SUMMARY
Introduction
As a result of a global reassessment of the Italian National formulary, the Italian Ministry of Health excluded all antihistamines from reimbursement between January 2003 and March 2004. The only exception was patients with moderate or severe chronic allergic rhinitis and urticaria (Nota 89B2). At present no data is available to describe the impact of the exclusion of a full class of drugs for a limited time period on the use of such drugs, clinical outcomes and implications on resource utilisation. Schering Plough US requested a proposal with this objective, which is hereby addressed
Proposal
This study aims to evaluate the impact of the exclusion (January 2003 - March 2004) of all antihistamines from reimbursement in children (0-14 years) with respiratory allergic disease in terms of clinical outcomes and resource use (including prescriptions, hospitalisations, emergency room visits, lab test etc).
Methods
Study design
Retrospective cohort study
Sample population
The sample population for this study (PEDIANET July 2005) comprised 180,096 children aged 0-14 years who were registered for at least one year (or were newborns) with one of the 109 registered paediatricians during the period 2002-2005
Cohorts
In this sample population we identified children who had asthma or wheezing and/or allergic rhinitis. The underlying sample population is dynamic as children may transfer in and out, analysis was carried out using a dynamic approach and a fixed cohort approach.
Asthma
For the dynamic approach children were considered to be asthmatic if they had a diagnosis of asthma and had at least two prescriptions for asthma drugs within one year. If one of these criteria was fulfilled the subsequent person time of that child was considered to asthmatic person time, in total 28,447 children contributed person time to the asthma cohort.
To be eligible for the fixed cohort approach children needed to have an asthma diagnosis prior to the start of the study (01/01/2002) or treatment with at least two asthma drugs occurring before the start of the study, 13,874 children were included in the fixed asthma cohort.
Allergic rhinitis
For the dynamic approach children were considered to be suffering from allergic rhinitis if they had a diagnosis of allergic rhinitis or had one or more prescriptions for nasal steroids. If one of these criteria was fulfilled the subsequent person time of that child was considered to be allergic rhinitis person time, 22,529 children contributed person time to the allergic rhinitis cohort.
To be eligible for the fixed allergic rhinitis cohort approach children needed to have a diagnosis of allergic rhinitis prior to the start of the study (01/01/2002) or treatment with nasal steroids or antihistamines before the start of the study, 20,410 children contributed to the fixed cohort.
Children contributed person time to the asthma+AR cohort if both conditions were fulfilled: 10,481 children contributed person time to this group. Children were in the fixed asthma+AR cohort if they had both conditions prior to the start of the study period, 6871 children fulfilled these conditions.
Statistical analysis
To assess whether rates for hospitalizations, emergency visits and other resource use changed between the before, during and after policy periods, the following analysis was conducted
1. Descriptive:
Rates were calculated per month and aggregated for 2002 (before), January 2003- March 2004 (during) and for April 2004-March 2005. Tables with monthly counts, rates and aggregated rates plus confidence intervals are provided. For each item a graph was produced.
2. Analytic:
Crude incidence rate ratios were calculated and multivariate Poisson regression was used for estimation of adjusted rate ratios. Two comparisons were made, the rate in the period during the policy was compared with before and the rate after the policy control was compared with the rate before. For comparison of rates with a frequent outcome we adjusted for all potential confounders: age, gender, monthly (average of weeks) counts for pollen, socio-economic status (gross income for an area), number of other visits, epilepsy, diabetes, sinusitis, otitis, pneumonia, influenza, varicella, hospitalization for asthma (year prior), number or oral corticosteroid prescriptions in year prior, number of SABA prescriptions in year prior. For pollen we obtained the absolute counts per week, year and region from the following site: www.pollinieallergia.net. Since the counts were inferred from graphs they may not be exact. To calculate monthly counts we calculated the average over the weeks.
Socio-economic status was classified by the mean income rate per household in the area of the physician. Low socio-economic status was income < 25.000 Euro’s (25th percent), medium socio-economic status 25-30,000 Euros and high socioeconomic status > 30,000 Euro’s per household (75th percent).
Hospitalizations and emergency room visits were rare and the full model did not converge. These rates were compared while adjusting for age, gender, socio-economic status (gross income for an area), hospitalization for asthma (year prior), number or oral corticosteroid prescriptions in year prior, number of SABA prescriptions in prior year. Only crude rate ratios could be calculated in some analysis.
