BACKGROUND: The Prognosis in Palliative care Study (PiPS) prognostic survival models predict survival in patients with incurable cancer. PiPS-A (Prognosis in Palliative care Study - All), which involved clinical observations only, and PiPS-B (Prognosis in Palliative care Study - Blood), which additionally required blood test results, consist of 14- and 56-day models that combine to create survival risk categories: 'days', 'weeks' and 'months+'. OBJECTIVES: The primary objectives were to compare PIPS-B risk categories against agreed multiprofessional estimates of survival and to validate PiPS-A and PiPS-B. The secondary objectives were to validate other prognostic models, to assess the acceptability of the models to patients, carers and heal...
Background Prognostic accuracy in palliative care is valued by patients, carers, and healthcare prof...
Introduction Clinicians often struggle to recognise when palliative care patients are imminently dyi...
Copyright © Author(s) (or their employer(s)) 2019. Introduction Clinicians often struggle to recogni...
BACKGROUND: More accurate methods of prognostication are likely to lead to improvements in the quali...
OBJECTIVE: To develop a novel prognostic indicator for use in patients with advanced cancer that is ...
BackgroundPrognosis in Palliative care Study (PiPS) models predict survival probabilities in advance...
Abstract Background More accurate methods of prognostication are likely to lead to improvements in t...
BACKGROUND: Prognostic information is important for patients with cancer, their families, and clinic...
Background: The Prognosis in Palliative care Scale (PiPS) predicts survival in advanced cancer patie...
Objectives: The Prognosis in Palliative care Study II (PiPS2) was a large multicentre observational ...
BACKGROUND: In patients with advanced cancer, prognosis is usually determined using clinicians' pred...
Background - Prognostic accuracy in palliative care is valued by patients, carers, and healthcare pr...
Background: Prognosis in Palliative Care Study (PiPS) predictor models were developed in 2011 to est...
AbstractBackgroundThe hospice movement has provided an excellent model of specialist palliative care...
BACKGROUND: Prognostic accuracy in palliative care is valued by patients, carers, and healthcare pro...
Background Prognostic accuracy in palliative care is valued by patients, carers, and healthcare prof...
Introduction Clinicians often struggle to recognise when palliative care patients are imminently dyi...
Copyright © Author(s) (or their employer(s)) 2019. Introduction Clinicians often struggle to recogni...
BACKGROUND: More accurate methods of prognostication are likely to lead to improvements in the quali...
OBJECTIVE: To develop a novel prognostic indicator for use in patients with advanced cancer that is ...
BackgroundPrognosis in Palliative care Study (PiPS) models predict survival probabilities in advance...
Abstract Background More accurate methods of prognostication are likely to lead to improvements in t...
BACKGROUND: Prognostic information is important for patients with cancer, their families, and clinic...
Background: The Prognosis in Palliative care Scale (PiPS) predicts survival in advanced cancer patie...
Objectives: The Prognosis in Palliative care Study II (PiPS2) was a large multicentre observational ...
BACKGROUND: In patients with advanced cancer, prognosis is usually determined using clinicians' pred...
Background - Prognostic accuracy in palliative care is valued by patients, carers, and healthcare pr...
Background: Prognosis in Palliative Care Study (PiPS) predictor models were developed in 2011 to est...
AbstractBackgroundThe hospice movement has provided an excellent model of specialist palliative care...
BACKGROUND: Prognostic accuracy in palliative care is valued by patients, carers, and healthcare pro...
Background Prognostic accuracy in palliative care is valued by patients, carers, and healthcare prof...
Introduction Clinicians often struggle to recognise when palliative care patients are imminently dyi...
Copyright © Author(s) (or their employer(s)) 2019. Introduction Clinicians often struggle to recogni...