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Table 4 Final multivariate post-treatment 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 = 249/93)b

Future pain intensity (N = 262/93)b

Independent variables

OR

(95 % CI)

P-value

 

β

(95 % CI)

P-value

Dose (per 6 spinal manipulation visits)

1.14

(0.95, 1.37)

0.150

 

−0.07

(−1.35, 1.21)

0.910

Time (in weeks)

1.08

(1.02, 1.14)

0.004

    

Pain/Disability

       

 Pain intensity

0.64

(0.51, 0.80)

<0.001

 

10.7

(8.84, 12.56)

<0.001

 Days with pain (last 4 weeks)

0.57

(0.46, 0.70)

<0.001

    

Objective Physical Exam

       

 LBP: right – left lateral bending

0.76

(0.63, 0.92)

0.005

    

 LBP: right lateral bending

    

2.95

(1.21, 4.69)

0.001

Performance metricsc

AUC

(95 % CI)

 

RMSE

(95 % CI)

R2

(95 % CI)

Training set

0.750

  

16.3

 

.366

 

Test set

0.665

(0.58, 0.74)

 

17.5

(15.0, 20.1)

.261

(7.5, 43.2)

  1. OR Odds ratio, PC part correlation, β regression coefficient, ROM range of motion, 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 time (scale unit = 1 week). Lower scores were favorable for pain and days with pain
  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 are given for the test set only