Prognostic models of survival in patients with advanced incurable cancer: the PiPS2 observational study

Health Technol Assess. 2021 May;25(28):1-118. doi: 10.3310/hta25280.

Abstract

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 health-care professionals and to identify barriers to and facilitators of clinical use.

Design: This was a national, multicentre, prospective, observational, cohort study with a nested qualitative substudy using interviews with patients, carers and health-care professionals.

Setting: Community, hospital and hospice palliative care services across England and Wales.

Participants: For the validation study, the participants were adults with incurable cancer, with or without capacity to consent, who had been recently referred to palliative care services and had sufficient English language. For the qualitative substudy, a subset of participants in the validation study took part, along with informal carers, patients who declined to participate in the main study and health-care professionals.

Main outcome measures: For the validation study, the primary outcomes were survival, clinical prediction of survival and PiPS-B risk category predictions. The secondary outcomes were predictions of PiPS-A and other prognostic models. For the qualitative substudy, the main outcomes were participants' views about prognostication and the use of prognostic models.

Results: For the validation study, 1833 participants were recruited. PiPS-B risk categories were as accurate as agreed multiprofessional estimates of survival (61%; p = 0.851). Discrimination of the PiPS-B 14-day model (c-statistic 0.837, 95% confidence interval 0.810 to 0.863) and the PiPS-B 56-day model (c-statistic 0.810, 95% confidence interval 0.788 to 0.832) was excellent. The PiPS-B 14-day model showed some overfitting (calibration in the large -0.202, 95% confidence interval -0.364 to -0.039; calibration slope 0.840, 95% confidence interval 0.730 to 0.950). The PiPS-B 56-day model was well-calibrated (calibration in the large 0.152, 95% confidence interval 0.030 to 0.273; calibration slope 0.914, 95% confidence interval 0.808 to 1.02). PiPS-A risk categories were less accurate than agreed multiprofessional estimates of survival (p < 0.001). The PiPS-A 14-day model (c-statistic 0.825, 95% confidence interval 0.803 to 0.848; calibration in the large -0.037, 95% confidence interval -0.168 to 0.095; calibration slope 0.981, 95% confidence interval 0.872 to 1.09) and the PiPS-A 56-day model (c-statistic 0.776, 95% confidence interval 0.755 to 0.797; calibration in the large 0.109, 95% confidence interval 0.002 to 0.215; calibration slope 0.946, 95% confidence interval 0.842 to 1.05) had excellent or reasonably good discrimination and calibration. Other prognostic models were also validated. Where comparisons were possible, the other prognostic models performed less well than PiPS-B. For the qualitative substudy, 32 health-care professionals, 29 patients and 20 carers were interviewed. The majority of patients and carers expressed a desire for prognostic information and said that PiPS could be helpful. Health-care professionals said that PiPS was user friendly and may be helpful for decision-making and care-planning. The need for a blood test for PiPS-B was considered a limitation.

Limitations: The results may not be generalisable to other populations.

Conclusions: PiPS-B risk categories are as accurate as agreed multiprofessional estimates of survival. PiPS-A categories are less accurate. Patients, carers and health-care professionals regard PiPS as potentially helpful in clinical practice.

Future work: A study to evaluate the impact of introducing PiPS into routine clinical practice is needed.

Trial registration: Current Controlled Trials ISRCTN13688211.

Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 28. See the NIHR Journals Library website for further project information.

Keywords: CAREGIVERS; DECISION-MAKING; HOSPICES; NEOPLASMS; PALLIATIVE CARE; PROGNOSIS; PROSPECTIVE STUDIES; QUALITATIVE RESEARCH.

Plain language summary

A prognosis is a prediction about how long someone will live after a diagnosis of illness. The Prognosis in Palliative care Study (PiPS) tools [PiPS-A (Prognosis in Palliative care Study – All) and PiPS-B (Prognosis in Palliative care Study – Blood), respectively] were designed to predict survival in patients with incurable cancer. Previously, they were found to be as accurate as health-care professionals. The purpose of this study was to find out whether PiPS was more accurate at prognosticating than health-care professionals, to evaluate other prognostic tools and to ask patients, their carers and health-care professionals what they thought about using them. We studied 1833 patients with advanced cancer and calculated their PiPS score and other prognostic scores. We asked health-care professionals to estimate how long the patients would live. We then followed up the patients to find out how long they actually lived and if the predictions made by health-care professionals were as accurate as the predictions made by the prognostic tools. We interviewed patients, their carers and health-care professionals to ask them what they thought about using these prognostic tools. We found that PiPS-B was as accurate as the combined wisdom of a doctor and a nurse at predicting whether patients would live for ‘days’, ‘weeks’ or ‘months+’. We found that PiPS-A predictions were not as accurate as predictions made by health-care professionals. We found that (where direct comparisons could be made) PiPS-B was better than other prognostic tools. Finally, we found that patients, carers and health-care professionals thought that PiPS tools could be helpful in clinical practice because they would be less subjective than clinicians’ intuition. This means that PiPS-B could be considered as a tool to support clinician predictions of survival and may lead to patients and families being able to take more control at the end of their lives. Further research will be required to investigate whether or not this approach actually leads to improvements in care.

Publication types

  • Multicenter Study
  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Caregivers*
  • Cohort Studies
  • Humans
  • Neoplasms* / therapy
  • Prognosis
  • Prospective Studies

Associated data

  • ISRCTN/ISRCTN13688211