Source field Medical references used in development/ maintenance Development note Pertinent notes for proper use Description of algorithm (if applicable), and definition of categories SMQ Files and Documents MedDRA distributed files unchanged by inclusion of SMQ files SMQ Introductory Guide Recommended reading for optimal use of SMQs Details of individual SMQs Notes for implementation and/or expectation of results Production SMQ Spreadsheet SMQs and included terms, SMQ summary SMQ changes: What s New document, Version Report, MVAT Original CIOMS Working Group documentation

49 Browser Demonstration SMQ View How to Run SMQs IT perspective of SMQs = stored queries Code at LLT level; most organizations store coded data as LLTs SMQ ASCII files include PTs and LLTs Load SMQs into a query tool; run query against coded MedDRA terms in safety or clinical trial database for Hits Use SMQ options, if applicable Narrow/broad search Algorithms Hierarchy

50 How to Run SMQs (cont) Query Exercise Topic: Acute renal failure Run SMQ Acute renal failure (broad search) Can you identify cases of interest in a dataset?

51 SMQ Narrow Search Results Example SMQ Broad Search Results Example

52 SMQ Testing, Production Maintenance, and Versioning SMQ Development Summary Pre-release testing by CIOMS Working Group members Typically, at least one company and one regulator database Cases retrieved reviewed for relevance Fine-tuning of SMQ may require several iterations Reviewed and approved by CIOMS WG Production Phase: continue to be fine-tuned through the MSSO maintenance process

53 SMQ Production Maintenance SMQ change request process Considered as simple change requests Part of the 100 allotted change requests per subscriber Final disposition is not time limited MSSO reviews all new terms in new release for inclusion in existing SMQs MSSO reviews existing terms for impact of demotions, moves, etc. All SMQ change requests reviewed by CIOMS WG after months in production SMQ Versioning It is recommended that organizations use the SMQs with data coded with the same version of MedDRA Match the MedDRA version of the SMQ with the MedDRA version of the coded data Mismatches of SMQ and MedDRA coded data could produce unexpected results

54 SMQ Versioning (cont) Example of PT added to SMQs in MedDRA Version 19.0: PT End stage renal disease in SMQ Chronic kidney disease Using version 18.1 SMQs which do not contain these PTs would fail to identify cases coded to these terms in a database using MedDRA Version SMQ Applications

55 SMQ Applications Clinical trials Where safety profile is not fully established, use multiple SMQs on routine basis as screening tool Selected SMQs to evaluate previously identified issue (pre-clinical data or class effect) Post-marketing Selected SMQs to retrieve cases for suspected or known safety issue Signal detection (multiple SMQs employed) Single case alerts Periodic reporting (aggregate cases for safety and other issues, e.g., lack of efficacy) Use of SMQs at FDA Acknowledgement: Dr. Chuck Cooper, Office of Translational Sciences, CDER, FDA

56 Use of SMQs at FDA (cont) Acknowledgement: Dr. Chuck Cooper, Office of Translational Sciences, CDER, FDA Use of SMQs at FDA (cont) Acknowledgement: Dr. Chuck Cooper, Office of Translational Sciences, CDER, FDA

57 Use of SMQs at FDA Reviewing Prescribing Information Proposed Prescribing Information: Warnings & Precautions: Dizziness/Somnolence Withdrawal of Antiepileptic Drugs Suicidal Behavior and Ideation (class labeling) SMQ (Narrow Search) RR (1) Hostility/aggression 4.4 (2) Vestibular disorders (1) Hearing and vestibular disorders (1) Hyponatraemia/SIADH (2) Hearing impairment (1) Dyslipidaemia * (1) Biliary disorders Final Prescribing Information Boxed Warning: Serious Psychiatric and Behavioral Reactions Warnings & Precautions: Falls Dizziness & somnolence Withdrawal of Antiepileptic Drugs Suicidal Behavior and Ideation (class labeling) (2) Functional, inflammatory and gallstone related biliary disorders Acknowledgement: Dr. Christopher Breder, Office of New Drugs, CDER, FDA 111 EMA: Signal Detection Analysis ICSR coding at LLT level, analysis at PT level (medical concept): It may be important to conduct analysis at higher level of hierarchy: SOC, HLGT, HLT When doing so, impact of axial and non multi-axial SOCs needs to be taken into account: relevant PTs in more than 1 SOC It may be important to conduct analysis at SMQ level to maximise likelihood that all terms related to a specific medical condition of interest are identified Challenge: strike the correct balance Too narrowly focused search (specificity): exclude events of potential relevance Too broad search (sensitivity): difficult to identify a trend or signal that may require further analysis (incl. case review) Acknowledgement: Dr. Aniello Santoro, EMA

58 Signal of Angioedema - PT vs. SMQ SMQ Angioedema (Narrow search) PT N. ICSR Angioedema 9 Eye swelling 1 Face oedema 1 Laryngeal oedema 1 Oedema mouth 1 Pharyngeal oedema 4 Swelling face 10 Swollen tongue 6 Urticaria Acknowledgement: Dr. Aniello Santoro, EMA 113 Signal of Lactic Acidosis - PT vs. SMQ Broad search of SMQ identifies additional ICSRs with related signs and symptoms where no specific diagnosis is made. These would be missed if search only conducted with PT Lactic acidosis. SMQ Lactic acidosis (Broad search) PT Cases Acidosis 2 Anion gap increased 1 Blood bicarbonate abnormal 1 Blood bicarbonate decreased 6 Blood gases abnormal 1 Blood lactic acid increased 27 Hyperlactacidaemia 22 Lactic acidosis 63 Metabolic acidosis 18 PCO2 decreased Acknowledgement: Dr. Aniello Santoro, EMA

59 Customized Searches Customized Searches Modified SMQs Do not modify SMQ unless there is a compelling reason makes it non-standard Modified MedDRA query based on an SMQ To be used to refer to an SMQ that has been modified All modifications must be documented Version updates and maintenance are responsibility of organization that created it

60 Modified MedDRA Queries Based on SMQs - Examples Additional PTs needed Product investigated for possible safety signal of dementia and user wishes to use SMQ Dementia For this particular product, PT Disturbance in attention may be needed. Document that this PT has been added to SMQ Dementia. Excluding PTs Antipsychotic investigated for QT prolongation also has association with hypotension/fainting Exclude PT Syncope from SMQ Torsade de pointes/qt prolongation (broad search) to prevent noise in retrieval Modified MedDRA Queries Based on SMQs Examples (cont) Changing scope of SMQ term Product being investigated for hyperglycaemia and diabetes mellitus; specific (narrow) search result is required Include PT Increased insulin requirement (normally a broad search term) with the narrow search terms in Hyperglycaemia/new onset diabetes mellitus (SMQ)

61 PT N. ICSRs Cardiac arrest 275 Cardiac death 4 Cardio-respiratory arrest 185 Electrocardiogram QT interval abnormal 1 Electrocardiogram QT prolonged 274 Electrocardiogram repolarisation abnormality 5 Electrocardiogram U-wave abnormality 1 Long QT syndrome 14 Loss of consciousness 490 Sudden cardiac death 97 Sudden death 140 Syncope 302 Torsade de pointes 36 Ventricular arrhythmia 8 Ventricular fibrillation 37 Ventricular tachyarrhythmia 1 Ventricular tachycardia 46 EMA: Use of a Modified MedDRA Query Based on an SMQ Signal of QT prolongation with Drug A: SMQ Torsade de pointes/qt prolongation Well-known association of Drug A with hypotension and fainting May be sensible to modify SMQ and exclude PTs Loss of consciousness and Syncope, to reduce noise in data retrieval Data retrieval strategy needs to be documented When an SMQ is modified, it should be called a Modified MedDRA query based on a SMQ Acknowledgement: Dr. Aniello Santoro, EMA 119 Customized Searches Ad Hoc Queries Need medical knowledge Need knowledge of structure and characteristics of MedDRA and of your data Refer to the MedDRA Data Retrieval and Presentation: Points to Consider document for query construction tips Save query for future use; maintenance needed for MedDRA version changes Consider submitting ad hoc query to MSSO via change request for possible development as an SMQ

