Idiopathic Scoliosis Progression Risk Calculator

Written and reviewed for scientific and factual accuracy by Dr. Austin Jelcick, PhD and Dr. Matthew Janzen, DC. Last reviewed/edited on October 28, 2020. First published May 20, 2019.

Predicting whether or not a child’s scoliosis will progress does not require a crystal ball or a World Almanac from the future. Past and present scientific literature and scientific studies provide us with evidence based calculations to help predict whether or not a scoliosis curve of the spine will worsen and progress. Enter your information below and easily calculate your risk of progression and learn more about how this is performed below.

In addition to your calculated risk of progression (chance that the scoliosis curve will worsen), you also will receive information regarding treatment potential. This is based on our current and past patient data and includes your probability of completing treatment with the scoliosis curve below surgical criteria; the average correction achieved based on your curve size; and the maximum correction (currently observed in our patients) based on your curve size. You can also view real patient results based on your curve size.

We hope this helps you during your scoliosis treatment journey!

Enter Your Information Here!

Please note, this calculator is designed for children and teens under the age of 18 or who have not reached skeletal maturity.
Hover over each item (ie. Cobb Angle) for additional information.

Cobb Angle :
Risser :
Age (years) :

Your risk of progression if untreated:

Risk of progression means this: If a scoliosis is left untreated, a curve worsening 5 degrees or more (for curves >20 degrees) or a curve worsening 10 degrees or more (for curves <20 degrees) is considered to be progressing.

VERSUS

Your probability for finishing treatment below surgical criteria:


Average correction for your curve size:



Your maximum expected correction:




View Results for Your Category

Adapted from: Lonstein, JE; Carlson, JM. The prediction of curve progression in untreated idiopathic scoliosis during growth. J Bone Joint Surg Am. 1984 Sep;66(7):1061-71. Calculator Copyright 2020 Janzen & Janzen Chiropractic Corp's Scoliosis Care Centers.

Learn How We Can Help

When discussing scoliosis treatment, it is highly useful to be able to estimate or predict whether or not a scoliosis curve will progress. Predicting whether or not a scoliosis curve of the spine will progress to surgical range is important as if we know a curve has a high probability of worsening, we know that early intervention is needed even more.

Various scientific studies have been conducted to determine a risk factor or formula to estimate the risk for scoliosis progression for individuals with idiopathic scoliosis. In general, the more growing a child with scoliosis has to do; the greater the chance is that their scoliosis will worsen1. As a young child’s skeleton is immature and can undergo rapid periods of growth during puberty, their scoliosis can rapidly progress during these growth spurts4, 5

Examining Curve Progression

Based on the size of a curve present in a child at a particular stage of development, we can predict their likelihood of progression. As age does not directly correspond to a given stage of puberty (every child is different7), we estimate scoliosis progression risk utilizing a combination of bone/skeletal age (determined by Risser sign), age, and the Cobb angle of the curve.

For instance, a 2017 study found that at the beginning of puberty (onset of pubertal growth), children with curves greater than 30 degrees had a 100% risk of progression to surgical range (>45 degrees); while children with curves 21 – 30 degrees still had a 72.5% risk of progressing to surgical range2. Similarly, another study examining children with idiopathic scoliosis who were untreated (no bracing, etc.) found that curve progression was directly related to the size and pattern of the curve, as well as their age, skeletal age (Risser sign), and menarchal status6.

Out Of Growth, Out Of The Woods?

While one might think that the risk of progression would begin to decrease after the peak rate of growth, a 2018 study found that the highest rate of scoliosis curve progression can happen after the peak rate of growth during a child’s growth spurt; with the period of time where curve progression could occur extending one and a half years after the peak rate, until skeletal maturity3. Therefore, scoliosis curves should continue to be closely monitored as a child is not “out of the woods” simply because they have passed their peak rate of growth.

While all of the factors discussed above contribute to the likelihood of progression, curve size is of paramount importance as initial Cobb angle8 is a recurring theme throughout the scientific literature: the larger the angle, the higher the risk for progression.

How To Predict Scoliosis Progression Risk

While modern day genetic testing and whole genome sequencing has found numerous genetic components which may be risk factors, additional studies are needed to confirm all of these and distill them into a true assessment for risk. Therefore, we can estimate scoliosis progression risk utilizing easily observable factors of a child and their scoliosis until a highly accurate, truly predictive genetic panel is developed and validated. Lonstein et al. conducted a study to determine a mathematical equation to assist in predicting curve progression utilizing easily observable items: a child’s age, their Risser sign (skeletal age), and the Cobb angle of their scoliosis.

Using these three items a risk factor was calculated and then compared to actual progression in patients. This correlation of calculated risk factor and actual observed progression was utilized to generate an predictive equation6.

Calculate Your Risk Of Scoliosis Progression

The calculator at the top of the page utilizes the equation and correlation determined by Lonestein et. Al and provides a progression risk based on the information you enter. Simply enter your child’s Cobb angle, Risser sign, and age; click the calculate button, and the likelihood of progression will appear. You will also find a button below to contact a Care Director to discuss your case further in detail; and can review scoliosis treatment results here as well.

References

  1. Bunnell, W. P. (1986): The natural history of idiopathic scoliosis before skeletal maturity. In Spine 11 (8), pp. 773–776.
  2. Charles, Yann Philippe; Daures, Jean-Pierre; Rosa, Vincenzo de; Diméglio, Alain (2006): Progression risk of idiopathic juvenile scoliosis during pubertal growth. In Spine 31 (17), pp. 1933–1942. DOI: 10.1097/01.brs.0000229230.68870.97.
  3. Cheung, Jason Pui Yin; Cheung, Prudence Wing Hang; Samartzis, Dino; Luk, Keith Dip-Kei (2018): Curve Progression in Adolescent Idiopathic Scoliosis Does Not Match Skeletal Growth. In Clinical Orthopaedics and Related Research 476 (2), pp. 429–436. DOI: 10.1007/s11999.0000000000000027.
  4. Cousminer, Diana L.; Berry, Diane J.; Timpson, Nicholas J.; Ang, Wei; Thiering, Elisabeth; Byrne, Enda M. et al. (2013): Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity. In Human molecular genetics 22 (13), pp. 2735–2747. DOI: 10.1093/hmg/ddt104.
  5. Dimeglio, Alain; Canavese, Federico (2013): Progression or not progression? How to deal with adolescent idiopathic scoliosis during puberty. In Journal of children’s orthopaedics 7 (1), pp. 43–49. DOI: 10.1007/s11832-012-0463-6.
  6. Lonstein, J. E.; Carlson, J. M. (1984): The prediction of curve progression in untreated idiopathic scoliosis during growth. In The Journal of bone and joint surgery. American volume 66 (7), pp. 1061–1071.
  7. Melmed, Shlomo; Polonsky, Kenneth S.; Larsen, P. Reed; Kronenberg, Henry (2016): Williams textbook of endocrinology. Philadelphia, PA: Elsevier.
  8. Tan, Ken-Jin; Moe, Maung Maung; Vaithinathan, Rose; Wong, Hee-Kit (2009): Curve progression in idiopathic scoliosis. Follow-up study to skeletal maturity. In Spine 34 (7), pp. 697–700. DOI: 10.1097/BRS.0b013e31819c9431.