Open Access<p>Homogeneity in prediction of survival probabilities for subcategories of hipprosthesis data: the Nordic Arthroplasty Register Association, 2000–2013</p>
Author(s) -
Christoffer BartzJohannessen,
Ove Furnes,
Anne Marie Fenstad,
Stein Atle Lie,
Alma B Pedersen,
Søren Overgaard,
Johan Kärrholm,
Henrik Malchau,
Keijo Mäkelä,
Antti Eskelinen,
J. Mark Wilkinson
Publication year - 2019
Publication title -
clinical epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.868
H-Index - 58
ISSN - 1179-1349
DOI - 10.2147/clep.s199227
Subject(s) - medicine , pooling , covariate , demography , statistics , sample size determination , arthroplasty , survival analysis , hazard ratio , surgery , mathematics , confidence interval , computer science , artificial intelligence , sociology
Introduction: The four countries in the Nordic Arthroplasty Register Association (NARA) share geographic proximity, culture, and ethnicity. Pooling data from different sources in order to obtain higher precision and accuracy of survival-probability estimates is appealing. Nevertheless, survival probabilities of hip replacements vary between the countries. As such, risk prediction for individual patients within countries may be problematic if data are merged. In this study, our primary question was to address when data merging for estimating prosthesis survival in subcategories of patients is advantageous for survival prediction of individual patients, and at what sample sizes this may be advised. Methods: Patients undergoing total hip replacements for osteoarthritis between January 1, 2000 and December 31, 2013 in the four Nordic countries were studied. A total of 184,507 patients were stratified into 360 patient subcategories based on country, age-group, sex, fixation, head size, and articulation. For each patient category, we determined the sample size needed from a single country to obtain a more accurate and precise estimate of prosthesis-survival probability at 5 and 10 years compared to an estimate using data from all countries. The comparison was done using mean-square error. Results: We found large variations in the sample size needed, ranging from 40 to 2,060 hips, before an estimate from a single Nordic country was more accurate and precise than estimates based on the NARA data. Conclusion: Using pooled survival-probability estimates for individual risk prediction may be imprecise if there is heterogeneity in the pooled data sources. By applying mean-square error, we demonstrate that for small sample sizes, applying the larger NARA database may provide a more accurate and precise estimate; however, this effect is not consistent and varies with the characteristics of the subcategory.