ARPEC Protocol for Drug Utilization Study

Home , Adefovir, Aldesulfone sodium, ATC code D06, ATC code J01, Capreomycin, Carindacillin

Study Protocol for Drug Utilization Study WP4 – Primary Care Antibiotic ARPEC Prescribing for Common Childhood Security: CO A 2009-11-01 Infections Author(s): Sandra de Bie, Katia Verhamme, Version: 1 1/32 Miriam Sturkenboom (all EMC)

ARPEC

Antibiotic Resistance and Prescribing in European Children

ARPEC Project A 2009-11-01

Protocol for Drug Utilization Study

WP4 – Primary Care Anti-infective agent prescribing for Common Childhood Infections

Version 1

Contents DOCUMENT INFORMATION ...... 3 DOCUMENT HISTORY ...... 3 DEFINITIONS ...... 4 ABBREVIATIONS ...... 5 DISEASE CLASSIFICATION SYSTEMS USED BY THE DATABASES ...... 6 INTRODUCTION...... 7 1. BACKGROUND ...... 7 2. STUDY OBJECTIVE ...... 7 3. STUDY DESIGN ...... 10 4. SOURCE DATA ...... 10 5. STUDY PERIOD ...... 12 6. STUDY POPULATION ...... 12 7. FOLLOW-UP PERIOD ...... 12 8. DATA COLLECTION ...... 13 OUTCOME MEASURES ...... 14 POPULATION LEVEL ...... 14 PERSON LEVEL USE ANALYSES ...... 15 DISEASE LEVEL ...... 16 PRESCRIPTION LEVEL ANALYSES ...... 17 ANALYSES OF ANTIBIOTIC USE ...... 19 TIMELINES ...... 20 APPENDIX 1: STUDY DRUGS ...... 21

Document Information

Grant Agreement A 2009-11-01 Acronym ARPEC Number Full title Antibiotic Resistance and Prescribing in European Children Project URL http://www.arpecstudy.eu EU Project officer

Deliverable Work package WP4

Delivery date Contractual n/a Actual n/a Status Draft final  Nature Report  Prototype  Other  Dissemination Public  Confidential  Level

Authors Sandra de Bie, Katia Verhamme, Miriam Sturkenboom (Partner) Responsible Miriam Sturkenboom Email [email protected] Author Partner EMC Phone +31-10-7044123

Document History Name Date Version Description Miriam Sturkenboom, Katia 13-10- 1 Verhamme and Sandra de Bie 2011

Definitions

. Associated partners of the ARPEC are referred to herein according to the following codes:

SGUL St George‟s University of London United Kingdom ESPID European Society of Pediatric Infectious Diseases ASIC PENTA Paediatric European Network for Treatment of AIDS PEDIANET Paedianet database Italy FIHBHGM EMC Erasmus University Medical Center Netherlands SERMAS Servicio Madrileño de Salud Spain UT NKUA National and Kapodistrian University of Athens Greece CVBF Consorzio per le Valutazioni Biologiche e Farmacologiche Italy UKL-FR UMCL UA University of Antwerp Belgium UMIL Universita Degli Studi Di Milano Italy VUCH Vilnius University Children Hospital Lithuania

. Grant Agreement: . Project: . Work plan: . Consortium: . Consortium agreement: . Foreground: . Background:

Abbreviations

The following abbreviations are used in this report: . ATC – anatomical therapeutic chemical classification system . DDD – defined daily dose . GP – general practitioner . ICD-9-CM – international classification of disease, 9th rev., clinical modification . ICD-10-GM – international classification of disease, 10th rev., German modification . ICPC – international classification of primary care . IPCI – Integrated Primary Care Information Project . THIN - The Health Improvement Network . Rx - prescription . WP – work package

Disease classification systems used by the databases

IPCI – ICPC BIFAP– ICPC PEDIANET database – ICD-9-CM THIN database – READ codes

INTRODUCTION

1. Background

The study Antibiotic Resistance and Prescribing in European children (ARPEC) is an initiative by the European Society of Pediatric Infectious Diseases (ESPID) to improve the evidence base for antibiotic prescribing in European Children. The overall aim of the project is to improve antimicrobial prescribing in hospitals and in the community, by obtaining up-to-date, clinically relevant data on variation in clinical management and antimicrobial resistance rates and then to feed this back via a number of educational initiatives, to paediatricians in-training and in clinical practice, across Europe. For this study, we will build on existing paediatric infectious diseases networks, including PENTA, ESPID and TEDDY. The project uses established methodologies from ESAC and EARSS and existing community prescribing databases to develop a prospective surveillance system to monitor rates of antibiotic prescribing and resistance in European children The project has been funded by the Executive Agency for Health and Consumers (EAHC) through DG SANCO.

The current document describes the design of the drug utilization study within the context of the WP4 – Primary Care Antibiotic Prescribing for Common Childhood Infections of the ARPEC project; leader Erasmus University Medical Center (EMC).

The purpose of this drug utilization study is fourfold. First, patterns of anti-infective drug use will be analyzed, in terms of prevalence, incidence, volume and dose of use on a population level. Secondly, the volume and duration of use on a person level will be analyzed. Thirdly, the volume of use for the most common childhood infections will be analyzed. Fourth, and last, the data will be analyzed on a prescription level.

