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Background: The International Classification of Diseases (ICD) is widely used by clinical coders worldwide for clinical coding morbidity data into administrative health databases. Accordingly, hospital data quality largely depends on the coders' skills acquired during ICD training, which varies greatly across countries. Objective: To characterise the current landscape of international ICD clinical coding training. Method: An online questionnaire was created to survey the 194 World Health Organization (WHO) member countries. Questions focused on the training provided to clinical coding professionals. The survey was distributed to potential participants who met specific criteria, and to organisations specialised in the topic, such as WHO Collaborating Centres, to be forwarded to their representatives. Responses were analysed using descriptive statistics. Results: Data from 47 respondents from 26 countries revealed disparities in all inquired topics. However, most participants reported clinical coders as the primary person assigning ICD codes. Although training was available in all countries, some did not mandate training qualifications, and those that did differed in type and duration of training, with college or university degree being most common. Clinical coding certificates most frequently entailed passing a certification exam. Most countries offered continuing training opportunities, and provided a range of support resources for clinical coders. Conclusion: Variability in clinical coder training could affect data collection worldwide, thus potentially hindering international comparability of health data. Implications: These findings could encourage countries to improve their resources and training programs available for clinical coders and will ultimately be valuable to the WHO for the standardisation of ICD training. [ABSTRACT FROM AUTHOR]

Objectives: To compare the treatment effectiveness of secukinumab in radiographic (r) versus non-radiographic (nr) axial spondyloarthritis (axSpA) patients treated in routine care across Europe., Methods: Prospectively collected data on secukinumab-treated axSpA patients with known radiographic status were pooled from nine countries.Remission rates based on patient-reported outcomes (PROs; Numeric Rating Scale (0-10), for example, pain ≤2/Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) ≤2 and Ankylosing Spondylitis Disease Activity Score (ASDAS) inactive disease (ID) <1.3 after 6/12/24 months of secukinumab treatment were calculated.Remission and drug retention rates in r-axSpA versus nr-axSpA patients were compared by logistic and Cox regression models (unadjusted/adjusted for age+sex/adjusted for multiple confounders)., Results: Overall, 1161 secukinumab-treated patients were included (r-axSpA/nr-axSpA: 922/239). At baseline, r-axSpA patients had longer disease duration and higher C reactive protein, were more often male and HLA-B27 positive and had received fewer prior biological or targeted synthetic disease-modifying antirheumatic drugs compared with nr-axSpA patients, whereas PROs were largely similar.During follow-up, crude PRO remission rates were significantly higher in r-axSpA compared with nr-axSpA patients (6 months: pain≤2: 40%/28%, OR=1.7; BASDAI≤2: 37%/25%, OR=1.8), as were drug retention rates (24 months: 66%/58%, HR 0.73 (ref: r-axSpA)). Proportions of patients achieving ASDAS ID were low for both groups, particularly nr-axSpA (6 months: 11%/8%).However, when adjusting for age+sex, these differences diminished, and after adjusting for multiple confounders, no significant between-group differences remained for either remission or drug retention rates., Conclusion: Crude remission/drug retention rates in European secukinumab-treated patients were higher in r-axSpA compared with nr-axSpA patients. In adjusted analyses, secukinumab effectiveness was similar in both groups, suggesting that observed differences were related to factors other than radiographic status., Competing Interests: Competing interests: SNC: Speaker fees BMS and GE, Research grant from Novartis (paid to the employer). SHR: Research grant from Novartis (paid to the employer). MO: Speaker and/or consultancy fees from AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB. Research grants from AbbVie, BMS, Merck, Novartis and UCB. MP: Research grant from Novartis (paid to the employer). Speaker fees: Sandoz. Brigitte Michelsen: Consulting fees from Novartis. Research grant from Novartis (paid to employer). KP: Consultancy fees: AbbVie, UCB, Pfizer, Eli Lilly, Celltrion, MSD