For all Poisson and other rate analysis the unit of analysis was a month, this means that the confounder status was assessed per month and therefore was time-varying.
Results
About 25,000 children with Allergic Rhinitis and asthma were included in the data analysis. Of these 5900 were prior to the study period, 8600 during the study period (Jan 2003-March 2004) and 9700 after this period. A total of more than 3.000.000 person/days of follow up were considered.
No significant difference was found in the hospitalisation rates and consumption of resources between the different periods.
PARTECIPANTS AND COLLABORATIONS
Coordinators
Miriam CJM Sturkenboom
Department of Epidemiology and Biostatistics and medical informatics, Erasmus University Medical Centre, Rotterdam
Carlo Giaquinto
Dipartimento di Pediatria, Padova
Luigi Cantarutti
Coordinamento Pedianet, PLS, Padova
Gino Picelli
International Pharmacoepidemiology and pharmacoeconomics Research Centre, Italy
David Battleman
Valuemedics Reserach, Arlington, VA, USA
Jonatan Tierce
Valuemedics Reserach, Arlington, VA, USA
Patrizia Berto
PBE consulting, Verona
Walter Giorgio Canonica
Clinica di Malattie dell'Apparato Respiratorio e Allergologia DIMI - Dipartimento di Medicina Interna Università degli Studi Genova
Partecipants
ABRUZZO
Bonfigli Emanuela, Collacciani Giuseppe, Ferretti Michele, Forcina Paolo.
CAMPANIA
Basile Paola, Bratto Massimo, Castaldo Annunziata, Conte Ugo Alfredo, Costanzo Nicola, Di Santo Giuseppe, Falco Pietro, Ferraiuolo Maurizio, Mariniello, Petrazzuoli Giovanni, Speranza Francesco, Sticco Maura, Tambaro Paolo.
EMILIA ROMAGNA
Alberti Arturo, Barone Roberto, Biondi Claudio, Casalboni Rita, Faedi Clara Maria, Hamameh Marwan, Lucchi Elide, Mazzini Franco, Ponti Roberto, Trebbi Miro, Varni Pierfiorenzo.
FRIULI VENEZIA GIULIA
De Clara Roberto, Lorusso Giuseppe, Masotti Sergio, Muzzolini Carmen, Nicolosio Flavia, Ulliana Antonella.
LOMBARDIA
Battilana Maria Pia, Clerici Schoeller Mariangela, Curto Salvatore, Elio Giuseppe, Frattini Claudio, Lietti Giuseppe, Mauri Laura, Picco Patrizia, Pirola Ambrogina, Ragazzon Ferdinando, Rosignoli Rino, Russo Annarita, Terenghi Albino, Tusa Antonino, Vannini Paola, Vertua Guido.
MARCHE
Bollettini Stefano, Budassi Roberto, Dolci Marco, Galvagno Andrea, Gentili Alberta, Gentilucci Pierfrancesco, Gobbi Costantino, Grelloni Mauro, Olimpi Laura, Senesi Paolo, Tonelli Gabriele.
PIEMONTE
Mirabelli Maria Cristina, Sciolla Nico Maria, Valpreda Andrea.
SARDEGNA
Basoccu Pietro, Cera Giuseppe Egidio, Cuboni Giancarlo, Lazzari Maura, Mulas Anna, Rosas Paolo.
SICILIA
Alongi Angelo, Avarello Giovanni, Barberi Frandanisa Maria, Petrotto Giuseppe, Puma Antonino, Salamone Pietro, Speciale Sergio, Volpe Concetta.
TOSCANA
Storelli Francesco
VENETO
Barbieri Patrizia, Bucolo Carmelo, Cantarutti Luigi, Cozzani Sandra, D’Amanti Vito Francesco, De Marchi Annamaria, Doria Mattia, Drago Stefano, Ferrara Enrico, Fusco Fabrizio, Giancola Giuseppe, Girotto Silvia, Grillone Giuseppe, Katende Charles Mulopo, Lista Cinzia, Macropodio Nadia, Milano Massimo, Pasinato Angela, Passarella Andrea, Ruffato Bruno, Sambugaro Daniela, Saretta Luigi, Schievano Paolo, Semenzato Flavio, Spanevello Walter, Tamassia Gianni, Toffol Giacomo.
Collaborations
Data Monitor
Antonio Scamarcia
Società Servizi Telematici, Padova
Computer-related Assistance
Alessandro Zandarin
Società Servizi Telematici, Padova
FINANCING
The study was partially funded by Schering, US