A common data protocol will be produced to prepare standardized input files to study prescription patterns in Italy (IT), The Netherlands (NL), Spain (ES) and the United Kingdom (UK), making use of the Pedianet database (IT), the Integrated Primary Care Information (IPCI) database (NL), the Health Improvement Network (THIN) (UK) and the BIFAP database (ES) respectively. All include the complete automated records of primary care doctors, with information on patient demographics, prescription data (including indication of use) and diagnosis. Using these databases, person time of follow up for each child can be calculated and stratified by calendar year and age group. All anti-infective agents prescribed in children during the follow up will be retrieved from prescription data and grouped on the basis of the WHO ATC System. Age and country specific prevalence rates for individual anti-infective agents will be calculated and linked to the indications of use.

2. Study Objective

The aim of this drug utilization study is to describe anti-infective drug utilization on four levels

Population level

a) Prevalence of use during the study period by country, age groups, gender, type of anti- infective (class and ATC7-level), and calendar time (year or month or week) (see appendix for which drugs are considered study drugs)

 Several age group classifications will be considered: o Based on the ICH categories . 0 - < 2 years . 2 - ≤ 11 years . 12 - < 18 years o Based on the „Blue book‟ . 0 - < 1 years . 1- < 5 years . 5 - < 12 years . 12 - < 18 years o One year categories . 0 - < 1 years . 1 - < 2 years . etc.

 Monthly prevalence is defined as the number of users per 1,000 person-months.  Yearly prevalence is defined as the number of users per 1,000 person-years.  A user is defined as a child with at least one prescription of the drug of interest in the period of interest (month or year) b) Total volume of use (prescriptions per month, person time of exposure) by country, age group, gender, type of antibiotic (class and ATC7-level), and calendar time.

 DU90% methodology stratified by country: how many antibiotics cover 90% of the prescriptions

 Volume of use will be expressed as: o Absolute number of prescriptions / child / month or /year o # mg / kg. The number of kg will be estimated using standardised weights per gender and age. o # mg / m2. The body surface area will be estimated using standardised weights and heights per gender and age. o The number of defined daily doses (DDDs) per 1,000 person-months or per 1,000 person-years; using the WHO methodology for DDDs o The number of defined daily doses (DDDs) per 1,000 person-months or per 1,000 person-years; using neonatal and pediatric DDDs that are currently under development. This method will use weight bands . 0-10 kg . 10-25 kg . 25-40 kg . 40-80 kg

 A pilot-study will be performed to test the performance of these different methods for estimating the volume of use.

Person level a) Volume of use per user  total number of Rx  number of Rx/person-month or / person-year o Stratified by type  duration of use /person-year  cumulative duration

b) Total number of different anti-infective agents used by a person during study period  Number of ATC codes within class within the period  Switching to determine treatment failure

Disease level a) Incidence of common childhood infections from the different databases will be analyzed. The following common childhood infections will be taken into account:

To study antibiotic use:  Respiratory tract infections i. Upper respiratory tract infections 1. Otitis Media 2. Tonsillitis + pharyngitis 3. Sinusitis ii. Lower respiratory tract infections 1. Bronchitis+ bronchiolitis 2. Pneumonia  Bacterial skin infections i. Impetigo and abscesses  Urinary tract infections  Gastro-enteritis  Fever To study systemic anti-viral use:  Chicken pox infections (varicella)  Herpes stomatitis  Influenza o To study systemic anti-mycotic use:  Oral candidiasis

b) For these common childhood infections it will be analysed which anti-infective drug is prescribed: Prevalence of anti-infective drug use during the disease episode by country, age groups, gender, type of anti-infective agent (class and ATC7-level) and calendar time (year or month) for the common childhood infections as defined at a). c) Additionally it will be analysed what proportion off all prescriptions of a drug-class is for these common childhood infections d) Co-existing of asthma for patients receiving antibiotic drugs for the treatment of lower respiratory infections will be taken into account in the analysis.

Prescription level For the analysis at prescription level the patient determinants at prescription of an anti-infective agent will be analyzed: . Characteristics of patients for each prescription: Age, gender, time, indication (see common childhood infections), dose (in mg; in mg/kg; in mg/m2; in #DDDs (see volume of use)), formulation, . Prior treatments with anti-infectives in previous year

This analysis allows for assessing correctness of prescriptions (dose/indication)

3. Study Design

The drug utilization study is a descriptive retrospective observational study.

4. Source data

The underlying population will consist of all eligible children, aged 0 to18 years, (see 6 Study population) retrieved from the following databases:

In 1992 the Integrated Primary Care Information Project (IPCI) was started by the Department of Medical Informatics of the Erasmus University Medical Center. IPCI is a longitudinal observational database that contains data from computer-based patient records of a selected group of general practitioners (GPs) throughout the Netherlands, who voluntarily chose to supply data to the database. GPs receive a minimal reimbursement for providing their data. They completely control usage of their data, through the Steering Committee and are permitted to withdraw data for specific studies. Collaborating practices are located throughout the Netherlands and the collaborating GPs are comparable to other GPs in the country according to age and gender. The database contains information on about 1.2 million patients. This is the cumulative amount of patients who have ever been part of the dynamic cohort of patients who have been registered. Turnover occurs as patients move and transfer to new practices. The records of „transferred out‟ patients remain in the database and are available for retrospective studies with the appropriate time periods. The system complies with European Union guidelines on the use of medical data for medical research and has been validated for pharmaco-epidemiological research. Approval for this study will be obtained from the „Raad van Toezicht‟ an IPCI specific ethical review board. The International Classification of Primary Care (ICPC) is the coding system for patient complaints and diagnoses, but diagnoses and complaints can also be entered as free text. Prescription data such as product name, quantity prescribed, dosage regimens, strength and indication are entered into the computer. The National Database of Drugs, maintained by the Royal Dutch Association for the Advancement of Pharmacy, enables the coding of prescriptions,

according to the Anatomical Therapeutic Chemical (ATC) classification scheme recommended by the WHO1 2.

