Development and validation of a model for predicting the risk of suicide in patients with cancer

Abstract

Objective

The objective of this study was to establish a nomogram model to predict SI in patients with cancer and further evaluate its performance.

Method

This study was performed among 390 patients in oncology departments of Affiliated Hospital of Nantong University from April 2020 to January 2021. Of these, eligible patients who were diagnosed with cancer were split into training and validation cohorts according the ratio of 2:1 randomly. In the training cohort, multivariate regression was performed to determine the independent variables related to SI. A nomogram was built incorporating these variables. The model performance was evaluated by an independent validation cohort.

Results

The prevalence of SI in patients with cancer was 22.31% and 19.23% in training and validation cohorts, respectively. The nomogram model suggested independent variables for SI, including depression, emotional function, time after diagnosis, family function and educational status. The area under the curve (AUC) was 0.93 (95%CI, 0.90–0.97) and 0.82 (95%CI, 0.74–0.90) in training and validation cohorts respectively, which indicated good discrimination of the nomogram in predicting SI in cancer patients. The p-value of the goodness of fit (GOF) test was 0.197 and 0.974 in training and validation cohorts respectively, suggesting our nomogram model has acceptable calibration power, and the calibration curves further indicated good calibration power.

Conclusion

In conclusion, the nomogram model for predicting individualized probability of SI could help clinical caregivers estimate the risk of SI in patients with cancer and provide appropriate management.

Keywords:

• Cancer
• calibration
• discrimination
• nomogram model
• suicide ideation

ACKNOWLEDGMENTS

The authors sincerely thank all the participants in this study.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was granted by the Humanities and Social Sciences of Ministry of Education Planning Fund [20YJAZH007]; Social and People's Livelihood Technology in Nantong city-General Project [MS12019038] and Postgraduate Research & Practice Innovation Program of Jiangsu Province [KYCX20＿2849].

Notes on contributors

Lin Du

Lin Du, School of Medicine, Nantong University, Nantong, Jiangsu, PR China.

Hai-Yan Shi

Hai-Yan Shi, Department of Thoracic Oncology, The Rugao People's Hospital, Nantong, Jiangsu, PR China.

Yan- Qian

Yan- Qian and Xiao-Hong Jin, Department of Oncology, Affiliated Hospital of Nantong University, Nantong, Jiangsu, PR China.

Xiao-Hong Jin

Yan- Qian and Xiao-Hong Jin, Department of Oncology, Affiliated Hospital of Nantong University, Nantong, Jiangsu, PR China.

Hai-Rong Yu

Hai-Rong Yu, Department of Thoracic Oncology, Affiliated Hospital of Nantong University, Nantong, Jiangsu, PR China.

Xue-Lei Fu

Xue-Lei Fu and Hua Wu, School of Medicine, Nantong University, Nantong, Jiangsu, PR China.

Hua Wu

Xue-Lei Fu and Hua Wu, School of Medicine, Nantong University, Nantong, Jiangsu, PR China.

Hong-Lin Chen

Hong-Lin Chen, School of Public Health, Nantong University, Nantong, Jiangsu, PR China.