Construction Of Risk Prediction Model For Cancer-related Fatigue In Patients With Cervical Cancer And Study Of Mindfulness Based Stress Reduction Intervention

Objective:As the most common malignant tumor in women,cervical cancer has become one of the important public health problems in the world.Among them,cancer related fatigue(CRF)often runs through all stages of radio chemotherapy,chemotherapy and even hospice care for cervical cancer patients.For this reason,this study first identified the independent risk factors of severe CRF in cervical cancer patients by screening and analyzing the common related factors of CRF in cervical cancer patients,constructed a risk prediction model for severe CRF and visualized the model.Secondly,the longitudinal tracking of CRF and related psychological variables was carried out to verify the time sequence of variable occurrence,and the internal mechanism relationship between influencing factors was deeply discussed and verified to reveal the interaction mechanism and law between CRF and its influencing factors in cervical cancer patients.Finally,the 8-week mindfulness decompression training guided by We Chat video outside the hospital was used to carry out positive psychological intervention on cervical cancer patients and track the intervention effect at three different time points to explore and verify whether online 8-week mindfulness decompression training can improve the positive psychological level of cervical cancer patients and relieve CRF symptoms.This study is to offer a scientific,accurate and convenient new evaluation tool for the prediction of severe CRF,so as to help clinical workers identify high-risk groups of cervical cancer CRF as early as possible.At the same time,individual independent risk factors can provide a reference for taking targeted intervention programs,so as to strengthen the management of CRF in cervical cancer patients,and achieve the purpose of preventing the occurrence of CRF or reducing the degree of CRF in patients,which can help improve the quality of life of patients with cervical cancer.Methods:In this study,a cross-sectional survey was first conducted to collect 284cervical cancer patients from the gynecology and obstetrics department of a hospital.The first 70%of cervical cancer case data were included in the model building group(training set),and then 30%of case data entered the study were included in the validation group(validation set).The final sample size of the model building group was 196 cases,and the sample size of the validation group was 88 cases.The data of cervical cancer patients in the model construction group were used for the construction of risk assessment model and internal evaluation,and used to establish the prediction probability for patients in the validation group.Combined with the actual situation of patients in the validation group with severe CRF,ROC curve,calibration curve and DCA decision curve were drawn to complete the validation of the model.The questionnaire includes general information questionnaire,cancer related fatigue scale,disease uncertainty scale,medical coping style scale,multi-dimensional perceived social support scale and psychological consistency-13 scale.Use IBM SPSS Statistics26 for statistics and analysis;Harman single factor method was used for common method deviation test;Using single factorχ~2.Logistic binary regression analysis was used to determine the independent influencing factors of severe CRF in cervical cancer patients,and the step-down method was used to screen the optimal risk model of severe CRF in cervical cancer patients and present the model in the form of nomograms;R4.1.2 software is used to complete the construction and verification of the model.The R packages used in this study include"rms 6.3.0","Desc Tools 0.99.46","ROCit 2.1.1","Resource Selection 0.3.5",and"rmda 1.6".P<0.05 indicates that the results are statistically significant.Secondly,this study continued to carry out longitudinal follow-up survey at three time points(after treatment,3 months apart,6 months apart),and the questionnaire still used the above scale.The survey objects in this part are cervical cancer patients who participated in the cross-sectional survey in the first part.The survey forms are divided into on-site face-to-face and telephone follow-up surveys.In the first part,284 patients were included in the cross section.In this study,patients were tracked twice(3 months and 6 months),and 96 patients with cervical cancer finally completed three tracking questionnaires effectively.Two longitudinal mediation models were constructed by using the cross lag model(CLPM)to systematically investigate the longitudinal relationship between disease uncertainty,coping style,social support,and psychological consistency and CRF in cervical cancer patients.IBM SPSS 26.0 was used for data statistics and correlation analysis;Use Amos 26.0 software to test the cross lag model;The significance of the mediation effect was verified by the deviation corrected percentile Bootstrap method;Harman single factor method was used for common method deviation test,and P<0.05 indicated that the results were statistically significant.Finally,this study adopted a pilot study design,and randomly assigned the study subjects to the intervention group(N=51)and the control group(N=51)at a ratio of 1:1.For the selected intervention group,they were informed to sign an informed consent and did not communicate with the control group about the intervention content.Unify gynecologists to establish We Chat groups for patients participating in the intervention,and inform participants to click on the mobile medical mindfulness intervention We Chat official account.The patients in the control group were given routine treatment and nursing;The intervention group received 8 weeks of mindfulness decompression training.The method of mobile phone-We Chat-push official account is adopted.Each group is composed of 20-30 patients.The starting point of intervention is one week after the first enrollment.Specific intervention contents:(1)understanding mindfulness;(2)Body scan;(3)Mindfulness yoga stretching;(4)Sit still;(5)Mindful walking;(6)Meditation practice;(7)Mindfulness meditation;(8)Mindfulness Therapy.After 8 weeks of mindfulness decompression training,3 months and 6 months after training,the scores of coping styles,psychological consistency,CRF,uncertainty of disease and social support in the intervention group and the control group were measured by We Chat follow-up to evaluate the intervention effect.SPSS Statistics 26was used for data analysis;Independent sample t-test was used to compare the data between the two groups;The change trend and difference of the two groups of research data were compared by repeated measurement ANOVA,with P≤0.05 as