Development and validation of a risk-prediction nomogram for chronic low back pain using a national health examination survey

Background Several prognostic factors for chronic low back pain (CLBP) have been reported. However, there is no study regarding the prediction of CLBP development in general population, using a risk prediction model. Based on this background, the aims of this study were: (1) to develop and validate a risk prediction model for CLBP (chronic low back pain) development in the general population, and (2) to create a nomogram which can help a person at risk of developing CLBP to receive appropriate counseling on risk modification.Methods Data on CLBP development, demographics, socioeconomic history, and comorbid health condition of participants were obtained through a nationally representative health examination and survey from 2007 to 2009. Prediction models for CLBP development were derived for health survey on a random sample of 80% of the data and were validated in the remaining 20%. After developing the risk prediction model for CLBP development, this model was incorporated into a nomogram.Results Data for 17,038 participants were finally analyzed, including 2,693 with CLBP and 14,345 without. The finally selected risk factors included age, gender, occupation, education level, mid-intensity physical activity, depressive symptom, and comorbidities. This model had good predictive performance in the validation dataset (concordance statistic = 0.7569, Hosmer-Lemeshow chi-square statistic = 12.10, p =.278). The findings indicated no significant differences between the observed probability and predicted probability according to our model.Conclusions The risk prediction model, presented by a nomogram, which is a score-based prediction system, could be incorporated into the clinical setting. Thus, our prediction model with a nomogram can help a person at risk of developing CLBP to receive appropriate counseling on risk modification from primary physicians.