The NIH Minimal Dataset for Chronic Low Back Pain: Responsiveness and Minimal Clinically Important Change

Study Design. Prospective cohort study. Objective. To analyze responsiveness and minimal clinically important change (MCIC) of the US National Institutes of Health (NIH) minimal dataset for chronic low back pain (CLBP). Summary of Background Data. The NIH minimal dataset is a 40-item questionnaire developed to increase use of standardized definitions and measures for CLBP. Longitudinal validity of the total minimal dataset and the subscale Impact Stratification are unknown. Methods. Total outcome scores on the NIH minimal dataset, Dutch Language Version, were calculated ranging from 0 to 100 points with higher scores representing worse functioning. Responsiveness and MCIC were determined with an anchor-based method, calculating the area under the receiver operating characteristics (ROC) curve (AUC) and by determining the optimal cut-off point. Smallest detectable change (SDC) was calculated as a parameter of measurement error. Results. In total 223 patients with CLBP were included. Mean total score on the NIH minimal dataset was 44 ± 14 points at baseline. The total outcome score was responsive to change with an AUC of 0.84. MCIC was 14 points with a sensitivity of 72% and specificity 82%, and SDC was 23 points. Mean total score on Impact Stratification (scale 8–50) was 34.4 ± 7.4 points at baseline, with an AUC of 0.91, an MCIC of 7.5 with a sensitivity 96% of and specificity of 78%, and an SDC of 14 points. Conclusion. The longitudinal validity of the NIH minimal dataset is adequate. An improvement of 14 points in total outcome score and 7.5 points in Impact Stratification can be interpreted as clinically important in individual patients. However, MCIC depends on baseline values and the method that is chosen to determine the optimal cut-off point. Furthermore, measurement error is larger than the MCIC. This means that individual change scores should be interpreted with caution. Level of Evidence: 2

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