Lumbar Scoliosis in Postmenopausal Women Increases With Age but Is Not Associated With Osteoporosis

Janet Rubin; Rebecca J. Cleveland; Alexander Padovano; David Hu; Maya Styner; James Sanders

Disclosures

J Endo Soc. 2021;5(5) 

In This Article

Materials and Methods

Study Design and Participants

A total of 900 women with density images and assessments captured in the University of North Carolina at Chapel Hill electronic medical record from 2014 to 2019 were randomly selected from assigned patient numbers recalling those who had received bone density scans. The patient population consisted of all women in our health care system and did not represent a subspecialty population. We focused on 3 age groups: 64 to 68 years (N = 300), 74 to 78 years (N = 300), and 84 to 88 years (N = 300). The age groups were selected to reflect the age of an initial baseline screening DXA in the United States (64 to 68 years), as well as DXA's performed in subsequent decades.[18] The institutional review board approved all aspects of this study.

Medical records of female patients having available DXA images were selected by a random number generator. Patient DXAs were analyzed with regard to ethnicity, weight, and T scores at 3 regions of interest. Height was not analyzed because it is inaccurately measured, or not measured at all, in radiology departments. Exclusion criteria included the presence of spinal instrumentation or absence of an available image (ie, performed at an outside facility where images were not available in our electronic health record). Cobb angle and osteoporosis at a single time point were assessed using the same scans. In a subset of 51 participants for whom more than one DXA was available, Cobb angle was determined in up to 7 sequential DXA exams.

Scoliosis Definition and Assessment

The Cobb angle is an accepted analysis of scoliosis severity and is determined by measuring the angle between the 2 maximally oppositely tilted superior vertebral end plate above and inferior end plate below the curve apex. Scoliosis was defined as a Cobb angle of 10° or more. Interpretation of Cobb scores in our study was completed by 2 independent readers (J.R. and J.S.). Intrarater agreement was high for continuous Cobb scores, with an intraclass correlation (ICC) of 0.92 (0.90–0.93), and for the dichotomous scoliosis definition (κ = 0.79; 95% CI, 0.76–0.82). Because of the high agreement, we used the mean Cobb score from both readers.

The reliability of Cobb angle measured from DXA scans was compared with Cobb angle assessed from other imaging modalities, which occurred within a 15-month window of the DXA scan. Twenty-nine patients had other imaging modalities available including lumbar x-rays, abdominal computed tomography scout films, and magnetic resonance imaging for comparison. Reliability was high, with an ICC of 0.92 (95% CI, 0.84–0.96), indicating substantial agreement between the measurements from different scans and validates the use of DXA scans in measuring Cobb angles, as performed by others.[15]

Osteoporosis Definition and Assessment

Osteoporosis was assessed using data obtained from DXA scans. T scores were assigned for the spine, hip neck, and TH. A T score of less than or equal to –2.5 was defined as consistent with a diagnosis of osteoporosis at that site. Having a diagnosis of osteoporosis at any one site (spine, TH, or FN) was considered as a diagnosis of osteoporosis.

Statistical Analyses

Descriptive statistics for covariates according to osteoporosis status were computed. Covariates included age, race (White or non-White), and body weight. Age in years was also used in some analyses as groups: 64 to 68, 74 to 78, and 84 to 88. Continuous variables are presented as means ± SD, and categorical variables are presented as frequencies and percentages. Normality was assessed with the Kolmogorov-Smirnov test. All tests were 2-sided and considered statistically significant at the .05 level. Analyses were conducted using the statistical software package SAS version 9.4 (SAS Institute Inc).

A missing image or presence of hardware was present in 390 (43%) of participants who were randomly sampled (Figure 1). Another 26 participants (3%) either had a missing Cobb angle reading from one reader or were missing covariates, for a final analysis sample size of 484 participants. For the assessment of an association between osteoporosis measures and presence of scoliosis, odds ratios (ORs) and 95% CI were calculated using logistic regression models for the presence of osteoporosis.[19] Covariates included age, weight, and race.

Figure 1.

Flowchart for data acquisition.

The post hoc power analysis considered the power required to detect an arbitrary partial Pearson correlation (based on continuous variables as opposed to a categorical yes/no) at a .05 α level using Fisher z test. While our analysis had excellent power to detect a 0.30 correlation, it actually has substantial power throughout: Even with a threshold of 0.90, a 0.15 partial Pearson correlation could be detected with 0.830 power.

An additional longitudinal analysis was performed on a subset of 51 individuals in the data set, without regard to initial Cobb angle or to BMD, to gather information on with longitudinal progression of lumbar curvature. Individuals were entered in this analysis if 2 or more DXA images were available for analysis. A linear mixed model was used for repeated measures, assuming a within-subjects spatial power covariance structure due to unequal numbers of follow-ups and irregular follow-up times (SAS/STAT15.1 User's Guide; SAS Institute, 2018). A spatial power model is similar to an autoregressive model in that observations closer in time are more correlated than observations further apart, but it does not require the time between observations to be equal. This model can also accommodate missing data points due to an unequal number of follow-ups.

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