Michael Downing

A reliability and validity study of the Palliative Performance Scale

BackgroundThe Palliative Performance Scale (PPS) was first introduced in1996 as a new tool for measurement of performance status in palliative care. PPS has been used in many countries and has been translated into other languages.MethodsThis study evaluated the reliability and validity of PPS. A web-based, case scenarios study with a test-retest format was used to determine reliability. Fifty-three participants were recruited and randomly divided into two groups, each evaluating 11 cases at two time points. The validity study was based on the content validation of 15 palliative care experts conducted over telephone interviews, with discussion on five themes: PPS as clinical assessment tool, the usefulness of PPS, PPS scores affecting decision making, the problems in using PPS, and the adequacy of PPS instruction.ResultsThe intraclass correlation coefficients for absolute agreement were 0.959 and 0.964 for Group 1, at Time-1 and Time-2; 0.951 and 0.931 for Group 2, at Time-1 and Time-2 respectively. Results showed that the participants were consistent in their scoring over the two times, with a mean Cohens kappa of 0.67 for Group 1 and 0.71 for Group 2. In the validity study, all experts agreed that PPS is a valuable clinical assessment tool in palliative care. Many of them have already incorporated PPS as part of their practice standard.ConclusionThe results of the reliability study demonstrated that PPS is a reliable tool. The validity study found that most experts did not feel a need to further modify PPS and, only two experts requested that some performance status measures be defined more clearly. Areas of PPS use include prognostication, disease monitoring, care planning, hospital resource allocation, clinical teaching and research. PPS is also a good communication tool between palliative care workers.

Use of the Palliative Performance Scale (PPS) for End-of-Life Prognostication in a Palliative Medicine Consultation Service

This study examines the use of the Palliative Performance Scale (PPS) in end-of-life prognostication within a regional palliative care program in a Canadian province. The analysis was done on a prospective cohort of 513 patients assessed by a palliative care consult team as part of an initial community/hospital-based consult. The variables used were initial PPS score, age, gender, diagnosis, cancer type, and survival time. The findings revealed initial PPS to be a significant predictor of survival, along with age, diagnosis, cancer type and site, but not gender. The survival curves were distinct for PPS 10%, 20%, and 30% individually, and for 40%-60% and > or =70% as bands. This is consistent with earlier findings of the ambiguity and difficulty when assessing patients at higher PPS levels because of the subjective nature of the tool. We advocate the use of median survival and survival rates based on a local cohort where feasible, when reporting individual survival estimates.

Correlation between Braden Scale and Palliative Performance Scale in advanced illness

This study describes the significant correlation between the Braden Scale (BS) and the Palliative Performance Scale (PPS) in patients with advanced illness that has not been previously reported. The analysis was based on a prospective sequential case series of 664 patients suffering from advanced illness who were referred to a regional palliative medicine programme in Toronto, Canada. Baseline BS and PPS scores assessed within 24 hours of referral were considered for analysis. After controlling for age, gender, consult site and diagnosis (cancer versus non cancer), we observed a significant positive correlation between baseline PPS and BS scores (r = 0·885, P < 0·001). These findings suggest that for patients with advanced illness where BS is not routinely used, PPS could be considered as a proxy for pressure ulcer risk assessment.

A joint model for interval-censored functional decline trajectories under informative observation.

Multi-state models are useful for modelling disease progression where the state space of the process is used to represent the discrete disease status of subjects. Often, the disease process is only observed at clinical visits, and the schedule of these visits can depend on the disease status of patients. In such situations, the frequency and timing of observations may depend on transition times that are themselves unobserved in an interval-censored setting. There is a potential for bias if we model a disease process with informative observation times as a non-informative observation scheme with pre-specified examination times. In this paper, we develop a joint model for the disease and observation processes to ensure valid inference because the follow-up process may itself contain information about the disease process. The transitions for each subject are modelled using a Markov process, where bivariate subject-specific random effects are used to link the disease and observation models. Inference is based on a Bayesian framework, and we apply our joint model to the analysis of a large study examining functional decline trajectories of palliative care patients.