Pedianet is an organised electronic network of family paediatricians (FPs) which has been established in 1998 to collect information for clinical and epidemiological research (www.pedianet.it). The system is based on the transmission of specific data (determined by individual studies) from computerised clinical files, which the paediatricians in the network fill out during their daily professional activities.

The PEDIANET database (www.pedianet.it) is a paediatric general practice research database comprising the clinical data of about 130 family paediatricians (FPs) distributed throughout Italy. Pedianet has been built up since 1999 by the Società Servizi Telematici (So.Se.Te.) based in Padova. PEDIANET currently collects the clinical, demographic, and prescription data for children that have provided informed consent and who are under the care of any FPs that currently provide data to the database (in Italy all children until the age of 14 are registered with a FP). Data are generated during routine patient care with the software JuniorBit ® and are stored in different files, which can be linked through a unique (anonymous) numerical identifier. The identification file contains information on the demographic data of the child and the eligibility status (registration status, date of registration, date of death). The prescription file contains information on all drugs (date of prescription, ATC code, product, formulation, quantity, dosing regimen, legend duration, indication, reimbursement status) and on all vaccinations that are prescribed by the paediatricians. Reasons for contact and diagnoses or hospitalizations (free text or coded by the ICD-9 system) are collected in the medical file. In addition the database contains information on referrals and examinations as well as data on growth. All data are stored and analysed according to the Italian privacy law. By December 2008 Pedianet database stored data from 250,000 children, these data are updated on a continuous basis. Various studies have been conducted with the PEDIANET database3-8.

The Health Improvement Network (THIN) is a database of primary care medical records from the United Kingdom. General practitioners are trained to complete their medical records using the Vision general practice computer system (InPractice Systems, London, UK). This electronic record serves as the primary medical records for the practice. Data recorded in THIN include demographics, details from general practitioners‟ visits such as medical diagnoses and prescriptions written by the general practitioners, diagnoses from specialist referrals and hospital admissions, some results of laboratory tests, some lifestyle characteristics and other measurements as taken in the practice. Within the database, diagnoses are recorded using READ codes. Prospective data collection for THIN began in September 2002, with electronic medical records that date back to 1985. In addition, practices may retrospectively enter significant medical events into the electronic medical record. Currently, the database has 2.7 million active patients registered. Recently a validation study was conducted by Lewis et al which concluded that “THIN data that are collected outside of the General Practice Research Database (GPRD) appear as valid as the data collected as part of the GPRD”.”12

The BIFAP database is a longitudinal observational population based database kept by the Spanish agency for medicines and medical devices that collates, from 2001 onwards, the computerized medical records of 2080 primary care physicians (1727 general practitioners (GPs) and 353 pediatricians) throughout Spain (Salvador-Rosa A, 2002). Access to health care in Spain is free. Primary care physicians play a key role in the Spanish health care system as they act as the gatekeepers of healthcare and are responsible for primary healthcare and specialist referral. The primary care of children in Spain is entrusted to primary care pediatricians until the age of 14 years old. After that age, primary care GPs are responsible of population health care.

The research database (2008) includes anonymized information on more than 3.180.161 patients totalling 11,526.564 person-years of follow-up. Data recorded in BIFAP include demographic information, prescription details, clinical events, specialist referrals and laboratory test results. The International Classification of Primary Care (ICPC) is the coding system for patient complaints and diagnoses, although this information can also be entered as free text. Prescription data such as product name, quantity dispensed, dosage regimens, strength and indication are entered into the computer. Prescriptions are coded according to the Anatomical Therapeutic Chemical (ATC) classification scheme.

5. Study period The study period for the drug utilization study will comprise 11 years from January 1st 1995 (or the date the respective databases start if this is later) until December 31st, 2010.

6. Study population

The study population will comprise all children (aged 0-18 years) in the source population with at least 6 months of valid database history, or who are born during the study period. Newborns (born during study period) thus do not require a valid database history.

7. Follow-up period

The patients start contributing to the study at the latest of any of the following dates: - Eligibility date according to the database holder - At birth, if birth is during the study period - Start of study period The follow-up ends at the earliest of any of the following dates - End of study period: December 31st, 2010. - Transfer out of database / end of registration / end of membership / interruption of registration or membership / last data collection of the database. - 18th / 14th (Pedianet) birthday - Death.

8. Data collection

The following data need to be selected by the different database owners and incorporated into a common data input model. These will be the input variables and files needed for Jerboa, the software tool which was previously developed in EU-ADR (FP7-ICT-2007-215847) and which will be adapted to ARPEC requirements to extract, prepare and aggregate data from a common data input model and subsequently to calculate the proposed drug use parameters in a systematic and uniform approach.

