Influncing Factors Of Survival And Establishment Of A Three-month Mortality Model For Patients With Advanced Tumor

ObjectiveTo explore the relationship between palliative performance scale(PPS)score,PPS decline track,clinical symptoms and signs of patients and survival time,and a three-month death risk model for advanced cancer patients was initially constructed based on the palliative performance scale(PPS),which would provide a reference for the health care workers,patients and families to jointly formulate and implement the appropriate early care plan and hospice decision-making.Methods1.By consulting relevant literature and combing clinical practice,we formulated a questionnaire and retrospectively analyzed the complete clinical data of 375 patients in hospice ward of Oncology Department of Hospital from 2018 to 2020 and their follow-up data within three months.Kaplan-Meier survival curve was drawn,and the difference of survival curve among different variable groups was tested by Log-rank.Cox proportional hazard regression model was used for multivariate survival analysis to screen out the independent risk factors affecting the survival of patients with advanced cancer and constructed the PI prediction model finally.2.Patients with advanced cancer admitted to the hospice of the oncology department of the hospital from 2020 to 2021 were prospectively observed.During the study period,the PPS score at the first admission was taken as the baseline,and 3days after admission and one week after admission were used as two time cut-off points.Changes in the PPS score within a short period of time were recorded.All patients were followed up for 3 months after the start of the study with detailed records.Cox proportional risk model was used to determine the relationship between the change of PPS score at different time points and the risk ratio of survival time.Results1.After single factor analysis,the variables significantly correlated with survival were screened out,and a total of 10 influencing factors(P<0.1)were entered into the next step of stepwise regression model.The results showed that the five variables of surgical history(HR=0.709,P=0.023),PPS≤50%(HR=4.585,P<0.001),dyspnea(HR=1.642,P=0.008),dysphagia(HR=1.925,P=0.001),delirium(HR=6.317,P<0.001)enter the main effect equation finally(P<0.05).Thus,the survival PI prediction model of advanced cancer patients was established(X~2=160.096,P<0.001).The overall test of the fitting model indicated that it was statistically significant.Patients in the model group and the verification group were divided into three risk subgroups(high,medium,and low)according to PI values.Log-rank test showed that the survival rates of the groups were significantly different(P<0.05).2.In prospective studies,univariate analysis results showed that the change of PPS score at 3 days after admission was correlated with the change of PPS score at 1week after admission(P<0.05).Multivariate analysis of Cox proportional risk model showed that the change of PPS score on admission was an independent risk factor,and the change of PPS score on admission 3 days after admission and one week after admission at two time cut-off points were P<0.05.The greater the increase in PPS change score,the higher the corresponding risk rate.At 3 days of admission,the hazard ratio of"PPS score change≥20%"and"PPS score change 10%-19%"were 2times and 4 times higher than that of"PPS score change<10%"respectively;At one week of admission,the hazard ratio of"PPS score change≥20%"and"PPS score change 10%-19%"were 2.5 times and 2.8 times higher than that of"PPS score change<10%"respectively.Conclusion1.This study proved that PPS was advanced cancer patients survival prediction assessment of effective predictors,and Surgical history is a protective factor for prognosis,and PPS≤50%,dyspnea,dysphagia and delirium were risk factors.The establishment of an effective PI model based on the five indicators is of certain reference significance for clinical medical workers to make medical decisions and formulate nursing objectives.2.It also proves that PPS decline trajectory is an effective predictor of survival in patients with advanced cancer.“Sentinel events”,namely changes in PPS scores within a short period of time,also reflect the development of the disease and changes in physical state,which can provide personalized feedback for the prognosis of palliative care.