the difference with statistical significance.Results:In the first part of the study,the incidence of severe CRF in cervical cancer patients was 46.8%.Long term passive smoking(β=1.107,OR=3.027,P=0.009),tumor recurrence(β=1.392,OR=4.022,P=0.032),coping style(β=1.028,OR=2.795,P<0.001),independent risk factors for severe CRF in cervical cancer patients,monthly income(β=-0.446,OR=0.640,P=0.040),exercise(β=-0.810,OR=0.445,P=0.003),social support(β=-0.823,OR=0.439,P=0.015)Psychological consistency(β=-2.498,OR=0.082,P<0.001)was a protective factor for severe CRF in patients with cervical cancer.C-Index of nomogram model is 0.921(95%CI:0.877～0.958);It can be seen from the ROC curve that the best cut-off value of the prediction probability of the nomogram model in the construction group is 0.412,which corresponds to the maximum Jordan index of 0.721.At this time,the sensitivity of the model is 0.821,the specificity is 0.900,and the accuracy is 0.857;AUC is 0.916(95%CI:0.876～0.957);Hosmer Lemeshow verification shows thatχ~2=9.021,P=0.340,greater than 0.05,indicating that the model has a high degree of discrimination.In the validation group,the AUC of the area under the ROC curve is 0.928(0.876～0.980),and the best cut-off value of the prediction probability of the nomogram model is 0.444,corresponding to the maximum Yoden index of 0.748.At this time,the sensitivity of the model is 0.889,the specificity is 0.860,and the accuracy is 0.875;The calibration curve has good consistency(χ~2=8.89,P=0.340>0.05),indicating that the model has good clinical practicability.The results of the second part showed that the total effect of disease uncertainty in T1 stage→T3 cancer-related fatigue was 0.418(P<0.01);After adding the T2 face,the direct effect of T1 disease uncertainty→T3 cancer-related fatigue was 0.315(P<0.01).The indirect effect of disease uncertainty in T1 stage→face in T2 stage→cancer-related fatigue in T3 stage was 0.103(P<0.01),and the intermediary effect was significant.The total effect of T1 stage disease uncertainty→T3 cancer-related fatigue was 0.419(P<0.01);After the avoidance of T2 was added,the direct effect of disease uncertainty in T1→cancer related fatigue in T3 was 0.429(P<0.01);The indirect effect of disease uncertainty in T1 stage→avoidance in T2 stage→cancer-related fatigue in T3 stage was-0.010(P>0.05),and the intermediary effect was not significant.The total effect of T1 stage disease uncertainty→T3 cancer-related fatigue was 0.406(P<0.01);After adding the yielding of T2 stage,the direct effect of disease uncertainty in T1 stage→T3 cancer-related fatigue was 0.303(P<0.01);The indirect effect of disease uncertainty in T1 stage→yielding in T2 stage→cancer-related fatigue in T3 stage was 0.104(P<0.01),and the intermediary effect was significant.The total effect of perceived social support→T3 cancer-related fatigue in T1 stage was-0.282(P<0.01);After adding the sense of psychological consistency in T2,the direct effect of perceived social support in T1→T3 cancer-related fatigue was-0.173(P>0.05);The indirect effect of perceived social support in T1 stage→psychological consistency in T2 stage→cancer-related fatigue in T3 stage was-0.109(P<0.01),and the intermediary effect was significant.The results of the third part showed that for the sense of psychological consistency,there was a statistically significant difference between the sense of psychological consistency after the intervention and that before the intervention in the control group(P<0.001);However,the psychological consistency of the experimental group after intervention,at 3-month follow-up and 6-month follow-up showed an upward trend compared with that before intervention,with a statistically significant difference(P<0.001).In terms of coping style,the face scores of the experimental group after intervention,at 3-month follow-up and 6-month follow-up showed an upward trend compared with those before intervention,with a statistically significant difference(P<0.001);The yield score of the experimental group after intervention,at the time of 3-month follow-up and 6-month follow-up showed a downward trend compared with that before intervention(P<0.001).For CRF,there was a statistically significant difference(P=0.002)between the CRF value at the 3-month follow-up in the control group and that before the intervention;The CRF value of the experimental group after intervention,at the time of 3-month follow-up and 6-month follow-up showed a downward trend compared with that before intervention,with a statistically significant difference(P<0.001).For social support,in the control group,the simple effect of measurement times was not significant(P>0.05),while in the experimental group,the simple effect of measurement times was not significant(P>0.05).For the sense of disease uncertainty,the score of the control group showed a downward trend after the intervention(P<0.001),and an upward trend at 3 and 6 months(P>0.05);The disease uncertainty score of the experimental group after intervention showed a significant downward trend compared with that before intervention(P<0.001),and showed an upward trend at 3 and 6 months(P>0.05).Conclusion:The prediction model for severe CRF risk of cervical cancer patients constructed in this study has good accuracy,differentiation and clinical practicability,which can be considered as a tool for clinical prediction of severe CRF of cervical cancer patients,to help clinical workers identify high-risk groups of CRF as early as possible,and at the same time,individual independent risk factors can provide reference for taking targeted intervention programs,so as to strengthen the management of CRF of cervical cancer patients,To prevent the occurrence of severe CRF or reduce the degree of CRF in patients.The disease uncertainty of cervical cancer patients can directly affect cancer-related fatigue,and can also indirectly affect cancer-related fatigue through coping styles;Perceived social support of cervical cancer patients indirectly affects cancer-related fatigue mainly through psychological consensus.At the same time,online 8-week mindfulness decompression training can effectively improve the psychological consistency,coping style and CRF of cervical cancer patients,and the positive effect of the intervention can last up to 6 months.It can also effectively improve the disease uncertainty of cervical cancer patients,but the intervention effect is not sustainable,only significant after the intervention.Clinical medical staff and main family caregivers can properly consider strengthening positive psychological intervention to improve the positive psychological level of patients,reduce their uncertainty about disease,promote their psychological consistency or improve their coping style,thereby reducing cancer-related fatigue of patients.