Adolescent idiopathic scoliosis (AIS) is a common spinal deformity with potentially severe consequences if the curve progresses unchecked. At the initial presentation, predicting future curve progression is crucial for managing therapy effectively. A risk analysis algorithm for curve progression would greatly assist patients and their families.
This systematic review identified several predictive factors correlated with a higher risk of curve progression.
The initial curve magnitude and skeletal maturity status
These characteristics emerged as the most relevant factors for predicting curve progression, followed by curve location, age, and menarche status. However, these factors have been considered independently, and their interactions have not been thoroughly investigated. When developing a risk analysis algorithm for AIS curve progression, the authors of the publication recommend that the focus should be on radiological parameters accessible during clinic visits while minimizing radiation exposure.
Radiological parameters
Several studies have highlighted the significant correlation between initial curve magnitude and the risk of progression (Table 2). Initial curve magnitude is a radiological parameter that can be easily diagnosed from standard radiographs. In the studies included in this analysis, a Cobb angle > 25–28° at initial presentation was mainly correlated with curve progression to > 50° of Cobb or the need for surgical intervention. Certainly, as adolescents are still in the growth phase, the actual curve progression also depends on skeletal maturity.
Interestingly, curve location, which is also easily diagnosed, was found significant in the investigation by Dolan et al. [16]. In their Akaike information criterion (AIC) model, they presented that thoracic curves were more likely to progress than lumbar or thoracolumbar curves (OR = 4.09). However, two other studies did not find any significance in curve location [32, 21].
Skeletal maturity, another major risk factor for progression
[13, 32, 15, 16, 23, 24]
Controversial findings exist regarding the actual categorization mechanism, with numerous studies highlighting inadequate predictability of further growth by Risser stages, and Risser classification being dependent on descent or bone mineral status [26]. Tanner and Whitehouse used DRU scores to establish a different method for determining skeletal maturity in adolescence [41]. Sanders, however, reported the lowest correlation of radius/ulna scores to curve acceleration phase [42], and Distal Radius and Ulna Classification (DRU) scores were modified by Luk et al. [43]. Neal et al. [28] documented a higher correlation to skeletal ossification based on SMS rather than Risser, but Risser is still significant, as confirmed by Sitoula et al. [32], who reported significant predictive probability for SMS and Risser stages. Moreover, recently published additional classification systems, such as the distal radius and ulna score, as well as the proximal humerus ossification scale, may allow for even further evaluation of stages at risk, as demonstrated by Li et al. [23, 24].
Regarding additional radiological parameters, specifically sagittal parameters, such as L3/4 tilt, pelvic tilt, T1 and T9 spinopelvic inclination, SPA and apical vertebrae angle, are parameters easily analyzed in standard radiographs and do not require additional radiation. These new parameters should be evaluated further in prospective studies.
The references and annotations in this post follow the numeration of the original article