Validation and Adaptation of the Multidimensional Prognostic Index in an Older Australian Cohort

Abstract

Background and aims: The Multidimensional Prognostic Index (MPI), an objective and quantifiable tool based on the Comprehensive Geriatric Assessment, has been shown to predict adverse outcomes in European cohorts. We conducted a validation study of the original MPI, and of adapted versions that accounted for the use of specific drugs and cultural diversity in the assessment of cognition, in older Australians. Methods: The capacity of the MPI to predict 12-month mortality was assessed in 697 patients (median age: 80 years; interquartile range: 72–86) admitted to a metropolitan teaching hospital between September 2015 and February 2017. Results: In simple logistic regression analysis, the MPI was associated with 12-month mortality (Low risk: OR reference group; moderate risk: OR 2.50, 95% CI: 1.67–3.75; high risk: OR 4.24, 95% CI: 2.28–7.88). The area under the receiver operating characteristic curve (AUC) for the unadjusted MPI was 0.61 (0.57–0.65) and 0.64 (95% CI: 0.59–0.68) with age and sex adjusted. The adapted versions of the MPI did not significantly change the AUC of the original MPI. Conclusion: The original and adapted MPI were strongly associated with 12-month mortality in an Australian cohort. However, the discriminatory performance was lower than that reported in European studies.

Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study

“…The prediction accuracy using the MPI categories and the test data set (AUC=0.632) was very similar to the poor accuracy obtained previously with follow-up on only 697 of the same patients (AUC=0.62), in which all records were used for assessing prediction accuracy rather than using separate training and testing data sets [ 5 ]. However, the higher accuracy obtained using the eight individual component features of the MPI combined with clinical data led to an accuracy similar to that originally reported for the three-category MPI within the original Italian MPI cohort [ 2 ].…”

“…Details of the data collection methods, including a description of the study design, study cohort, and collected data, have been previously published [ 5 ]. Briefly, the cohort consisted of patients aged 65 years and above admitted to the Flinders Medical Centre Acute Medical Unit and then transferred to either the general medical or acute care of the elderly wards between September 14, 2015, and February 17, 2017.…”

“…Prediction accuracy for 12-month mortality (12MM) using the area under the receiver operating curve (AUC) of 0.751 was achieved with the three MPI categories when validated in an older Italian population [ 2 ]. However, despite it being a significant predictor of 12MM in a similar older hospital population within Australia [ 5 ], its diagnostic accuracy was not confirmed (AUC=0.64, with age and gender adjustment). The relatively poor performance for prediction compared with the prediction accuracy with the Italian cohort might be partly explained by the homogenization of scores from the separate MPI domains into a single aggregate-weighted scoring system.…”

Predictors of short- and long-term mortality among acutely admitted older patients: role of inflammation and frailty

“…A minimum required sample size of 442–448 patients was calculated to detect, with a probability of a type I error of 0.05 and a type II error of 0.2, a 1-year mortality rate difference between MPI severe- and moderate-risk groups of approximately 30%, according to previous literature [ 14 ].…”

“…In addition to frailty, a cluster of clinical and demographic factors including age and sex is associated with poor prognosis and mortality in elderly patients [7][8][9][10][11][12]. Although studies demonstrated an increased prognostic value of MPI according to sex and older age [13,14], at present these factors are not included in this tool. Among clinical factors, systemic inflammation correlates with important clinical outcomes in older patients acutely hospitalized, including mortality, duration of hospital stay and nonelective readmissions [15].…”