62 Exercise SMQ Lack of efficacy/effect often needs to be modified based on the particular characteristics of a product Consider how you would create a Modified MedDRA Query based on SMQ Lack of efficacy/effect for: An inhaled bronchodilator indicated for use in asthma A contraceptive Remember to document changes! Modified SMQs Adding PTs Excluding PTs Changing scope of SMQ term (narrow to broad or vice versa) SMQ Lack of efficacy/effect often modified based on particular product

63 Course Summary In this course, we: Reviewed MedDRA s scope, structure, and characteristics Reviewed key sections of the MedDRA Data Retrieval and Presentation: Points to Consider document Reviewed key points for developing queries using MedDRA Worked on MedDRA query exercises Course Summary (cont) In this course, we: Reviewed SMQ background and definition Reviewed the development status of SMQs Discussed SMQ data characteristics Discussed SMQ testing, production maintenance, and versioning Reviewed SMQ applications Discussed customized searches

64 MSSO Contacts Website Frequently Asked Questions

65 MedDRA DATA RETRIEVAL AND PRESENTATION: POINTS TO CONSIDER ICH-Endorsed Guide for MedDRA Users on Data Output Release 3.13 Based on MedDRA Version March 2017 Disclaimer and Copyright Notice This document is protected by copyright and may be used, reproduced, incorporated into other works, adapted, modified, translated or distributed under a public license provided that ICH's copyright in the document is acknowledged at all times. In case of any adaption, modification or translation of the document, reasonable steps must be taken to clearly label, demarcate or otherwise identify that changes were made to or based on the original document. Any impression that the adaption, modification or translation of the original document is endorsed or sponsored by the ICH must be avoided. The document is provided "as is" without warranty of any kind. In no event shall the ICH or the authors of the original document be liable for any claim, damages or other liability arising from the use of the document. The above-mentioned permissions do not apply to content supplied by third parties. Therefore, for documents where the copyright vests in a third party, permission for reproduction must be obtained from this copyright holder. MedDRA trademark is owned by IFPMA on behalf of ICH

66 Table of Contents SECTION 1 INTRODUCTION Objectives of this Document Reasons to Use MedDRA How to Use this Document... 2 SECTION 2 GENERAL PRINCIPLES Quality of Source Data Data conversion considerations Impact of data conversion method Documentation of Data Retrieval and Presentation Practices Do Not Alter MedDRA Organisation-Specific Data Characteristics Characteristics of MedDRA that Impact Data Retrieval and Analysis Grouping terms (HLTs and HLGTs) Granularity Multiaxiality MedDRA Versioning SECTION 3 GENERAL QUERIES AND RETRIEVAL General Principles Graphical displays Patient subpopulations Overall Presentation of Safety Profiles Overview by primary System Organ Class Overall presentations of small datasets Focused searches SECTION 4 STANDARDISED MedDRA QUERIES i

67 4.1 Introduction SMQ Benefits SMQ Limitations SMQ Modifications and Organisation-Constructed Queries SMQs and MedDRA Version Changes SMQs Impact of MedDRA Legacy Data Conversion SMQ Change Requests SMQ Technical Tools SMQ Applications Clinical trials Post-marketing SMQ Search Options Narrow and broad searches Hierarchical SMQs Algorithmic SMQs SMQ and MedDRA Grouping Terms SECTION 5 CUSTOMISED SEARCHES Modified MedDRA Query Based on an SMQ Customised Queries SECTION 6 APPENDIX Links and References Membership of the ICH Points to Consider Working Group Current members of the ICH Points to Consider Working Group Former members of the ICH Points to Consider Working Group Figures ii

68 SECTION 1 INTRODUCTION The Medical Dictionary for Regulatory Activities terminology (MedDRA) was designed for sharing regulatory information for human medical products. In order for MedDRA to harmonise the exchange of coded data, users should be consistent in the assignment of terms to verbatim reports of symptoms, signs, diseases, etc. MedDRA is a large terminology with very specific ( granular ) terms called Lowest Level Terms (LLTs) that serve to accurately record the reporter s words (verbatim term). LLTs are generally synonyms linked to their parent terms known as Preferred Terms (PTs).PTs are also relatively specific and large in number. While a highly granular terminology such as MedDRA reduces the need for interpretation at data entry, it impacts the processes of data retrieval, sorting and presentation necessary for support of drug development, pharmacovigilance and risk management. The hierarchical structure of MedDRA facilitates data retrieval by providing grouping terms (High Level Terms [HLTs] and High Level Group Terms [HLGTs]) that aggregate the very specific terms used for coding into broader medical categories. MedDRA s multiaxiality (assignment of a PT to more than one System Organ Class [SOC]) allows flexibility in data retrieval via primary and secondary paths. Whilst grouping terms and multiaxiality permit a reasonable first approach to data retrieval, the complexity of MedDRA requires guidance to optimise the results. This Data Retrieval and Presentation: Points to Consider (DRP:PTC) document is an ICHendorsed guide for MedDRA users. It is updated in step with new MedDRA versions and is a companion document to MedDRA. It was developed and is maintained by a working group charged by the ICH Steering Committee. The working group consists of regulatory and industry representatives of the European Union, Japan, and the United States, as well as representatives from the Canadian regulatory authority, the World Health Organization, the MedDRA Maintenance and Support Services Organization (MSSO) and the Japanese Maintenance Organization (JMO) (see Appendix, Section 6.2 for list of members). The principles described in this document are most effective when used in conjunction with the principles described in the MedDRA Term Selection: Points to Consider document for data entry (coding). This document provides data retrieval and presentation options for either industry or regulatory purposes. Although MedDRA includes some data retrieval tools, this document addresses data retrieval in a broader context. Examples shown in this document are intended to facilitate reader understanding and are not intended to imply regulatory requirements. Figures referenced in the text are found in the Appendix, Section Objectives of this Document The objective of the DRP:PTC document is to demonstrate how data retrieval options impact the accuracy and consistency of data output. For example, certain drugs or 1

69 therapeutic areas may need a customised approach for data output. Options for data input described in the MedDRA Term Selection: Points to Consider document or in organisation-specific coding guidelines should also be taken into consideration. Organisations are encouraged to document their data retrieval and output strategies, methods and quality assurance procedures in organisation-specific guidelines which should be consistent with this DRP:PTC document. 1.2 Reasons to Use MedDRA MedDRA is used to report adverse reaction/adverse event (AR/AE) terms in individual case reports both on paper or electronically. Its structure allows for aggregation of those reported terms in medically meaningful groupings to facilitate analysis of safety data. MedDRA can also be used to list AR/AE data in reports (tables, line listings, etc.), compute frequencies of similar AR/AEs, and capture and analyse related data such as product indications, investigations, and medical and social history. 1.3 How to Use this Document The principles described in this document apply to all data encoded with MedDRA with a focus on aggregated data. This document does not address the use of MedDRA for single case reporting, labeling, medical evaluation and statistical methodology. This Points to Consider document aims to help all MedDRA users, since the MedDRA terminology itself contains no specific guidelines for its use. The document provides a framework to foster consistent use of MedDRA for data analysis and presentation for medically meaningful review and analysis of clinical data. This document describes the features of MedDRA and highlights the impact of MedDRA s structure, rules and conventions on data output. Examples and options described in the document are not intended to communicate specific regulatory reporting requirements or address specific database issues. This document cannot address every situation, therefore, medical judgment should always be applied. The document is not a substitute for MedDRA training. It is essential for users to have knowledge of MedDRA s structure and content. For optimal use of MedDRA, one should refer to the MedDRA Introductory Guide, the Introductory Guide for Standardised MedDRA Queries (SMQs) (see Appendix, Section 6.1), and the MedDRA Term Selection: Points to Consider document). Users are invited to contact the MSSO Help Desk with any questions or comments about this DRP:PTC document. Users may also wish to refer to the CIOMS report Development and Rational Use of Standardised MedDRA Queries (SMQs): Retrieving Adverse Drug Reactions with MedDRA for additional information about the purpose and appropriate use of SMQs in safety surveillance activities. Please refer to the CIOMS website for more information on 2