For the source population the following data will need to be extracted as input files for Jerboa

- PatientID (same as in other files) - Eligibility date ((date of patient registration in the database and for which quality data is available) = (physician up to standard for medical record databases)) - Exit date: date patient ends his/her follow-up (transfer out of database; end of registration; end of membership; interruption of registration or membership; Death; 18th / 14th (Pedianet) birthday; or last data collection date of the database) - Date of birth - Gender

The following information on anti-infective agents use will be retrieved from the databases (for the full list see Annex drug list source file) Required fields for anti-infective agents use for which an exactly calculated duration is required (for details see Jerboa instruction):

PatientID Patient ID. ATC Anatomic Therapeutic Chemical classification system (7 characters) Date Date of prescription Formulation Formulation Strength Indicate the strength (amount of active substance) per single entity of the formulation (in milligram). TotUnit Total number of single entities of the formulation: tablets, liquids (ml), capsules, suppositories, number of injections. UnitDay Number of prescribed units (tablets, liquids (ml), capsues, suppositories, injections) per day. DDDtot Total number of DDDs of the prescription duration Prescribed duration of the prescription as regularly assessed by database.

Data on drugs should cover the period from eligibility (patient registered and database up to quality/standard) and thus includes also all drugs during the 6 months run in period Several diseases (indication of use of anti-infective agents, common childhood infections and underlying comorbidity of asthma) will be studied as characteristics and need to be extracted locally and prepared for the common input model:

The datafile that needs to be prepared for each of these conditions comprises the following variables (regular jerboa event input file that has been used for rate estimations):

PatientID PatientID Date Date of diagnosis of the disease ( Eventtype Type of disease (for names see Jerboa names as specified in the Jerboa disease extraction instructions for the observational studies) Code Disease code of event

Data on diseases should cover the period from eligibility (patient registered and database up to quality/standard) and thus includes all events during the 6 months run in period, plus recurrent events.

Outcome measures

Population level

1-Monthly prevalence of use, overall and by type of antibiotic, will be measured as the number of individuals receiving at least one antibiotic prescription in that month, divided by the number of person months of all individuals alive and registered in the database in that month.

Table 2.1.1: Prevalence of antibiotic use parameters Measure Unit of Unit Numerator Denominator Output Jerboa time Prevalence Calendar Number/ Number of Total number Prevalence of use of specific month 1,000 individuals having of person per anti-infective anti-infective persons at least one day months in that agent (ATC 7) by agent use months of exposure to a month calendar month specific anti- and calendar year infective agent stratified by during specific country, age and month gender Prevalence Calendar Number/ Number of Total number Prevalence of use of use of month 1,000 individuals having of person per class of anti- anti-infective persons at least one day months in that infective agent agent (class months of exposure to a month (ATC 5 level) by level) specific class of calendar month an anti-infective and calendar year agent during stratified by specific month country, age and gender Prevalence Calendar Number/ Number of Total number Prevalence of use

of type of month 1,000 individuals having of person per anti-infective anti-infective persons at least one day months in that agent (ATC 3 agent use months of exposure to month level) by calendar (ATC-3 any type of an month and level) anti-infective calendar year (antibiotics, agent during stratified by antivirals or specific month country, age and antimycotics gender )

The output files of Jerboa that will be shared will comprise the numerator, denominator and outcome measures by different ATC levels, age, gender and calendar month/year.

The volume of anti-infective agent use will be expressed by the number of Rx and the person- time exposed.

Table 2.1.2 Volume of anti-infective agent use

Measure Unit of Unit Numerator Denominator Output Jerboa time Volume of Calendar Number/ Number of Rx Total number Sum of Rx per anti-infective month 1,000 of person specific type of agents person months anti-infective months agents (ATC 7 level) by calendar month and calendar year stratified by country, age and gender Volume of Calendar Person Person time of Total number Sum of person anti-infective month months/ exposure of person days of exposure agents 1,000 months per anti-infective person agent (ATC 7) by months calendar year stratified by country, age and gender

The Jerboa output file that will be sent to will comprise the numerator, denominator and outcome measures by ATC code and calendar month/year and age, gender.

Person level use analyses

For each individual patient we will calculate several parameters to estimate duration and volume of use as well as switching over the study period. These parameters allow for the analysis of the pattern of use of antibiotics.

Volume of use per user.

The following parameters for duration of use will be calculated per patient from the date of first prescription of an anti-infective agent. Information on calculation of the duration based on DDD is given in Annex X of the Jerboa instructions.

Table 2.2.2 Parameters to estimate duration of antibiotic use per patient

Measure Unit Output Jerboa Volume of use of Sum Rx the sum of Rx of anti-infective agents after anti-infective agents study start Volume of use of Rx in first year after the sum of Rx of anti-infective agents in 1st year anti-infective agents first prescription after first prescription in the first year following the first prescription Cumulative Duration Sum Person days the duration of exposure to all anti-infective of anti-infective exposure agents after study start (independent of agent use overlap) Duration of anti- Sum Person days the duration of exposure to all anti-infective infective agents in exposure in first agents in 1st year after first prescription first year year (independent of overlap) The categories of duration of use will be based on the results from the analysis above, together with the knowledge on clinically relevant periods of duration of use. The Jerboa output file will be at the level of an individual patient and comprise the following variables: ATC code (level 7) for index anti-infective agent, year of first prescription, age at first prescription, gender, days of follow-up after first prescription, sum anti-infective agents Rx after entry, sum Rx in the 1st year following the first prescription, sum exposure days total, sum exposure days first year, number of different anti-infective agents in follow-up, number of different anti-infective agents in first year. These data will be produced locally and sent to the Datawarehouse.

Disease level

Anti-infective prescriptions for common infectious diseases in childhood are going to be analysed.

