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Andrea Spini,1 Luca L’Abbate,2 Ylenia Ingrasciotta,1 Giorgia Pellegrini,1 Massimo Carollo,1 Valentina Ientile,2 Olivia Leoni,3 Martina Zanforlini,4 Domenica Ancona,5 Paolo Stella,5 Anna Cavazzana,6 Angela Scapin,6 Sara Lopes,7 Valeria Belleudi,7 Gianluca Trifirò1 1Department of Diagnostics and Public Health, University of Verona, Verona, Italy; 2Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy; 3Lombardy Regional Centre of Pharmacovigilance and Regional Epidemiologic Observatory, Milan, Italy; 4Azienda Regionale per l’Innovazione e gli Acquisti, S.p.A, Milan, Italy; 5Apulian Regional Health Department, Bari, Italy; 6Azienda Zero, Regione Veneto, Italy; 7Department of Epidemiology, Lazio Regional Health Service, Rome, ItalyCorrespondence: Gianluca Trifirò, Department of Diagnostics and Public Health, University of Verona, P. le L.A. Scuro 10, Verona, 37134, Italy, Tel +39 045 802 7679, Email gianluca.trifiro@univr.itPurpose: This research aimed to develop and validate a META-algorithm combining individual immune-mediated inflammatory disease (IMID)-specific algorithms to identify the exact IMID indications for incident biological drug users from claims data within the context of the Italian VALORE project.Methods and Patients: All subjects with at least one dispensing of TNF-alpha inhibitors, anti-interleukin agents, and selective immunosuppressants approved for IMIDs were identified from claims databases of Latium region in Italy (observation period: 2010– 2020). Validated coding algorithms for identifying individual IMIDs from claims databases were found from published literature and combined into a META-algorithm. Positive predictive value (PPV), sensitivity (Se), negative predictive value (NPV), specificity (Sp), and accuracy (Acc) were estimated for each indication against the electronic therapeutic plans (ETPs) of the Latium region as the reference standard. Lastly, the frequency of the indication of use across individual biologic drugs was compared with that reported in three other Italian regions (Lombardy, Apulia, and the Veneto region).Results: In total, 9755 incident biological drug users with a single IMID indication were identified. Using the newly developed META-algorithm, an indication of use was detected in 95% (n=9255) of the total cohort. The estimated Acc, Se, Sp, PPV, and NPV, against the reference standard were as follows: 0.96, 0.86, 0.97, 0.82, and 0.98 for Crohn’s disease, 0.96, 0.80, 0.98, 0.85, and 0.97 for ulcerative colitis, 0.93, 0.76, 0.99, 0.95, and 0.92 for rheumatoid arthritis, 0.97, 0.75, 0.99, 0.85, and 0.98 for spondylarthritis, and 0.91, 0.92, 0.91, 0.88, and 0.94 for psoriatic arthritis/psoriasis, respectively. Additionally, no substantial difference was observed in the frequency of indication of use by active ingredient among Latium and the other three Italian regions included in the study.Conclusion: The newly developed META-algorithm demonstrated high validity estimates in the Italian claims data and was capable of discriminating with good performance among the most frequent IMID indications.Plain Language Summary: In the claims database, the lack of information on the indication of use represents a well-known limitation for the conduct of observational studies. This study was conducted to develop and validate a META-algorithm that accurately identifies the exact indication for the use of biological drugs in treating various immune-mediated inflammatory diseases. Using claims databases from the Latium region, we developed and validated a META-algorithm. The META-algorithm combines disease-specific algorithms for different immune-mediated inflammatory diseases (ie, Crohn’s disease, ulcerative colitis, rheumatoid arthritis, spondyloarthritis, psoriasis, and psoriatic arthritis) and was tested against a reference standard (electronic therapeutic plans of the Lazio region). The META-algorithm reported high validity estimates and was able to distinguish with a good performance among the most frequent IMIDs as indications for use. Applying this META-algorithm may facilitate post-marketing surveillance of biological drugs such as TNF-alpha inhibitors, anti-interleukin, and selective immunosuppressants in specific therapeutic areas in an Italian setting.Keywords: immune-mediated inflammatory diseases, biological drugs, validation, claims data, META-algorithm, indication for use

Andrea Spini,1 Luca L’Abbate,2 Ylenia Ingrasciotta,1 Giorgia Pellegrini,1 Massimo Carollo,1 Valentina Ientile,2 Olivia Leoni,3 Martina Zanforlini,4 Domenica Ancona,5 Paolo Stella,5 Anna Cavazzana,6 Angela Scapin,6 Sara Lopes,7 Valeria Belleudi,7 Gianluca Trifirò1 1Department of Diagnostics and Public Health, University of Verona, Verona, Italy; 2Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy; 3Lombardy Regional Centre of Pharmacovigilance and Regional Epidemiologic Observatory, Milan, Italy; 4Azienda Regionale per l’Innovazione e gli Acquisti, S.p.A, Milan, Italy; 5Apulian Regional Health Department, Bari, Italy; 6Azienda Zero, Regione Veneto, Italy; 7Department of Epidemiology, Lazio Regional Health Service, Rome, ItalyCorrespondence: Gianluca Trifirò, Department of Diagnostics and Public Health, University of Verona, P. le L.A. Scuro 10, Verona, 37134, Italy, Tel +39 045 802 7679, Email gianluca.trifiro@univr.it

Ylenia Ingrasciotta,1,2 Valentina Isgrò,1 Saveria Serena Foti,2 Valentina Ientile,3 Andrea Fontana,4 Luca L’Abbate,3 Roberto Benoni,1 Elena Sofia Fiore,1 Michele Tari,5 Angela Alibrandi,6 Gianluca Trifirò1,2 1Department of Diagnostics and Public Health, University of Verona, Verona, Italy; 2Academic Spin-off “INSPIRE – Innovative Solutions for Medical Prediction and Big Data Integration in Real World Setting” – Azienda Ospedaliera Universitaria “G. Martino”, Messina, Italy; 3Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy; 4Unit of Biostatistics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni, Rotondo, Italy; 5Caserta-1 Local Health Service, Caserta, Italy; 6Department of Economics, University of Messina, Messina, ItalyCorrespondence: Ylenia Ingrasciotta, Department of Diagnostics and Public Health, University of Verona, P. le L.A. Scuro 10, Verona, 37134, Italy, Tel +39 045 802 7679, Email ylenia.ingrasciotta@univr.itBackground: Inflammatory bowel diseases (IBDs), Crohn’s disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs.Objective: To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database.Methods: Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score.Results: In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥ 1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1– 80.5) to 98.8 (95% CI: 93.5– 100.0) for CD and from 64.7% (95% CI: 50.1– 77.6) to 94.1 (95% CI: 83.8– 98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was “Algorithm 3”, based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was “Algorithm 3”, based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857).Conclusion: In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use.Keywords: biological drugs, algorithm, healthcare database, ulcerative colitis, Crohn’s disease