70 the second edition (2016) of this report, also known as the Red Book. See Section 6.1 Links and References. 3

71 SECTION 2 GENERAL PRINCIPLES 2.1 Quality of Source Data High quality data output occurs when the quality of the information originally reported is maintained with consistent and appropriate term selection. Organisations should pursue continuous oversight of data quality. Data quality issues are also addressed in the MedDRA Term Selection: Points to Consider document Data conversion considerations Give special consideration to the method used to convert data from other terminologies into MedDRA. The methods used can impact retrieval and presentation strategies. Method 1 Data converted from legacy terminology terms to MedDRA Example Results will reflect the specificity of the previous terminology The benefits of the greater specificity of MedDRA are not attained Reported Legacy Term MedDRA Term Gastrointestinal ischaemia Gastrointestinal Disorder Gastrointestinal disorder Example Method 2 Data converted from the original reported terms (verbatim terms) to MedDRA terms Reported Legacy Term MedDRA Term Gastrointestinal ischaemia Gastrointestinal Disorder Gastrointestinal ischaemia Document the data conversion method used, including the date of the conversion and the MedDRA version used Impact of data conversion method Combining the two conversion methods described above can affect interpretation of data output. 4

72 Example Data Output with Combined Data Conversion Methods If data have been converted directly from legacy terminology terms to MedDRA terms (Method 1), and if newly acquired data are coded directly from reported terms to MedDRA, the resulting differences in specificity could make interpretation difficult. When designing a search strategy, it may be useful to examine the reported terms for data converted using Method 1. If the search has been based on specific MedDRA terms, data previously coded to non-specific terms may be otherwise overlooked. Example Impact of Method 1 Conversion on Search Strategy If searching with MedDRA PT Gastrointestinal ischaemia, cases of gastrointestinal ischaemia coded with the legacy term Gastrointestinal disorder would be missed. In this case, it would be important to know the date of the legacy data conversion and the MedDRA version used. To conduct a search requiring this level of detail, it might be necessary to review or recode from the reported terms. For legacy data, this information might be found in fields other than those for ARs/AEs. 2.2 Documentation of Data Retrieval and Presentation Practices It is important to document MedDRA term selection conventions, data retrieval and output strategies (including SMQs and other queries) and quality assurance procedures. Organisation-specific strategies should be consistent with the Points to Consider documents and should include: MedDRA version used for the search Search strategy methods (sufficiently detailed to be reproducible) Version update processes Processes for creating and maintaining customized MedDRA queries 2.3 Do Not Alter MedDRA MedDRA is a standardised terminology with a pre-defined term hierarchy that should not be altered. Users must not make ad hoc structural alterations to MedDRA, including changing the primary SOC allocation; doing so would compromise the integrity of this standard. If terms are found to be incorrectly placed in the MedDRA hierarchy, a change request should be submitted to the MSSO. 5

73 2.4 Organisation-Specific Data Characteristics Although MedDRA is a standardised terminology, different organisations have implemented it in various ways. It is important to understand organisation-specific data characteristics and implementation strategies. Each organisation should have access to a MedDRA specialist to provide expert advice and who has the knowledge of the following database characteristics: Example Database structure (how the MedDRA hierarchy is stored and used) Data storage (e.g., level of term, synonym/reported term) Data conversion from other terminologies (if applicable) Coding practices over time Impact of Coding Practices Over Time Consider the impact of gender-specific terms when comparing MedDRA coded data to data coded with an older terminology that may not have had corresponding genderspecific terms. If the prior terminology had only a single, gender-neutral term for breast cancer, consider the impact of selecting gender-specific breast cancer terms in MedDRA for current data. Limitations or restrictions Example Output or Display of Multiaxial PTs Do not assume that PTs in their secondary SOC locations will be seen when searching in a specific HLT or HLGT since the database configuration may not allow output or display by the secondary path. Term selection principles used o o o Selecting more than one term when coding a medical condition increases counts of terms. Selecting a diagnosis term only (and not terms for signs and symptoms) reduces the counts of terms. The adverse event profile resulting when both diagnosis and signs/symptoms terms are coded may appear different than when the diagnosis only is coded. Always consider the organisation s coding conventions when using or 6

74 comparing data from other databases (e.g., co-developing or co-marketing partners, regulatory authorities). 2.5 Characteristics of MedDRA that Impact Data Retrieval and Analysis MedDRA s structure, rules and conventions are detailed in the MedDRA Introductory Guide. Keep the following MedDRA characteristics in mind for data retrieval and presentation: Grouping terms (HLTs and HLGTs) The HLT and HLGT levels are an additional tool for data analysis and retrieval as they provide clinically relevant groupings of terms. Example HLGT Cardiac arrhythmias Example as of MedDRA Version 19.0 Cardiac Arrhythmias HLT Cardiac conduction disorders HLT Rate and rhythm disorders NEC HLT Supraventricular arrhythmias HLT Ventricular arrhythmias and cardiac arrest Review terms within a grouping term Review terms within the HLGT or HLT of interest to be sure that all terms therein are suited for the purpose of the output. Example Blood Pressure Terms HLT Vascular tests NEC (incl blood pressure) PT Blood pressure abnormal PT Blood pressure decreased PT Blood pressure increased PT Blood pressure measurement Note that terms for increased and decreased blood pressure are grouped under a single HLT which also includes PTs for pulmonary arterial pressure, vascular resistance, haemodynamic tests, etc. Example as of MedDRA Version

75 2.5.2 Granularity MedDRA PTs are more specific ( granular ) than comparable terms in other terminologies. Figure 1 illustrates how data coded to a single concept from another terminology may be coded to several PTs in MedDRA. Related events that may have been represented by a single term in another terminology may be represented by more than one MedDRA PTs. The potential impact of this on signal detection should be kept in mind Multiaxiality Multiaxiality means that a PT may exist in more than one SOC. This allows terms to be grouped in different, but medically appropriate, ways (e.g., by etiology or organ system). Each PT is assigned one primary SOC; all other SOC assignments for that PT are called secondary. Having a single primary SOC prevents double counting of events when outputting data from all SOCs. All possible secondary SOC assignments for any given PT may not be present in MedDRA. However, new or revised SOC assignments can be created as a result of the change request process Primary SOC assignment rules Primary SOC assignment rules are described in the MedDRA Introductory Guide. These rules affect the way terms are placed in MedDRA and determine their data display by SOC. Because these rules allow for terms related to a particular medical condition to be in more than one SOC, users should be familiar with the general structure and content of all MedDRA SOCs to be sure that data are not overlooked. 8

