Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal

Zixing Bai; Xuhan Cao; Yanjun Yang; Xudong Sun; Yongli Dong; Jianmin Wen; Weidong Sun

doi:10.2147/JPR.S386315

Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal

J Pain Res. 2022 Nov 7:15:3523-3536. doi: 10.2147/JPR.S386315. eCollection 2022.

Authors

Zixing Bai^#¹, Xuhan Cao^#¹, Yanjun Yang¹, Xudong Sun¹, Yongli Dong², Jianmin Wen¹, Weidong Sun¹

Affiliations

¹ Second Department of Orthopedics, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, People's Republic of China.
² Scientific Research Department, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, People's Republic of China.

^# Contributed equally.

Abstract

Objective: To investigate the risk factors for hallux valgus complicated with pain under the second metatarsal and construct an effective model and method for predicting hallux valgus complicated with pain under the second metatarsal based on risk factors.

Methods: A total of 545 patients with hallux valgus who were admitted to our hospital were divided randomly into a training set and a validation set. The demographic characteristics, imaging indices and gait test indices of the patients were collected. The risk factors were identified by univariate and multivariate logistic regression analyses. A risk prediction model for hallux valgus with pain under the second metatarsal was established, and the area under the curve (AUC) of the receiver operating characteristic and a decision curve analysis were used for verification and identification. The value of the model was tested in the verification group.

Results: Second metatarsal length, second metatarsal peak pressure, hallux valgus angle (HVA), intermetatarsal angle 1-2 (IMA1-2) and weight were the risk factors for hallux valgus complicated with pain under the second metatarsal. Based on the weighting of these seven risk factors, a prediction model was established. The AUC of the prediction model was 0.84 (95% confidence interval [CI]: 0.802~0.898, P < 0.05), and the results of a Hosmer-Lemeshow test showed a good degree of calibration (χ ² = 10.62, P > 0.05). The internal validation of the AUC was 0.83 (95% CI: 0.737-0.885, P < 0.05). The model had obvious net benefits when the threshold probability was 10%-70%.

Conclusion: Second metatarsal length, second metatarsal peak pressure, HVA, IMA1-2 and weight were the risk factors for hallux valgus combined with second metatarsal pain. The risk prediction model for hallux valgus complicated with pain under the second metatarsal based on these seven variables was proven effective.

Level of evidence: Level III, retrospective comparative study.

Keywords: hallux valgus; metatarsalgia; nomogram; predictive model; risk factors.

Grants and funding

This research was supported by the Beijing Municipal Science and Technology Project (Z191100006619024) and the Beijing Municipal Natural Science Foundation of China (7172244).