Incidence of common childhood infections from the different databases will be analyzed. The following infections will be taken into account:

To study antibiotic use:  Respiratory tract infections

i. Upper respiratory tract infections 1. Otitis Media 2. Tonsillitis + pharyngitis 3. Sinusitis ii. Lower respiratory tract infections 1. Bronchitis+ bronchiolitis 2. Pneumonia  Bacterial skin infections i. Impetigo and abscesses  Urinary tract infections  Gastro-enteritis  Fever To study systemic anti-viral use:  Chicken pox infections (varicella)  Herpes stomatitis  Influenza o To study systemic anti-mycotic use:  Oral candidiasis

For these diseases mapping of disease codes is necessary, as databases use different disease codes. The mapping to UMLS coding will be done as part of the study.

Prevalence of use during the study period will be analysed and stratified by country, age groups, gender, type of anti-infective (class and ATC7-level) formulation, and calendar time (year or month) for the common childhood infections as defined above.

Prescription level analyses

The following characteristics of anti infective use will be assessed for each prescription (at ATC 7 level). Table 2.4.1 also reflects the variables in the output file of Jerboa.

Table 2.4.1 Characteristics to be assessed for each antibiotic prescription at date of the prescription Characteristics Definition/timing ATC ATC code of the prescription Duration Duration of prescription Strength Strength of a unit (see input files) Formulation Formulation of prescription (see input files) Patient file Age At date of anti-infective Rx Gender Male /Female Year Calendar year at date of anti-infective Rx Month Calendar month at date of anti-infective Rx From Event FILE History of asthma History of asthma

Common childhood +/- 7 days of date of anti-infective prescription infections (see 1.1.12)

From Prescriptions file Prescription sequence Since first anti-infective prescription in the study period number Previous use of anti- ATC code of the last anti-infective agent in the year before infective agent Time since last anti- Days since end of last prescription infective agent Anti-infective agent Number of any anti-infective agent in the year before number

Analyses of antibiotic use

All data elaboration will be done locally at the centres by Jerboa scripts, the query output (de- identified) can be used locally and will be shared centrally in the DWH for further (pooled) analyses.

Anti-infective use will be described on a population, person, disease and prescription level and compared between databases and countries.

Characteristics of anti-infective users will be described and compared between individual anti- infective agents by database, age, gender and by country. An important aspect of the drug utilization will be to describe volume and duration of use and channelling in different countries by product and to see whether channelling has changed over calendar time.

Chi-square test for categorical variables and Student‟s t-test for continuous variables, with a significance level of p<0.05, will be used for assessing the differences among use of various anti-infective agents compared to a reference exposure (to be defined).

Timelines

Event Date Final protocol October 2011 Testing the protocol in Dutch data November 2011 Preparation input tables local databases December 2011 Jerboa run no. 1 January 2012 Start analysis run no. 1 February 2012 UMLS mapping March 2012 Jerboa run no. 2 April 2012 Start analysis run no. 2 April 2012 Report September 2012

Appendix 1: Study drugs

ATC Antibacterials for systemic use DDD Unit Route DDD2 Unit2 Route2 J01 J01A Tetracyclines J01AA Tetracyclines J01AA01 demeclocycline 0.6 g O J01AA02 doxycycline 0.1 g O / P J01AA03 chlortetracycline 1 g O J01AA04 lymecycline 0.6 g P J01AA05 metacycline 0.6 g O J01AA06 oxytetracycline 1 g O / P J01AA07 tetracycline 1 g O / P J01AA08 minocycline 0.2 g O / P J01AA09 rolitetracycline 0.35 g P J01AA10 penimepicycline J01AA11 clomocycline 1 g O J01AA12 tigecycline 0.1 g P J01AA20 combinations of tetracyclines J01AA56 oxytetracycline, combinations J01B Amphenicols J01BA Amphenicols J01BA01 chloramphenicol 3 g O / P J01BA02 thiamphenicol 1.5 g O / P J01BA52 thiamphenicol, combinations J01C Beta-lactam antibacterials, penicillins J01CA Penicillins with extended spectrum J01CA01 ampicillin 2 g O / P / R J01CA02 pivampicillin 1.05 g O J01CA03 carbenicillin 12 g P J01CA04 amoxicillin 1 g O / P J01CA05 carindacillin 4 g O J01CA06 bacampicillin 1.2 g O J01CA07 epicillin 2 g O / P J01CA08 pivmecillinam 0.6 g O J01CA09 azlocillin 12 g P J01CA10 mezlocillin 6 g P J01CA11 mecillinam 1.2 g P J01CA12 piperacillin 14 g P J01CA13 ticarcillin 15 g P J01CA14 metampicillin 1.5 g O / P J01CA15 talampicillin 2 g O J01CA16 sulbenicillin 15 g P J01CA17 temocillin 2 g P