76 Example Type of Disorder Primary SOC Rule Example Comment Congenital All terms for congenital disorders have as their primary SOC assignment SOC Congenital, familial and genetic disorders PT Congenital absence of bile ducts has a primary SOC assignment of SOC Congenital, familial and genetic disorders and a secondary SOC assignment of SOC Hepatobiliary disorders The secondary SOC assignment for these terms is their site of manifestation SOC Neoplastic All terms for malignant and benign neoplasms (except cysts and polyps) have as their primary SOC assignment SOC Neoplasms benign, malignant and unspecified (incl cysts and polyps) PT Skin cancer has a primary SOC assignment of SOC Neoplasms benign, malignant and unspecified (incl cysts and polyps) and a secondary SOC assignment of SOC Skin and subcutaneous tissue disorders Cyst and polyp terms are an exception to this rule. The primary SOC assignment for cyst and polyp terms is the site of manifestation SOC, and the secondary SOC is SOC Neoplasms benign, malignant and unspecified (incl cysts and polyps) Infectious All terms for infectious disorders have as their primary SOC assignment SOC Infections and infestations PT Enterocolitis infectious has a primary SOC assignment of SOC Infections and infestations and a secondary SOC assignment of SOC Gastrointestinal disorders The secondary SOC assignment for these terms is their site of manifestation SOC If a PT links to more than one of these three SOCs, the following priority is used to determine the primary SOC: SOC Congenital, familial and genetic disorders SOC Neoplasms benign, malignant and unspecified (incl cysts and polyps) SOC Infections and infestations 9

77 Non multiaxial SOCs Terms in the following three SOCs do not have multiaxial links: SOC Investigations SOC Surgical and medical procedures SOC Social circumstances This is important when designing queries and other retrieval strategies because one cannot rely on multiaxiality to locate all terms of interest in MedDRA. Example Impact of Non Multiaxial SOCs on Data Queries When querying a database for events or cases of thrombocytopenia, data coded to PTs in SOC Blood and lymphatic system disorders is a logical starting point. Additionally, data coded to terms in SOC Investigations such as PT Platelet count decreased and data coded to terms in SOC Surgical and medical procedures - such as PT Platelet transfusion could also be of interest. Neither of these PTs has a link to SOC Blood and lymphatic system disorders. Failure to consider data coded in the non multiaxial SOCs could lead to incomplete analysis of thrombocytopenia. As noted above, terms for test results are in SOC Investigations and do not have multiaxial links to terms for corresponding medical conditions. Keep this in mind when reviewing tables and data listings of MedDRA coded data. Example Terms for Test Results in SOC Investigations When querying a database for events or cases of hepatic abnormalities, data coded to PTs in SOC Hepatobiliary disorders is a logical starting point. Additionally, data coded to terms in SOC Investigations such as PT Liver function test abnormal and data coded to terms in SOC Surgical and medical procedures - such as PT Liver transplant could also be of interest. Neither of these PTs has a link to SOC Hepatobiliary disorders. Failure to consider data coded in the non multiaxial SOCs could lead to incomplete analysis. Figure 2 further illustrates the impact of data coded as test results vs. the corresponding medical condition. 10

78 Clinically related PTs Clinically related PTs might be overlooked or not recognized as belonging together because they might be in different groupings within a single SOC or they may be located in more than one SOC (see Section 2.5.3). Example Similar Skin Conditions in Different Groupings HLGT Epidermal and dermal conditions HLT Bullous conditions PT Stevens-Johnson syndrome PT Toxic epidermal necrolysis HLT Exfoliative conditions PT Dermatitis exfoliative PT Dermatitis exfoliative generalised PT Nikolsky's sign PT Skin exfoliation Example as of MedDRA Version 19.0 The frequency of a medical concept may be underestimated if the above points are not considered; this may impact interpretation of data (see Section 3.2). MedDRA SOCs group terms by body systems, aetiologies and specialised purposes. Data may be coded to terms in SOCs that had not been anticipated by the user. Keep in mind the potential impact of multiaxiality on frequencies of the medical condition of interest. Example Preferred Term Post procedural haemorrhage Chest pain Primary SOC Injury, poisoning and procedural complications General disorders and administration site conditions 2.6 MedDRA Versioning MedDRA is updated twice yearly. Version X.0 contains both simple and complex changes; version X.1 contains only simple changes. Organisations should be aware of the types of MedDRA changes for their possible impact on data output. 11

79 Types of MedDRA Changes Simple Changes Add a PT (new medical concept) Move an existing PT from one HLT to another Demote a PT to LLT level Add or remove a link to an existing PT Add an LLT Move an existing LLT from one PT to another Promote an LLT to PT level Make a current LLT non-current or a noncurrent LLT current Changing the primary SOC allocation Changes to SMQs Complex Changes Add or change multiaxial links Add new grouping terms Merge existing grouping terms Restructure a SOC Add a new SOC Both simple and complex changes impact retrieval and presentation strategies. Users should read the documentation provided with each MedDRA release, especially the What s New document. The MSSO and JMO provide tools to assist the user in comparing the changes between MedDRA versions. The Version Report (provided by the MSSO and JMO) is a spreadsheet listing all changes between the current version of MedDRA and the one previous to it; this spreadsheet is provided with each new release of MedDRA. The MSSO also provides the MedDRA Version Analysis Tool (MVAT) that facilitates identification and understanding of the impact of changes between any two MedDRA versions, including non-consecutive ones (see Appendix, Section 6.1 of this document; also, see Section of the MedDRA Term Selection: Points to Consider document). Organisations should plan and document their strategy for handling MedDRA version updates. When planning or performing data retrieval and presentation, the MedDRA version used should be documented. Keep in mind that MedDRA changes may impact previous data retrieval approaches and results, including event frequencies. 12

80 Example Impact of Version Changes Demoted PT PT Metastatic pain was included in a query developed using terms in MedDRA Version If the query had been re-run on data using MedDRA Version 19.0, these events would not have been found at the PT level because PT Metastatic pain had been demoted to an LLT and linked to PT Cancer pain. See Figure 3. Example as of MedDRA Version 18.1 and 19.0 Example Impact of Version Changes Change of Primary SOC Assignment PT Intra-abdominal haematoma had a primary link to SOC Vascular disorders and a secondary link to SOC Gastrointestinal disorders in MedDRA Version In Version 18.1, the primary SOC assignment was changed to SOC Gastrointestinal disorders and the secondary assignment to SOC Vascular disorders. In a primary SOC output of data, PT Intra-abdominal haematoma will seem to have disappeared from SOC Vascular disorders. Example as of MedDRA Version 18.0 and 18.1 Terms used to construct queries should be in the same MedDRA version as the data being queried. An organisation s legacy data may be coded in more than one version of MedDRA. New terms may have been included in a new query built in a newer MedDRA version; depending upon the organisation s versioning method, these new terms might not be present in the older data. This could lead to search results that are incomplete. A search built with terms of an earlier MedDRA version (e.g., used previously on a now closed study) might not identify all relevant data in an integrated safety summary (ISS) containing data coded in a later version of MedDRA. Queries stored in an organisation s system should be updated to the appropriate version of MedDRA before using them on new data. Advice on how an organisation should handle new MedDRA versions is not within the scope of this document (see MedDRA Term Selection: Points to Consider, Appendix 4.1). Some databases may contain data of multiple studies coded in different versions of MedDRA. This may impact aggregation of those data (e.g., in an ISS). Refer to MSSO documents on versioning options for clinical trial and post-marketing data for more information (see Appendix, Section 6.1). 13

81 SECTION 3 GENERAL QUERIES AND RETRIEVAL 3.1 General Principles Data retrieval is performed for summary and analysis of clinical trial data, pharmacovigilance, medical information questions and for a number of other purposes. The search strategies, methods and tools used to retrieve data might differ based on the intended use of the output. A general approach for data retrieval is outlined in the chart below. Define medical issues/safety question (See Section 3.1) Develop MedDRA search strategy (See Section 3.2.3) SMQ SOC with 2ry Links Grouping terms (HLGT, HLT) Customized search Modified MedDRA Query based on an SMQ Customized Query Retrieval of events or cases matching search strategy Assessment of data (events or cases) related to medical/safety issue or question 14

