TABLE 4.

Performance of multivariable linear regression models for predicting pain severity and impact outcomes 1 year after mastectomy

	Surgery specific pain outcomes: Breast Cancer Pain Questionnaire (BCPQ)				General pain outcomes: Brief Pain Inventory (BPI)
	Pain Severity Index	Cognitive emotional impact	Physical impact	Sensory disturbance	BPI mean	BPI impairment
(0–200, higher is worse)	(14–56, higher is worse)	(0–38, higher is worse)	0–8 (higher is worse)	(0–10, higher is worse)	(0–100, higher is worse)
RMSE
Apparent	16.69	4.85	3.75	1.65	1.30	14.87
Optimism-corrected	18.35	5.20	4.01	1.75	1.44	16.42
%RMSE (error as % of reported scores range)	17.64	13.34	20.06	21.91	22.16	19.78
Calibration
Intercept	−0.47	−4.08	−0.48	−0.57	−0.16	−0.71
Slope	1.04	1.21	1.14	1.22	1.11	1.05

RMSE is a measure of the average magnitude of the difference between observed vs. predicted scores. Apparent RMSE reflects predictive performance on the model development sample, while optimism-corrected RMSE (estimated via bootstrapping) is adjusted to better estimate performance on future samples. The shrinkage factor, a measure of model calibration, was estimated as the average slope of the regression line between the observed scores for the original development sample vs. their predicted scores using models built on each bootstrap sample

RMSE root mean square error