Prognostic Prediction Model Study Of Aplastic Anemia Based On Tertiary Prevention Theory

Objective:This study aimed to identify the risk factors associated with prognosis and occurrence of infection in aplastic anemia patients and further used logistic regression to develop a risk prediction model for poor prognosis after transplantation in these patients,in order to provide reference for the tertiary prevention and individualized diagnosis and treatment of aplastic anemia,and promote early detection and intervention in high-risk groups,so as to improve the quality of patient’s life and reduce medical costs.Methods:This study was divided into two parts:Firstly,we conducted a systematic search of electronic medical literature databases using a well-designed search strategy with inclusion and exclusion criteria,to obtain relevant studies on the prognosis and risk factors of infection in patients with aplastic anemia.Relevant data were extracted,then,a systematic review and meta-analysis was performed.Secondly,the prognostic factors of aplastic anemia obtained from the meta-analysis were used as dependent variables in exploratory analysis to build reliable model based on data of patients with aplastic anemia obtained from BioLINCC.Finally,data from clinical records of MIMIC-Ⅳ were extracted and analyzed to test the established model.Results:A total of 34 studies were included for meta-analysis of prognostic factors in patients with aplastic anemia.Among patients who received transplantation,12 important factors were identified which included:patient age,acute graft-versus-host disease,human leukocyte antigen matching,peripheral blood hematopoietic stem cell transplantation,graft failure,year of transplantation,recipients’ preoperative CMV infection status,donor-recipient relationship,Eastern Cooperative Oncology Group score,hematopoietic stem cell transplantation comorbidity index,karnofsky performance score,and CD34 cell input.The pooled hazard ratios(HRs)were:1.77,2.58,2.25,1.98,8.25,0.59,2.12,1.87,8.13,2.13,0.64,2.63,respectively.A total of 10 studies were included in the systematic review and meta-analysis of influencing factors of infection in aplastic anemia patients.8 important risk factors were identified:age,duration of hospital-stay,duration of granulocyte deficiency,neutrophil count,albumin count,invasive procedures,comorbidities,and antimicrobial use.The pooled odds ratios(ORS)were 2.33,1.93,1.27,2.65,0.90,4.72,5.18,and 3.98,respectively.Multiple logistic regression analysis confirmed the association between three risk factors(age,transplant outcome,and number of infections)and poor prognosis in patients with aplastic anemia.Based on these risk factors,a prognosis prediction model for aplastic anemia was established and a nomograph was drawn to predict whether patients with aplastic anemia have higher risk of poor prognosis.The specific formula was Logit(P)=-3.485+0.041*Age(years)+1.906*Transplant failure+0.228*Number(frequency)of infections.The area under the curve of the regression model was 0.791,which meant the prediction effect was good.In addition,external validation confirmed that the model could effectively predict the risk of poor prognosis in transplant recipients of aplastic anemia,and also confirmed the important clinical significance of the model.Conclusion:This study provided a comprehensive evaluation(systematic review and meta-analysis)of relevant studies on prognostic factors for aplastic anemia.A prognosis prediction model for aplastic anemia with a good prognostic effect was established.This helps in prediction of individuals with aplastic anemia and evidence-based clinical prevention and intervention of the disease,thus contributing new ideas and directions for the development of other prognostic prediction models.