Construction and evaluation of clinical predictive model of stigma in patients with lymphoma
10.3760/cma.j.cn115682-20200228-01164
- VernacularTitle:淋巴瘤患者病耻感临床预测模型的构建与评估
- Author:
Kejin LI
1
;
Jianmei ZHOU
;
Aifeng MENG
;
Jianhong LIU
;
Lagen LIU
;
Xiaoxu ZHI
;
Min LI
Author Information
1. 江苏省肿瘤医院内科，南京 210009
- Keywords:
Lymphoma;
Stigma;
Quality of life;
Predictors
- From:
Chinese Journal of Modern Nursing
2020;26(28):3862-3868
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish and evaluate the clinical prediction model of stigma in patients with lymphoma so as to provide a basis for the assessment and response of stigma in patients with lymphoma.Methods:Convenience sampling method was used to select 130 patients with lymphoma who were hospitalized in Jiangsu Cancer Hospital from June to December 2019. We collected patients' clinical data, and assessed patients' quality of life and stigma. The R software was used to analyze and process the data, and screened characteristic factors were predicted by combining with the LASSO regression model. Multivariate Logistic regression analysis was used to analyze the influencing factors of stigma in patients with lymphoma. We constructed a nomogram model to evaluate the identification, calibration and clinical applicability of the predictive model through C index, calibration chart and decision curve analysis.Results:A total of 120 patients' valid data were gathered. Patients with lymphoma had a high level of stigma. The predictive factors of the predictive model included whether to be hospitalized for the first time, age, patient's medical insurance type, scores of the thirtieth and twenty-seventh question of the quality of life questionnaire. The model showed good predictive ability. The C index of training group, overall sample and validation group were 0.824, 0.776 and 0.684 respectively, and the C index performed well.Conclusions:The nomogram model developed in this research can help clinical nurses early identify lymphoma patients with a high level stigma, and give targeted response plans, which can greatly improve the quality of life and prognosis of patients, and is worthy of clinical application.