82 Prior to data retrieval, there may be known or potential safety issues that need detailed investigation. Information from pre-clinical studies, clinical trials post-marketing surveillance, class effects of similar products, and regulatory queries may identify areas of possible focus; these may affect the strategy for aggregating search terms, the methodology, and the way data are displayed. Be aware of database characteristics, organisation-specific data entry conventions, data sources, the size of the database, and the version of MedDRA used for coding all data. Archived searches may be available to the user, especially those used in pharmacovigilance; these may be suitable for use if updated. When presenting adverse event data, it is important to display and to group related events (i.e., events that represent the same condition of interest) so that the true occurrence rate of an event is not obscured. Search strategies should be documented. The search output alone may not suffice for data assessment (e.g., frequency of a condition). Search results should be evaluated against the question originally posed. Sorting related events into categories can be challenging. A search that is too narrowly focused might exclude events of potential relevance; a search that is too broad might make it difficult to identify a trend or signal. Careful interpretation is required when grouping terms that correspond to a potential event or medical condition for analysis (whether a syndrome or not). The purpose is to identify trends that may require further analysis, including review of individual cases. For complex queries, create a data analysis plan including a definition of the medical condition of interest. An interdisciplinary discussion might be helpful to identify the most suitable methods and tools relevant to the query. These principles may apply to the types of searches listed in the table below: Example Types of Searches Application of General Principles Safety profile overview in a summary report, Periodic Safety Update Report (PSUR), ISS, etc. Comparing frequencies of ARs/AEs reporting rates for spontaneous reports or incidence for studies) Analysis of a specific safety concern Identifying patient subpopulations at risk (search of medical history) Graphical displays Graphical displays can be useful especially with large datasets. Such displays allow quick visual representation of potential signals. Organisations are encouraged to use graphs for data display. Histograms, bar charts, and pie charts can be useful as can more complex, statistically-derived displays (e.g., data mining algorithms). Examples of these types of displays are in the Appendix, Section

83 3.1.2 Patient subpopulations For data retrieval for specific subpopulations such as those based on age or gender, it is necessary to refer to individual database fields for demographics. 3.2 Overall Presentation of Safety Profiles The aims of an overall safety profile presentation are to: Highlight distribution of ARs/AEs Identify areas for in depth analysis Present the data in a way that allows for easy recognition of patterns of terms potentially related to the relevant medical conditions. There are various ways to do this ranging from a full listing of terms to sophisticated statistical approaches such as data mining techniques (for reference, see ICH E2E: Pharmacovigilance Planning Document; listed in the Appendix, Section 6.1). Historically, the standard approach has been to display data by Body System (or System Organ Class) and Preferred Term corresponding to SOCs and PTs in MedDRA. Due to MedDRA s unique characteristics (multiaxiality, granularity), this PT-SOC approach may need to be augmented with other types of data outputs (e.g., secondary SOC output, display by grouping terms [HLTs, HLGTs], etc.), depending on the reason for the output. For example, if a number of reports describe a similar medical condition, they could be represented by: Many different PTs (dilution of signal) Different grouping terms Different SOCs SOCs where the user would not intuitively expect them (e.g., SOC General disorders and administration site conditions, SOC Pregnancy, puerperium and perinatal conditions, SOC Injury, poisoning and procedural complications, SOC Infections and infestations). See examples in the table below: PTs with Primary SOC General disorders and administration site conditions and Secondary SOC Cardiac disorders PT Chest discomfort PT Chest pain PT Oedema peripheral PT Sudden death PT Localised oedema PT Oedema due to cardiac disease PT Peripheral oedema neonatal PT Cardiac death Example as of MedDRA Version

84 3.2.1 Overview by primary System Organ Class This overview is recommended as a first step in data retrieval and for planning of further analysis. Display of all data ensures that all events will be seen and may be useful to identify data clusters by SOC. If the hierarchy is also displayed, clusters may occur at the HLGT or HLT levels. For a small dataset, this display by primary SOC may be all that is necessary. Objectives: Method: Include all events (none are omitted) Display all data in the entire MedDRA hierarchy The primary SOC view including HLGTs, HLTs and PTs can be used for standard tables (clinical trials and post-marketing data) and for cumulative summaries (post-marketing data). Line listings (both clinical and post-marketing data) can also be displayed by primary SOC and PT. Depending on the reason for the output, it might be beneficial to use the primary SOC and PT display; for large datasets, display by SOC and by grouping terms (HLGTs and HLTs) may be preferable. Figure 4 is an example of such an output. The Internationally Agreed Order of SOCs was developed for consistency irrespective of language or alphabet (see Figure 5). The SOC order was based upon the relative importance of each SOC in AR/AE reports. Use of the Internationally Agreed Order may be applicable to certain regulatory functions, e.g., the SPC guideline (see the MedDRA Introductory Guide and MedDRA ASCII files). Organisations that share data should agree on the order of SOCs when preparing data for presentation. Data displays in tables or in graphical presentations may facilitate understanding by the viewer. Figures 6, 7 and 8 are examples of such displays. Figures 9a and 9b display data for one compound in two patient populations. Within each patient population, the reports are split by SOC and by reporter. The upper bar of each pair represents numbers of reports from consumers (blue), and the lower bar represents reports from health care professionals (red). If further detail is needed, adverse events can be displayed by PT with decreasing frequency. In depth analysis requires medical expertise to define terms that should be aggregated. Benefits: Provides an overview of data distribution; helps identify areas of special interest that may need in depth analysis Grouping terms aggregate related PTs, facilitating identification of medical conditions of interest 17

85 A PT will be displayed only once, preventing over-counting of terms A primary SOC overview may be the only form of data display necessary for a small dataset Limitations: Because it is based on a PT-to-primary SOC assignment, there may be incomplete groupings of terms for a medical condition or syndrome as such terms may be distributed among different SOCs Events may not be found where the user expects them due to MedDRA placement rules Potential for a lengthy data output when applied to large datasets Overall presentations of small datasets When the safety profile consists of a small list of PTs (e.g., early in clinical development), a display of these PTs may be adequate. Figure 10 is an example of this Focused searches Focused searches may be useful for further investigation of medical concepts of interest. For example, a focused search may be used to determine the number of cases or events of interest in response to a regulatory query. In certain situations, such as those listed below (note that this list is not all-inclusive), users may wish to design a specific search in addition to the Overview by Primary System Organ Class (see Section 3.2.1). Further examination of clusters seen in Primary SOC output Previously identified safety concerns (e.g., known class effects, results from toxicology and animal studies, etc.) Monitoring events of special interest Responding to regulatory queries Below are listed options for focused search approaches. The order of applying these approaches may depend on resources, expertise, systems or other factors Focused searches by secondary SOC assignments This focused search augments the Overview by Primary System Organ Class (see Section 3.2.1) by addressing secondary SOC assignments, thus providing a more comprehensive view of the data and taking advantage of MedDRA s multiaxiality. Method: The method used for a focused search by secondary SOC assignment may depend on the database characteristics of the organisation. 18

86 Options include: Example Query of the SOC, HLGT and HLT levels to include both the primary and secondary SOC assignments in the display Output PTs in their secondary SOC locations programmatically (see Figure 11) If the database does not allow automated output by secondary SOC, then perform the query using available processes (e.g., programming a list of all individual PTs in the primary and secondary SOC locations) Programming a List of PTs in Primary and Secondary SOC Locations SOC Eye disorders HLGT Vision disorders HLT Visual pathway disorders PT Chiasma syndrome PT Optic nerve compression (primary SOC location) PT Optic nerve disorder (primary SOC location) PT Optic neuropathy (primary SOC location) PT Toxic optic neuropathy (primary SOC location) PT Visual cortex atrophy PT Visual pathway disorder 3 of 7 PTs are primary to SOC Nervous system disorders Example as of MedDRA Version 19.0 Benefits: Multiaxial links enhance the utility of the grouping terms. This method overcomes the primary SOC limitations as described under Section Limitations: Still displays only terms that are represented in one SOC or HLGT/HLT which may not include all terms related to a medical condition This method of display of PTs by both primary and secondary SOC assignments could lead to double counting of cases/events 19