J01CA18 hetacillin 2 g O J01CA20 combinations J01CA51 ampicillin, combinations J01CA51 ampicillin, combinations J01CE Beta-lactamase sensitive penicillins J01CE01 benzylpenicillin 3.6 g P J01CE02 phenoxymethylpenicillin 2 g O J01CE03 propicillin 0.9 g O J01CE04 azidocillin 1.5 g O J01CE05 pheneticillin 1 g O J01CE06 penamecillin 1.05 g O J01CE07 clometocillin 1 g O J01CE08 benzathine benzylpenicillin 3.6 g P J01CE09 procaine benzylpenicillin 0.6 g P J01CE10 benzathine phenoxymethylpenicillin 2 g O J01CE30 combinations J01CF Beta-lactamase resistant penicllins J01CF01 dicloxacillin 2 g O / P J01CF02 cloxacillin 2 g O / P J01CF03 meticillin 4 g P J01CF04 oxacillin 2 g O / P J01CF05 flucloxacillin 2 g O / P J01CG Beta-lactamase inhibitors J01CG01 sulbactam 1 g P J01CG02 tazobactam J01CR Combinations of penicillins, incl beta lactamase inhibitors J01CR01 ampicillin and enzyme inhibitor 2 g P J01CR02 amoxicillin and enzyme inhibitor 1 g O 3 g P J01CR03 ticarcillin and enzyme inhibitor 15 g P J01CR04 sultamicillin 1.5 g O J01CR05 piperacillin and enzyme inhibitor 14 g P J01CR50 combinations of penicillins J01D Other beta-lactam antibacterials J01DB First-generation cephalosporins J01DB01 cefalexin 2 g O J01DB02 cefaloridine 3 g P J01DB03 cefalotin 4 g P J01DB04 cefazolin 3 g P J01DB05 cefadroxil 2 g O J01DB06 cefazedone 3 g P J01DB07 cefatrizine 1 g O J01DB08 cefapirin 4 g P J01DB09 cefradine 2 g O / P J01DB10 cefacetrile J01DB11 cefroxadine J01DB12 ceftezole 3 g P

J01DC Second-generation cephalosporins J01DC01 cefoxitin 6 g P J01DC02 cefuroxime 0.5 g O 3 g P J01DC03 cefamandole 6 g P J01DC04 cefaclor 1 g O J01DC05 cefotetan 4 g P J01DC06 cefonicid 1 g P J01DC07 cefotiam 4 g P 1.2 g O J01DC08 loracarbef 0.6 g O J01DC09 cefmetazole 4 g P * J01DC10 cefprozil 1 g O J01DC11 ceforanide 4 g P J01DD Third-generation cephalosporins J01DD01 cefotaxime 4 g P J01DD02 ceftazidime 4 g P J01DD03 cefsulodin 4 g P J01DD04 ceftriaxone 2 g P J01DD05 cefmenoxime 2 g P J01DD06 latamoxef 4 g P J01DD07 ceftizoxime 4 g P J01DD08 cefixime 0.4 g O J01DD09 cefodizime 2 g P J01DD10 cefetamet 1 g O J01DD11 cefpiramide 2 g P J01DD12 cefoperazone 4 g P J01DD13 cefpodoxime 0.4 g O J01DD14 ceftibuten 0.4 g O J01DD15 cefdinir 0.6 g O J01DD16 cefditoren 0.4 g O J01DD17 cefcapene 0.45 g O J01DD54 ceftriaxone, combinations J01DD62 cefoperazone, combinations 4 g P J01DE Fourth-generation cephalosporins J01DE01 cefepime 2 g P J01DE02 cefpirome 4 g P J01DE03 cefozopran 4 g P J01DF Monobactams J01DF01 aztreonam 4 g P J01DH Carbapenems J01DH02 meropenem 2 g P J01DH03 ertapenem 1 g P J01DH04 doripenem 1.5 g P J01DH05 biapenem 1.2 g P J01DH51 imipenem and enzyme inhibitor 2 g P J01DH55 panipenem and betamipron 2 g P J01DI Other cephalosporins

J01DI01 ceftobiprole medocaril 1.5 g P J01DI02 ceftaroline fosamil J01E Sulfonamides and trimethoprim J01EA Trimethoprim and derivatives J01EA01 trimethoprim 0.4 g O / P J01EA02 brodimoprim 0.2 g O J01EA03 iclaprim J01EB Short-acting sulfonamides J01EB01 sulfaisodimidine 4 g O / P J01EB02 sulfamethizole 4 g O J01EB03 sulfadimidine 4 g O J01EB04 sulfapyridine 1 g O J01EB05 sulfafurazole 4 g O / P J01EB06 sulfanilamide J01EB07 sulfathiazole J01EB08 sulfathiourea 6 g O J01EB20 combinations J01EC Intermediate-acting sulfonamides J01EC01 sulfamethoxazole 2 g O J01EC02 sulfadiazine 0.6 g O J01EC03 sulfamoxole 1 g O / P J01EC20 combinations J01ED Long-acting sulfonamides J01ED01 sulfadimethoxine 0.5 g O J01ED02 sulfalene 0.1 g O J01ED03 sulfametomidine J01ED04 sulfametoxydiazine 0.5 g O J01ED05 sulfamethoxypyridazine 0.5 g O J01ED06 sulfaperin 0.5 g O J01ED07 sulfamerazine 3 g O J01ED08 sulfaphenazole 1 g O J01ED09 sulfamazone 1.5 g O / R J01ED20 combinations J01EE Combinations of sulfonamides and trimethoprim, incl. Derivatives J01EE01 sulfamethoxazole and trimethoprim J01EE02 sulfadiazine and trimethoprim J01EE03 sulfametrole and trimethoprim J01EE04 sulfamoxole and trimethoprim J01EE05 sulfadimidine and trimethoprim J01EE06 sulfadiazine and tetroxoprim J01EE07 sulfamerazine and trimethoprim J01F Macrolides, lincosamides and streptogramins J01FA Macrolides J01FA01 erythromycin 1 g O / P 2 g O J01FA02 spiramycin 3 g O J01FA03 midecamycin 1 g P

