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Table 2 Final multivariate pretreatment pain-prediction models and performance metricsa

From: Prediction of pain outcomes in a randomized controlled trial of dose–response of spinal manipulation for the care of chronic low back pain

 

Responders (N = 297/94)b

Future pain intensity (N = 289/94)b

Independent variables

OR

(95 % CI)

P-value

 

β

(95 % CI)

P-value

Dose (per 6 spinal manipulation visits)

1.27

(1.08, 1.49)

0.004

 

−1.86

(−3.35, −0.38)

0.014

Pain/Disability

       

 Pain intensity

    

4.77

(1.85, 7.70)

0.001

 Pain unpleasantness

    

3.29

(0.35, 6.24)

0.028

General Health

       

 Comorbidities

0.81

(0.67, 0.97)

0.025

    

 EuroQol – VAS

    

−2.20

(−4.00, −0.39)

0.017

 EuroQol 5D – self-care (1–3)

0.64

(0.41, 0.99)

0.044

    

Objective Physical Exam

       

 LBP: sum for 4 lumbar ROM pain scores

0.81

(0.67, 0.97)

0.024

 

2.89

(0.61, 5.16)

0.013

Performance metricsc

AUC

(95 % CI)

 

RMSE

(95 % CI)

R2

(95 % CI)

 Training set

0.624

  

17.4

 

.268

 

 Test set

0.479

(0.387, 0.575)

 

19.4

(17.0, 21.6)

.065

(−10.5, 21.9)

  1. OR Odds ratio, PC part correlation, β regression coefficient, VAS visual analogue scale, AUC Area under the curve (receiver operating characteristic curve), RMSE root mean squared error (SD of prediction error), R2 coefficient of determination, LBP low back pain
  2. aVariables were selected into the regression models using forward selection among variables with p < .05 in the univariate analysis; dose was forced into the models. Independent variables were standardized except for dose (scale unit = 6 visits) and self-care (scale unit = 1 on a 1–3 scale). Lower scores were favorable for pain and self-care; higher scores for EuroQol VAS
  3. bThe first number is the sample size for the model in the training set and the second number is the N for the test set
  4. cChance performance is indicated by 0.5 for AUC. RMSE is the standard deviation of the error in prediction of future pain intensity evaluated on the 0 – 100 pain scale. R2 is the proportion of the variance in pain intensity explained by the independent variables in the model. Confidence intervals for the performance metrics are given for the test set only