87 SECTION 4 STANDARDISED MedDRA QUERIES 4.1 Introduction Standardised MedDRA Queries (SMQs) were created to standardise identification and retrieval of safety data. SMQs are a joint effort of the Council for International Organizations of Medical Sciences (CIOMS) and ICH (including MSSO and JMO) representing both industry and regulatory authorities. An SMQ is a grouping of terms from one or more SOCs that relate to a defined medical condition or area of interest. The terms included relate to signs, symptoms, diagnoses, syndromes, physical findings, laboratory and other physiologic test data, etc. that are associated with the medical condition or area of interest. Users should carefully read the Introductory Guide for Standardised MedDRA Queries (SMQs) before applying an SMQ to fully understand the scope of the SMQ and to properly apply search options such as algorithms and weightings. 4.2 SMQ Benefits As with all MedDRA-based queries, users of SMQs should be aware of several factors that may influence data retrieval including database characteristics, data conversion processes, coding conventions, and MedDRA versioning. For more details, see Section 3.1. SMQ benefits include: Application across multiple therapeutic areas Validated reusable search logic Standardised communication of safety information Consistent data retrieval Maintenance by MSSO and JMO 4.3 SMQ Limitations SMQs do not cover all medical topics or safety issues SMQs evolve and undergo further refinement even though they have been tested during development 4.4 SMQ Modifications and Organisation-Constructed Queries If any modifications are made to term content or structure of an SMQ, it can no longer be called an SMQ but it should instead be referred to as a modified MedDRA query based on an SMQ. See Section 5.1 for further details on SMQ modification. 20

88 Under no circumstances should a query constructed for the specific need of an organisation be called an SMQ by its originator. This is to ensure that there is no confusion with the ICH-endorsed SMQs applied by other MedDRA users. Any alternate name for the organisation-constructed query is acceptable as long as it could not be potentially confused with an ICH-endorsed SMQ. 4.5 SMQs and MedDRA Version Changes Each SMQ relates to a specific MedDRA version. SMQs are part of each new MedDRA release, are maintained by MSSO and JMO, and correspond to the terms present in that version of MedDRA. The SMQ version should always correspond to the MedDRA version of the data being searched. As with all searches of MedDRA-based data, it is important to document the MedDRA and SMQ versions used. Changes to SMQs that can occur with each MedDRA version include (but are not limited to) the following: Addition of PTs Inactivation of a PT (i.e., effectively removing a PT from an SMQ) Change of term scope (e.g., a narrow term becomes a broad term) Restructuring of an SMQ (e.g., change in the hierarchical position of an SMQ) Creation of a new SMQ For a full description of the types of changes that can occur to SMQs, please refer to the MedDRA Change Request Information document (see Appendix, Section 6.1). Changes introduced with each new version are documented in the What s New document for each MedDRA version. (The cumulative changes are contained within the ASCII files in the fields called Term_addition_version and Term_last_modified_version ). The MedDRA version of the SMQ and the coded data being searched should be the same because mismatches could produce unexpected results. For example, if an SMQ from an older version of MedDRA is applied to data coded in a more recent version, data coded to terms that are not present in the older SMQ would not be retrieved. Example Consequence of Version Mismatch of Coded Data and SMQ PT End stage renal disease was added to SMQ Chronic kidney disease in MedDRA Version Using Version 18.1 of this SMQ which does not contain this PT would fail to identify cases coded to this term in a database using MedDRA Version Example as of MedDRA Version 18.1 and

89 4.6 SMQs Impact of MedDRA Legacy Data Conversion The conversion method for data originally coded in another terminology (e.g., COSTART) also impacts the application and output of SMQs. See Section 2.1.2, Impact of data conversion method. 4.7 SMQ Change Requests Users are encouraged to submit Change Requests to MSSO and JMO to improve the utility of SMQs. A justification (and possibly testing data) for a submitted Change Request must be provided. The MSSO may require more time to evaluate SMQ Change requests than regular MedDRA Change Requests. Before submitting an SMQ Change Request, users should review the SMQ documentation for inclusion and exclusion criteria of the SMQ. 4.8 SMQ Technical Tools The MSSO browsers (both the Desktop and Web-Based browsers) allow for searching and viewing the contents of SMQs and they include additional details such as the SMQ description (definition) and development notes. An Excel spreadsheet containing the terms in each production SMQ is available from MSSO and JMO (see Appendix, Section 6.1). This spreadsheet allows a user to transfer SMQ terms to query tools. File specifications related to SMQs are found in the MedDRA Distribution File Format Document supplied with each MedDRA version. The MedDRA website has a list of some system tools that provide technical support for SMQs (see Appendix, Section 6.1). 4.9 SMQ Applications SMQs were developed to address the high granularity and unique features of MedDRA and to maximise the likelihood that all terms related to a specific medical condition of interest are identified. The user should first review the list of available SMQs to determine which of them may be applicable to the question being asked. If an SMQ seems applicable, the user should check the documentation in the SMQ Introductory Guide to understand the purpose and definition of the SMQ. The user may also wish to review the term contents of the SMQ. Following application of the selected SMQ on coded data, search results (i.e., retrieved data) should then be evaluated against the question originally posed. The search output alone may not be sufficient for data assessment (e.g., frequency of a condition). Define and document criteria for case evaluation. 22

90 Generally, more cases/events will be retrieved than will eventually be subjected to analysis due to noise. This is a more significant consideration for broad searches but in principle also applies to narrow searches (see Section ) Clinical trials SMQs may be applied in the clinical trial setting especially for aggregate data where the safety profile has yet to be fully established. In this instance, most (if not all) available SMQs may be used, possibly on a routine basis. Alternatively, a user can apply an SMQ (or SMQs) that relates to a previously identified area of interest (e.g., from pre-clinical data or class effect) for further evaluation. Example Targeted Safety Study When developing a data analysis plan for a targeted safety study, consider using the narrow terms of an SMQ to aggregate events of interest Post-marketing Focused searches A specific SMQ or a selection of SMQs may be used to retrieve relevant cases for subsequent medical review. Example Emerging Safety Signal A company suspects an emerging signal of pancreatitis for a new HIV product. SMQ Acute pancreatitis can be applied to the data Signal detection The entire set of SMQs may be used on the database for signal detection. The user may wish to use the narrow terms or more specific levels of hierarchical SMQs (i.e., a subsearch SMQ) to minimise dilution of the signal Single case alert SMQs may be used to create a watch list (e.g., an automated notification system) to alert the user of incoming cases needing urgent review. Example Single Case Alert A medical issue of interest needs to be communicated to a regulatory authority as part of an agreed risk management plan. The SMQ narrow search or more specific levels of a hierarchical SMQ may be applied to identify potential cases of interest. 23