and Novartis. Catalin Codreanu: Speaker and consultancy fees from AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer. Adrian Ciurea: None. Bente Glintborg: Research grants from Pfizer, Abbvie, BMS, Sandoz. MJS: Speaker fees from AbbVie, AstraZeneca, Janssen, Lilly, Medac, Novartis, Pfizer. Ismail Sari: None. ZR: Speaker and consultancy fees from Abbvie, Novartis, Eli Lilly, Pfizer, Janssen, SOBI, Swixx BioPharma, AstraZeneca, Amgen, MSD, Medis, Biogen, Eli Lilly, Sanofi, Lek. BG: Speaker and consultancy fees from Novartis and Nordic-Pharma. GJM: Research grant from GSK. HR: Consulting and/or speaking fees from AbbVie, Celgene, Pfizer, UCB, Viatris. FI: None. Karin Laas: Speakers fees from AbbVie, Johnson and Johnson, Novartis, Pfizer. JKW: Speaker fees from AbbVie, Amgen. Research support from AbbVie, Amgen, Eli Lilly, Novartis, Pfizer. MvdS: Consultant for Novartis, AbbVie, Eli Lilly UCB, Speakers fee: Novartis, UCB, Janssen, Grant/research support: UCB, Janssen, Novartis, Eli Lilly. Sella Aarrestad Provan: Consultancy fees and Research grants from Boehringer Ingelheim. IC: Speaker and/or consultancy fees from BMS, Eli-Lilly, Galapagos, Gilead, Janssen, Novartis, MSD, Pfizer, GSK. JZ: Speakers fees from AbbVie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Sanofi, Astra Zeneca, Sobi. CM: None. MJN: Speaker and/or consultancy fees from AbbVie, Amgen, Eli Lilly, Janssens, Novartis, Pfizer. Research grants from Novartis and Pfizer. AGL: Speaking and/or consulting fees from AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB. Research grant from Novartis. AB: Speaker and/or consultancy fees from AbbVie, Lilly, Janssen and Novartis. YE: None. Katja Perdan Pirkmajer: Speaker and/or consultancy fees from AbbVie, Novartis, MSD, Medis, Eli Lilly, Pfizer, Lek, Janssen and Boehringer Ingelheim. GG: None. GTJ: Speaker fee from Janssen. Research grants (paid to employer) from AbbVie, Pfizer, UCB, Amgen, GSK. A-MH: Grant/research support from MSD. MSC: None. SV: None. DdG: None. TKK: Speaker and/or consultancy fees from AbbVie, Amgen, Celltrion, Gilead, Novartis, Pfizer, Sandoz, UCB and Grünenthal. LO-V: None. IvdH-B: Speaker and/or consultancy fees from AbbVie, UCB, MSD, Novartis, Lilly. Unrestricted Grants received for investigator initiated studies from MSD, Pfizer, AbbVie, UCB. Fees received for Lectures from BMS, AbbVie, Pfizer, MSD, UCB. MLH: Advisory Board AbbVie (No personal income, paid to institution). Prev. chaired the steering committee of the Danish Rheumatology Quality Registry (DANBIO, DRQ), which receives public funding from the hospital owners and funding from pharmaceutical companies. Speaker for Pfizer, Medac, Sandoz (no personal income, institution). Research grants (institution) from AbbVie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Nordforsk. LMO: Research grant from Novartis (paid to the employer)., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: To investigate sex differences in patient-reported outcome measures (PROMs) among axSpA patients initiating their first TNFi and identify factors contributing to these disparities over the follow-up., Methods: Data were included from 15 EuroSpA registries and consisted of axSpA patients initiating their first TNFi, with ≥2 measurements for each analysed PROM (BASDAI and BASFI, scale 0-100) taken at any time point. Linear mixed models were employed to analyse sex differences in PROMs over 24 months and to evaluate how baseline characteristics were related to the observed sex differences., Results: We analysed 13 102 (38% women) in the BASDAI analyses and 10 623 (38% women) in the BASFI analyses. At follow-up, mean sex differences in BASDAI increased from 4.3 units at baseline (95% CI, 3.5-5.1)-8.0 (7.2-8.8) at 6 months, and in BASFI from 2.2 (1.4-3.1)-4.6 (3.6-5.5), with consistently worse scores in women. Baseline characteristics could not substantially account for the observed sex differences over time; however, the magnitude of the sex differences was reduced by HLA-B27 positivity, longer disease duration, and increased CRP levels, but increased by TNFi initiation in later years and peripheral arthritis., Conclusion: In axSpA patients initiating their first TNFi, baseline sex differences in BASDAI and BASFI increased two-fold after 6 months of treatment and persisted thereafter, with worse scores in women. Several baseline characteristics moderated the sex differences, though none could fully account for them. These findings improve our understanding of sex differences and underscore their importance in axSpA., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)