J01FA05 oleandomycin 1 g O J01FA06 roxithromycin 0.3 g O J01FA07 josamycin 2 g O J01FA08 troleandomycin 1 g O J01FA09 clarithromycin 1 g P J01FA10 azithromycin 0.5 g P 0.3 g O J01FA11 miocamycin 1.2 g O J01FA12 rokitamycin 0.8 g O J01FA13 dirithromycin 0.5 g O J01FA14 flurithromycin 0.75 g O J01FA15 telithromycin 0.8 g O J01FF Lincosamides J01FF01 clindamycin 1.2 g O 1.8 g P J01FF02 lincomycin 1.8 g O / P J01FG Streptogramins J01FG01 pristinamycin 2 g O J01FG02 quinupristin/dalfopristin 1.5 g P J01G Aminoglycoside antibacterials J01GA Streptomycins J01GA01 streptomycin 1 g P J01GA02 streptoduocin 1 g P J01GB Other aminoglycosides J01GB01 tobramycin 0.3 g Inhal.sol 0.24 g P J01GB03 gentamicin 0.24 g P J01GB04 kanamycin 1 g P J01GB05 neomycin 1 g O J01GB06 amikacin 1 g P J01GB07 netilmicin 0.35 g O / P J01GB08 sisomicin 0.24 g P J01GB09 dibekacin 0.14 g P J01GB10 ribostamycin J01GB11 isepamicin J01GB12 arbekacin 0.2 g P J01M Quinolone antibacterials J01MA Fluoroquinolones J01MA01 ofloxacin 0.4 g O / P J01MA02 ciprofloxacin 1 g O 0.5 g P J01MA03 pefloxacin 0.8 g O / P J01MA04 enoxacin 0.8 g O J01MA05 temafloxacin 0.8 g O J01MA06 norfloxacin 0.8 g O J01MA07 lomefloxacin J01MA08 fleroxacin 0.4 g O / P J01MA09 sparfloxacin 0.2 g O J01MA10 rufloxacin 0.2 g O J01MA11 grepafloxacin 0.4 g O

J01MA12 levofloxacin 0.5 g O / P J01MA13 trovafloxacin 0.2 g O / P J01MA14 moxifloxacin 0.4 g O / P J01MA15 gemifloxacin J01MA16 gatifloxacin 0.4 g O / P J01MA17 prulifloxacin 0.6 g O * J01MA18 pazufloxacin 1 g P J01MA19 garenoxacin J01MA21 sitafloxacin 0.1 g O J01MB Other quinolones J01MB01 rosoxacin 0.3 g O J01MB02 nalidixic acid 4 g O J01MB03 piromidic acid 2 g O J01MB04 pipemidic acid 0.8 g O J01MB05 oxolinic acid 1 g O J01MB06 cinoxacin 1 g O J01MB07 flumequine 1.2 g J01R Combinations of antibacterials J01RA Combinations of antibacterials J01RA01 penicillins, combinations with other antibacterials J01RA02 sulfonamides, combinations with other antibacterials (excl. trimethoprim) J01RA03 cefuroxime, combinations with other antibacterials J01RA04 spiramycin, combinations with other antibacterials J01X Other antibacterials J01XA Glycopeptide antibacterials J01XA01 vancomycin 2 g P J01XA02 teicoplanin 0.4 g P J01XA03 telavancin J01XA04 dalbavancin J01XA05 oritavancin J01XB Polymyxins J01XB01 colistin 3 MU P / Inhal J01XB02 polymyxin B 0.15 g P J01XC Steroid antibacterials J01XC01 fusidic acid 1.5 g O / P J01XD Imidazole derivatives J01XD01 metronidazole 1.5 g P J01XD02 tinidazole 1.5 g P J01XD03 ornidazole 1 g P J01XE Nitrofuran derivatives J01XE01 nitrofurantoin 0.2 g O J01XE02 nifurtoinol 0.16 g O J01XX Other antibacterials J01XX01 fosfomycin 3 g O 8 g P J01XX02 xibornol J01XX03 clofoctol 1.5 g R

J01XX04 spectinomycin 3 g P J01XX05 methenamine 3 g O 2 g O J01XX06 mandelic acid 12 g O J01XX07 nitroxoline 1 g O J01XX08 linezolid 1.2 g O / P J01XX09 daptomycin 0.28 g P

ATC Antimycotics for systemic use DDD Unit Route J02 J02A Antimycotics for systemic use J02AA Antibiotics J02AA01 amphotericin B 35 mg P J02AA02 hachimycin J02AB Imidazole derivatives J02AB01 miconazole 1 g P J02AB02 ketoconazole 0.2 g O J02AC Triazole derivatives J02AC01 fluconazole 0.2 g O / P J02AC02 itraconazole 0.2 g O / P J02AC03 voriconazole 0.4 g O / P J02AC04 posaconazole 0.8 g O J02AX Other antimycotics for systemic use J02AX01 flucytosine 10 g O / P J02AX04 caspofungin 50 mg P J02AX05 micafungin 0.1 g P J02AX06 anidulafungin 0.1 g P