91 Periodic reporting SMQs may help aggregate relevant cases for ongoing review of specific safety issues in periodic safety reports. SMQs may also be used for other routine reviews of aggregate data (e.g., reports of lack of efficacy) in the context of a periodic report SMQ Search Options Some SMQs have options that may be used to refine a particular search. The most common option is use of narrow and broad search terms. By definition, a broad search includes both narrow and broad terms. Some SMQs are hierarchical (i.e., contain one or more sub-searches). Other SMQs use algorithms, and in one case (SMQ Systemic lupus erythematosus), weightings are assigned to particular terms for signs, symptoms and laboratory results to help identify cases Narrow and broad searches Most SMQs have narrow and broad PTs. The narrow PTs have a greater likelihood of identifying only events of interest (high specificity) while the broad terms are intended to identify additional possible events (high sensitivity). Some events retrieved by the broad search terms may, upon further review, not relate to the condition of interest. The user can select the scope of the search (narrow or broad) that is most applicable to the question being asked. Figure 12 is an example of output of narrow and broad searches. When a compound is in early phase development or has only recently been marketed, it may be advisable to use the broad search. Example Use of Broad Search If evaluating an emerging signal of lactic acidosis using SMQ Lactic acidosis, narrow terms may be applied to identify events where the specific diagnosis has been reported; however, events of reported signs and symptoms would not be retrieved. If there is additional need to find cases where no specific diagnosis (but mainly signs and symptoms) have been reported, then a broad search (i.e., narrow + broad search terms) should be applied Hierarchical SMQs Several SMQs have a hierarchical structure (one or more levels of sub-searches of increasing specificity). The user can select the search that is most applicable to the question being asked or a combination of sub-search SMQs as needed. The SMQ Introductory Guide has explanatory notes on the appropriate use of each hierarchical SMQ. An example of a hierarchical SMQ is illustrated below (SMQ Haematopoietic cytopenias). 24

92 Haematopoietic cytopenias (SMQ) ( ) Haematopoietic cytopenias affecting more than one type of blood cell (SMQ) ( ) Haematopoietic erythropenia (SMQ) ( ) Haematopoietic leukopenia (SMQ) ( ) Haematopoietic thrombocytopenia (SMQ) ( ) Example Use of SMQ Hierarchy The medical condition of interest is thrombocytopenia. SMQ Haematopoietic cytopenias may be too inclusive because sub-searches for decreases of other hematopoietic cell lines (e.g., SMQ Haematopoietic leukopenia) are included. A user may wish to select only the sub-search SMQ Haematopoietic thrombocytopenia in this instance Algorithmic SMQs An algorithm provides for a combination of terms which if retrieved in a single case are more likely to identify a case of interest than isolated broad search terms (see table below). The broad terms of algorithmic SMQs are subdivided into categories that could be groupings of organ-specific signs or symptoms, laboratory terms, etc. (Note: the broad search categories are labeled B, C, D, etc.) Using an algorithm may reduce the amount of noise (i.e., non-relevant cases). Using an algorithmic SMQ without applying the algorithm (i.e., simply applying the narrow and broad searches) will yield different results from those obtained using the algorithm. 25

93 Example Category B Upper airway/respiratory Algorithmic SMQ (SMQ Anaphylactic reaction)* Category C Angioedema/Urticaria, etc. Category D Cardiovascular/Hypotension Acute respiratory failure Allergic oedema Blood pressure decreased Asthma Bronchial oedema Algorithm: Angioedema Erythema Case = A (Narrow terms not included in the table) Or term from Category B and term from Category C Blood pressure diastolic decreased Blood pressure systolic decreased Or term from either Category B or Category C plus term from Category D * Not all terms in these categories are listed in the table SMQ Systemic lupus erythematosus is an algorithmic SMQ with assigned weights for its included PTs (e.g., PT Pleural effusion = 3); a total weighted score greater than 6 suggests a case of interest. Users should not assume that all software tools support algorithmic SMQs SMQ and MedDRA Grouping Terms Data retrieved using MedDRA grouping terms (HLGTs, HLTs) may differ from those retrieved using a related SMQ. Example Comparison SMQ and Grouping Terms Cardiac arrhythmia is a suspected issue (e.g., by review of a primary SOC output of all data). If events retrieved by using HLGT Cardiac arrhythmias are compared to those retrieved by SMQ Cardiac arrhythmias, more events may be retrieved by the SMQ because it includes additional terms from other SOCs such as SOC Investigations. 26

94 SECTION 5 CUSTOMISED SEARCHES MedDRA allows for a variety of searching options as described above. However, there will be situations when a customised search is needed. 5.1 Modified MedDRA Query Based on an SMQ Do not modify the term content or structure of an SMQ unless there is a compelling reason to do so since altering it in any way makes it non-standard (see Section 4.4). If an SMQ is modified in any way, it should be referred to as a modified MedDRA query based on an SMQ. All modifications to the original SMQ should be documented. If a modified MedDRA query based on an SMQ is to be used on an ongoing basis, version updates and maintenance of the query are the responsibility of the organisation that created it. Example Modified MedDRA Queries based on SMQs Additional PTs are needed Exclusion of PTs Changing the scope (narrow or broad) of an SMQ term A product is being investigated for a possible safety signal of dementia, and the user wishes to use SMQ Dementia. For this particular product, PT Disturbance in attention may be needed. An antipsychotic product is being investigated for potential QT prolongation and also has a well-described association with hypotension and fainting. When using SMQ Torsade de pointes/qt prolongation (broad search), the user may wish to exclude PT Syncope to prevent excess noise in data retrieval. A product is being investigated for the potential for hyperglycaemia and diabetes mellitus. SMQ Hyperglycaemia/new onset diabetes mellitus has PT Increased insulin requirement as a broad search term. For this query, it may be useful to include PT Increased insulin requirement in the narrow search. 5.2 Customised Queries Consider these points when constructing a customised query for MedDRA-coded data: Those responsible for constructing a customised query should: o Have medical knowledge 27

95 o o Know the structure and characteristics of MedDRA (e.g., hierarchy, multiaxiality) and the general content of MedDRA groupings (SOCs, HLGTs, and HLTs) Understand the characteristics and structure of the data The specificity of the search should be defined. Initial focus should be on SOCs related to the condition of interest. For example, a customised search for a renal condition should start with SOC Renal and urinary disorders. The non multiaxial SOCs (SOC Investigations, SOC Surgical and medical procedures and SOC Social circumstances) should always be reviewed. Also, it may be useful to review terms in other SOCs that are not organ systems (e.g., SOC General disorders and administration site conditions, SOC Injury, poisoning and procedural complications and SOC Pregnancy, puerperium and perinatal conditions). It may be useful to identify relevant query terms by the following approaches: o o A bottom-up survey of MedDRA (terms at the LLT and PT levels initially) A top-down survey of MedDRA (starting at the SOC level and drilling down through the hierarchy) Consider looking at secondary links for multiaxial terms since additional relevant query terms could be found. For example, PT Dyspnoea can be found with other respiratory symptoms PTs in its primary SOC Respiratory, thoracic and mediastinal disorders, and it can also be found with related cardiac symptoms in its secondary SOC Cardiac disorders. Include grouping terms (HLGTs, HLTs) when possible (remembering the caveats described in Section 2.5.1). In general, queries should be built on PTs and grouping terms. Unless very specific concepts (e.g., bacterial species) are needed, avoid using LLTs to build queries. Consider saving the customised query for future use; maintenance is necessary for MedDRA version changes. A customised query that may be useful to other MedDRA users can be submitted to the MSSO as a Change request for possible development as an SMQ. 28

96 SECTION 6 APPENDIX 6.1 Links and References The following documents and tools can be found on the MedDRA website: ( MedDRA Term Selection: Points to Consider document (also available on the JMO website: MedDRA Introductory Guide Introductory Guide for Standardised MedDRA Queries (SMQs) MedDRA Change Request Information document MedDRA Web-Based Browser * MedDRA Desktop Browser MedDRA Version Report (lists all changes in new version) * MedDRA Version Analysis Tool (compares any two versions) * MSSO s Recommendations for Single Case Reporting using Semi-annual Version Control MSSO s Recommendations for MedDRA Implementation and Versioning for Clinical Trials Transition Date for the Next MedDRA Version Production SMQ spreadsheet* List of system tools that support SMQs * Requires user ID and password to access The following document can be found on the ICH website ( ICH E2E: Pharmacovigilance Planning The following report can be found on the CIOMS website ( Development and Rational Use of Standardised MedDRA Queries (SMQs): Retrieving Adverse Drug Reactions with MedDRA. Second edition. 29

