Le Stum Mathieu, Le Goff-Pronost Myriam, Stindel Eric, Dardenne Guillaume
Université de Brest, UBO, LATIM, UMR 1101, Brest, France.
Institut National de la Santé et de la Recherche Médicale, INSERM, Laboratory for Medical Information Processing (LATIM), UMR1101, Brest, France.
PLoS One. 2025 Jan 7;20(1):e0312701. doi: 10.1371/journal.pone.0312701. eCollection 2025.
From several decades, the evolutions of the Incidence Rate (IR) of Primary Knee Arthroplasties are continuously increasing worldwide and have been widely studied in several countries. Some recent works have highlighted the fact that the IR is following a sigmoid curve composed of an exponential growth followed by a linear phase and finished by a plateau. Our objective is to assess the IR evolution of eleven European countries, representing thus a large proportion of this continent, regarding this sigmoid.
IRs of primary knee arthroplasties for Austria, Denmark, Finland, France, Germany, Hungary, Italy, Poland, Spain, Sweden, and the United Kingdom between 2005 and 2019 were retrieved from the EUROSTAT database. Several regression models were fitted to each country's IRs: Poisson, linear, asymptotic, logistic, and Gompertz regression. For each country and each model, the RMSE (Root Mean Square Error) and R2 were calculated and used to estimate their position with respect to this sigmoid curve.
The best regression models for knee arthroplasties varied following countries. Logistic and Gompertz regressions had the lowest RMSE and R2 values for Austria, Denmark, Germany, Sweden, and the UK. Hungary, Italy, and Poland favored the Poisson regression model. Finland and Spain presented difficulties in determining the optimal model (linear or Poisson), while France faced challenges in choosing between logistic, Gompertz, and linear regression.
In conclusion, the growth dynamics of IR differ across European countries. Some countries seem to have already reached a plateau and will therefore experience slight growth in the future.
几十年来，全球原发性膝关节置换术发病率（IR）持续上升，多个国家对此进行了广泛研究。近期一些研究指出，发病率呈S形曲线变化，先是指数增长，接着是线性阶段，最后趋于平稳。我们的目标是评估代表欧洲大陆很大一部分的11个欧洲国家的发病率变化情况，以研究这种S形曲线。
从欧盟统计局数据库中获取2005年至2019年奥地利、丹麦、芬兰、法国、德国、匈牙利、意大利、波兰、西班牙、瑞典和英国的原发性膝关节置换术发病率。对每个国家的发病率拟合了几种回归模型：泊松回归、线性回归、渐近回归、逻辑回归和冈珀茨回归。对于每个国家和每个模型，计算均方根误差（RMSE）和R²，并用于估计它们相对于该S形曲线的位置。
膝关节置换术的最佳回归模型因国家而异。奥地利、丹麦、德国、瑞典和英国的逻辑回归和冈珀茨回归的RMSE和R²值最低。匈牙利、意大利和波兰倾向于泊松回归模型。芬兰和西班牙在确定最佳模型（线性或泊松）方面存在困难，而法国在逻辑回归、冈珀茨回归和线性回归之间进行选择时面临挑战。
总之，欧洲各国发病率的增长动态各不相同。一些国家似乎已经达到平稳期，因此未来增长将较为缓慢。