ATC Antimycobacterials DDD Unit Route J04 J04A Drugs for treatment of tuberculosis J04AA Aminosalicylic acid and derivatives J04AA01 aminosalicylic acid 12 g O J04AA02 sodium aminosalicylate 14 g O / P J04AA03 calcium aminosalicylate J04AB Antibiotics J04AB01 cycloserine 0.75 g O J04AB02 rifampicin 0.6 g O / P J04AB03 rifamycin 0.6 g P J04AB04 rifabutin 0.15 g O J04AB05 rifapentine J04AB30 capreomycin 1 g P J04AC Hydrazides J04AC01 isoniazid 0.3 g O / P J04AC51 isoniazid, combinations J04AD Thiocarbamide derivatives J04AD01 protionamide 0.75 g O J04AD02 tiocarlide 7 g O J04AD03 ethionamide 0.75 g O J04AK Other drugs for treatment of tuberculosis J04AK01 pyrazinamide 1.5 g O J04AK02 ethambutol 1.2 g O / P J04AK03 terizidone J04AK04 morinamide J04AM Combinations of drugs for treatment of tuberculosis J04AM01 streptomycin and isoniazid J04AM02 rifampicin and isoniazid J04AM03 ethambutol and isoniazid J04AM04 thioacetazone and isoniazid J04AM05 rifampicin, pyrazinamide and isoniazid J04AM06 rifampicin, pyrazinamide, ethambutol and isoniazid J04B Drugs for treatment of lepra J04BA Drugs for treatment of lepra J04BA01 clofazimine 0.1 g O J04BA02 dapsone 50 mg O J04BA03 aldesulfone sodium 0.33 g O

ATC Antivirals for systemic use DDD Unit Route DDD2 Unit2 Route2 J05 J05A Direct acting antivirals J05AA Thiosemicarbazones J05AA01 metisazone J05AB Nucleosides and nucleotides excl. reverse transcriptase inhibitors J05AB01 aciclovir 4 g O / P J05AB02 idoxuridine J05AB03 vidarabine J05AB04 ribavirin 6 g Inhal.solution 1 g O J05AB06 ganciclovir 0.5 g P 3 g O J05AB09 famciclovir 0.75 g O J05AB11 valaciclovir 3 g O J05AB12 cidofovir 25 mg P J05AB13 penciclovir J05AB14 valganciclovir 0.9 g O J05AB15 brivudine 0.125 g O J05AC Cyclic amines J05AC02 rimantadine J05AC03 tromantadine J05AD Phosphonic acid derivatives J05AD01 foscarnet 6.5 g P J05AD02 fosfonet J05AE Protease inhibitors J05AE01 saquinavir 1.8 g O J05AE02 indinavir 2.4 g O J05AE03 ritonavir 1.2 g O J05AE04 nelfinavir 2.25 g O J05AE05 amprenavir 1.2 g O J05AE06 lopinavir 0.8 g O J05AE07 fosamprenavir 1.4 g O J05AE08 atazanavir 0.3 g O J05AE09 tipranavir 1 g O J05AE10 darunavir 1.2 g O J05AF Nucleoside and nucleotide reverse transcriptase inhibitors J05AF01 zidovudine 0.6 g O / P J05AF02 didanosine 0.4 g O J05AF03 zalcitabine 2.25 mg O J05AF04 stavudine 80 mg O J05AF05 lamivudine 0.3 g O J05AF06 abacavir 0.6 g O J05AF07 tenofovir disoproxil 0.245 g O J05AF08 adefovir dipivoxil 10 mg O J05AF09 emtricitabine 0.2 g O J05AF10 entecavir 0.5 mg O J05AF11 telbivudine 0.6 g O * J05AF12 clevudine 30 mg O

J05AG Non-nucleoside reverse transcriptase inhibitors J05AG01 nevirapine 0.4 g O J05AG02 delavirdine J05AG03 efavirenz 0.6 g O J05AG04 etravirine 0.4 g O J05AH Neuraminidase inhibitors J05AH01 zanamivir 20 mg Inhal.powder J05AH02 oseltamivir 0.15 g O J05AR Antivirals for treatment of HIV infections, combinations J05AR01 zidovudine and lamivudine J05AR02 lamivudine and abacavir J05AR03 tenofovir disoproxil and emtricitabine J05AR04 zidovudine, lamivudine and abacavir J05AR05 zidovudine, lamivudine and nevirapine J05AR06 emtricitabine, tenofovir disoproxil and efavirenz J05AR07 stavudine, lamivudine and nevirapine J05AX Other antivirals J05AX01 moroxydine 0.3 g O J05AX02 lysozyme J05AX05 inosine pranobex J05AX06 pleconaril J05AX07 enfuvirtide 0.18 g P J05AX08 raltegravir 0.8 g O * J05AX09 maraviroc 0.6 g O * J05AX10 maribavir

ATC Antibiotics and chemotherapeutics for dermatological use DDD Unit Route D06 D06A Antibiotics for topical use D06AA Tetracycline and derivatives D06AA01 demeclocycline D06AA02 chlortetracycline D06AA03 oxytetracycline D06AA04 tetracycline D06AX Other antibiotics for topical use D06AX01 fusidic acid D06AX02 chloramphenicol D06AX04 neomycin D06AX05 bacitracin D06AX07 gentamicin D06AX08 tyrothricin D06AX09 mupirocin D06AX10 virginiamycin D06AX11 rifaximin D06AX12 amikacin D06AX13 retapamulin D06B Chemotherapeutics for topical use D06BA Sulfonamides D06BA01 silver sulfadiazine D06BA02 sulfathiazole D06BA03 mafenide D06BA04 sulfamethizole D06BA05 sulfanilamide D06BA06 sulfamerazine D06BA51 silver sulfadiazine, combinations D06BB Antivirals D06BB01 idoxuridine D06BB02 tromantadine D06BB03 aciclovir D06BB04 podophyllotoxin D06BB05 inosine D06BB06 penciclovir D06BB07 lysozyme D06BB08 ibacitabine D06BB09 edoxudine D06BB10 imiquimod D06BB11 docosanol D06BB53 aciclovir, combinations D06BX Other chemotherapeutics D06BX01 metronidazole D06C Antbiotics and chemotherapeutics, combinations