97 6.2 Membership of the ICH Points to Consider Working Group Current members of the ICH Points to Consider Working Group Affiliation Member Commission of the European Communities European Federation of Pharmaceutical Industries and Associations Health Canada Japanese Maintenance Organization Japan Pharmaceutical Manufacturers Association MedDRA MSSO Ministry of Health, Labour and Welfare/Pharmaceuticals and Medical Devices Agency Pharmaceutical Research and Manufacturers of America US Food and Drug Administration World Health Organization Maria Luisa Casini Kavita Chadda Hilary Vass* Christina Winter Dwana Pritchett Lynn Macdonald Yutaka Nagao Kazuyuki Sekiguchi Mitsuru Takano Tomoko Narita Yo Tanaka Hitomi Takeshita Miyako Shionoiri Judy Harrison Daisuke Inoue Miki Ohta Daisuke Sato Yasuko Inokuma Kiyomi Ueno Milbhor D Silva Sonja Brajovic # Christopher Breder Daisuke Tanaka * Current Rapporteur # Regulatory Chair Former Rapporteur 30

98 6.2.2 Former members of the ICH Points to Consider Working Group Affiliation Member Commission of the European Communities European Federation of Pharmaceutical Industries and Associations Health Canada Japanese Maintenance Organization Japan Pharmaceutical Manufacturers Association MedDRA MSSO Ministry of Health, Labour and Welfare/Pharmaceuticals and Medical Devices Agency Pharmaceutical Research and Manufacturers of America US Food and Drug Administration Dolores Montero; Carmen Kreft-Jais; Morell David; Sarah Vaughan Barry Hammond ; Reinhard Fescharek Alison Bennett; Valérie Bergeron; Heather Morrison; Polina Ostrovsky; Michelle Séguin; Stephanie Silva; Heather Sutcliffe; Bill Wilson Osamu Handa; Akemi Ishikawa; Yasuo Sakurai; Yuki Tada; Reiji Tezuka Takayoshi Ichikawa; Akemi Ishikawa; Satoru Mori; Yasuo Sakurai; Kunikazu Yokoi JoAnn Medbery; Patricia Mozzicato Yuhei Fukuta; Tamaki Fushimi; Wakako Horiki; Sonoko Ishihara; Makiko Isozaki; Kazuhiro Kemmotsu; Tatsuo Kishi; Chie Kojima; Emiko Kondo; Hideyuki Kondou; Kemji Kuramochi; Tetsuya Kusakabe; Kaori Nomura; Izumi Oba; Shinichi Okamura; Yoshihiko Sano; Nogusa Takahara; Kenichi Tamiya; Daisuke Tanaka; Shinichi Watanabe; Takashi Yasukawa; Go Yamamoto; Manabu Yamamoto; Nobuhiro Yamamoto David Goldsmith; Sidney Kahn; Anna-Lisa Kleckner; Susan M. Lorenski; JoAnn Medbery; Margaret M. Westland Miles Braun; Andrea Feight; John (Jake) Kelsey ; Brad Leissa; Toni Piazza-Hepp Former Rapporteur 31

99 6.3 Figures OTHER TERMINOLOGY PREFERRED TERMS No. of EVENTS MedDRA Version 19.0 PREFERRED TERMS No. of EVENTS Infection 15 Upper respiratory tract infection Nasopharyngitis Infection Lower respiratory tract infection Skin infection Abdominal pain 9 Abdominal pain Accidental injury 4 Injury Abdominal pain upper Abdominal tenderness Laceration Ligament sprain Back injury Figure 1 How data coded to a single concept from another terminology may be expressed by several PTs in MedDRA. Example as of MedDRA Version

100 Reported Event (% subjects) Hyperglycaemia (4.1) Increased blood sugar (2.7) Glucose increased (2.2) Blood glucose high (1.0) Increasing glucoses (0.5) OTHER TERMINOLOGY MedDRA Version 19.0 Coded Term (% subjects) Hyperglycaemia (10.5) Body System/SOC (% subjects) Metabolism & nutritional disorders (10.5) PT (% subjects) Hyperglycaemia (4.1) Blood glucose increased (6.4) SOC (% subjects) Metabolism and nutrition disorders (4.1) Investigations (6.4) Figure 2 Multiple MedDRA terms may be used to code similar medical conditions included in a disorder SOC ; associated laboratory findings are in SOC Investigations. Example as of MedDRA Version Preferred Terms MedDRA Version 18.1 Events/Cases MedDRA Version 19.0 Metastatic pain 15 0 (no longer a PT) Cancer pain 5 20 Figure 3 Impact of MedDRA version changes demotion of a PT Example as of MedDRA Version 18.1 and 19.0 Comment In MedDRA Version 18.1, Metastatic pain was a PT and in Version 19.0 it was demoted to an LLT under PT Cancer pain 33

101 Figure 4 Primary SOC output listing, MedDRA Version 17.1 example. Note that some PTs are multiaxial, however, this figure shows only the primary SOC assignments 34

102 MedDRA Version 20.0 English Alphabetical Order Blood and lymphatic system disorders Cardiac disorders Congenital, familial and genetic disorders Ear and labyrinth disorders Endocrine disorders Eye disorders Gastrointestinal disorders General disorders and administration site conditions Hepatobiliary disorders Immune system disorders Infections and infestations Injury, poisoning and procedural complications Investigations Metabolism and nutrition disorders Musculoskeletal and connective tissue disorders Neoplasms benign, malignant and unspecified (incl cysts and polyps) Nervous system disorders Pregnancy, puerperium and perinatal conditions Product issues Psychiatric disorders Renal and urinary disorders Reproductive system and breast disorders MedDRA Version 20.0 Internationally Agreed Order Infections and infestations Neoplasms benign, malignant and unspecified (incl cysts and polyps) Blood and lymphatic system disorders Immune system disorders Endocrine disorders Metabolism and nutrition disorders Psychiatric disorders Nervous system disorders Eye disorders Ear and labyrinth disorders Cardiac disorders Vascular disorders Respiratory, thoracic and mediastinal disorders Gastrointestinal disorders Hepatobiliary disorders Skin and subcutaneous tissue disorders Musculoskeletal and connective tissue disorders Renal and urinary disorders Pregnancy, puerperium and perinatal conditions Reproductive system and breast disorders Congenital, familial and genetic disorders General disorders and administration site conditions 35

103 MedDRA Version 20.0 English Alphabetical Order Respiratory, thoracic and mediastinal disorders Skin and subcutaneous tissue disorders Social circumstances Surgical and medical procedures MedDRA Version 20.0 Internationally Agreed Order Investigations Injury, poisoning and procedural complications Surgical and medical procedures Social circumstances Vascular disorders Product issues Figure 5 The alphabetical SOC order (in English) and the Internationally Agreed Order of SOCs Figure 6 Example of a graphical display (frequency by primary SOC) 36

104 Figure 7 Example of a graphical display (frequency by primary and secondary SOC) 37

105 System Organ Class Figure 8 Example of a tabular display (frequency by primary SOC) Nervous system disorders Skin and subcutaneous tissue disorders Psychiatric disorders General disorders and administration site conditions Gastrointestinal disorders Investigations Injury, poisoning and procedural complications Reproductive system and breast disorders Ear and labyrinth disorders Musculoskeletal and connective tissue disorders Eye disorders Cardiac disorders Vascular disorders Immune system disorders Respiratory, thoracic and mediastinal disorders Renal and urinary disorders Blood and lymphatic system disorders Metabolism and nutrition disorders Infections and infestations Hepatobiliary disorders Endocrine disorders Neoplasms benign, malignant and unspecified Social circumstances Surgical and medical procedures Pregnancy, puerperium and perinatal conditions Congenital, familial and genetic disorders Number of Reports Figure 9a The upper bar of each pair represents numbers of reports from Consumers (blue) and the lower bar reports from Health Care Professionals (red) (Population 1) 38