Relationship between certainty of axSpA and treatemnt response
Authors
Mills, Emma Marie ; Nielsen, Amalie Birk ; Mills, Alexander Andrew Matthew
Term
5. Term (Master thesis)
Education
Publication year
2024
Pages
21
Abstract
Formål: at undersøge om behandlingsresultater adskiller sig mellem patienter med 'sikker' aksial spondyloartrit (axSpA), der opfylder ASAS-klassifikationskriterierne, og patienter med en klinisk axSpA-diagnose, som ikke gør. Metode: et retrospektivt kohortestudie baseret på journalgennemgang med data fra elektroniske journalsystemer og den kliniske database DANBIO; MR-scanninger blev vurderet af en radiolog. Patienterne blev inddelt som 'sikker' axSpA (opfylder ASAS-kriterier) eller klinisk axSpA (lægen stiller diagnosen uden at alle kriterier er opfyldt). Vi sammenlignede ændringer i BASDAI (et patientrapporteret symptomscore, hvor højere tal betyder mere sygdomsaktivitet), hvor længe patienterne forblev på en given behandling (behandlingsfastholdelse), og effekten af non-steroide antiinflammatoriske lægemidler (NSAID) sammenlignet med biologiske sygdomsmodificerende antireumatiske lægemidler (bDMARDs). Vi anvendte almindelige statistiske modeller til at sammenligne grupper over tid. Resultater: Blandt 129 patienter blev 71 klassificeret som 'sikker' axSpA og 58 som klinisk axSpA. Der var ingen statistisk signifikant forskel i behandlingsrespons mellem grupperne. Patienter med 'sikker' diagnose havde tendens til at blive længere på behandlingen end klinisk diagnosticerede, men forskellen var ikke signifikant (p = 0,078). Overordnet set faldt BASDAI i begge grupper under behandling, og overlappende konfidensintervaller tydede på ingen signifikante forskelle. Behandling med bDMARDs gav større fald i BASDAI end behandling med NSAID, uanset diagnosegruppe (p < 0,05). Konklusion: Der blev ikke fundet en klar forskel i behandlingsrespons mellem patienter med 'sikker' og klinisk axSpA. Selvom 'sikker' diagnose var forbundet med længere behandlingsfastholdelse og muligvis bedre effekt, var dette ikke statistisk sikkert. Begge grupper havde gavn af behandling, hvilket rejser spørgsmål om nødvendigheden af at følge klassifikationskriterierne strengt i kliniske beslutninger.
Objective: to examine whether treatment outcomes differ between patients with 'certain' axial spondyloarthritis (axSpA) who meet the ASAS classification criteria and patients with a clinical axSpA diagnosis who do not. Methods: a retrospective cohort study using medical record review with data from electronic health systems and the clinical database DANBIO; MRI scans were assessed by a radiology specialist. Patients were grouped as 'certain' axSpA (met ASAS criteria) or clinical axSpA (diagnosed by the clinician without meeting all criteria). We compared changes in BASDAI (a patient-reported symptom score where higher values indicate more active disease), how long patients stayed on a given treatment (treatment adherence), and the effects of non-steroidal anti-inflammatory drugs (NSAIDs) versus biologic disease-modifying antirheumatic drugs (bDMARDs). We used standard statistical models to compare groups over time. Results: Of 129 patients, 71 were classified as 'certain' and 58 as clinical. There was no statistically significant difference in treatment response between groups. Patients with a 'certain' diagnosis tended to remain on treatment longer than those with a clinical diagnosis, but this was not significant (p = 0.078). Overall, BASDAI scores decreased with treatment in both groups, and overlapping confidence intervals indicated no significant differences. Treatment with bDMARDs produced larger reductions in BASDAI than NSAIDs regardless of diagnosis group (p < 0.05). Conclusion: We found no clear difference in treatment response between 'certain' and clinical axSpA. Although 'certain' diagnoses were associated with longer adherence and possibly greater effectiveness, this was not statistically significant. Both groups benefited from treatment, raising questions about the need to strictly adhere to classification criteria in clinical decision-making.
[This summary has been rewritten with the help of AI based on the project's original abstract]
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