Format

Send to

Choose Destination
Support Care Cancer. 2019 Mar 13. doi: 10.1007/s00520-019-04727-y. [Epub ahead of print]

Prognostication in advanced cancer: update and directions for future research.

Author information

1
Department of Palliative Care, Rehabilitation and Integrative Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1414, Houston, TX, 77030, USA. dhui@mdanderson.org.
2
Department of Clinical Oncology, Barretos Cancer Hospital, Barretos, SP, Brazil.
3
Division of Hematology/Oncology and Palliative Care, Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA.
4
Border Medical Oncology, Albury Wodonga Regional Cancer Centre, Albury, NSW, 2640, Australia.
5
UNSW Rural Clinical School, Albury Campus, Albury, 2640, Australia.
6
Department of Palliative Care, Rehabilitation and Integrative Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1414, Houston, TX, 77030, USA.
7
Department of Pediatric Oncology, Emma Children's Hospital, Academic Medical Center, Amsterdam, The Netherlands.
8
Institut CatalĂ  d'Oncologia - ICO, Nursing University of Barcelona, Barcelona, Spain.
9
Department of Palliative and Supportive Care, Palliative Care Team and Seirei Hospice, Seirei Mikatahara General Hospital, Shizuoka, Japan.
10
Department of Family Medicine, Dongguk University Ilsan Hospital, Goyang, South Korea, Department of Medicine, School of Medicine, Dongguk University, Seoul, South Korea.

Abstract

The objective of this review is to provide an update on prognostication in patients with advanced cancer and to discuss future directions for research in this field. Accurate prognostication of survival for patients with advanced cancer is vital, as patient life expectancy informs many important personal and clinical decisions. The most common prognostic approach is clinician prediction of survival (CPS) using temporal, surprise, or probabilistic questions. The surprise and probabilistic questions may be more accurate than the temporal approach, partly by limiting the time frame of prediction. Prognostic models such as the Glasgow Prognostic Score (GPS), Palliative Performance Scale (PPS), Palliative Prognostic Score (PaP), Palliative Prognostic Index (PPI), or Prognosis in Palliative Care Study (PiPS) predictor model may augment CPS. However, care must be taken to select the appropriate tool since prognostic accuracy varies by patient population, setting, and time frame of prediction. In addition to life expectancy, patients and caregivers often desire that expected treatment outcomes and bodily changes be communicated to them in a sensible manner at an appropriate time. We propose the following 10 major themes for future prognostication research: (1) enhancing prognostic accuracy, (2) improving reliability and reproducibility of prognosis, (3) identifying the appropriate prognostic tool for a given setting, (4) predicting the risks and benefits of cancer therapies, (5) predicting survival for pediatric populations, (6) translating prognostic knowledge into practice, (7) understanding the impact of prognostic uncertainty, (8) communicating prognosis, (9) clarifying outcomes associated with delivery of prognostic information, and (10) standardizing prognostic terminology.

KEYWORDS:

Cancer; Clinical decision-making; Prognostication; Survival

PMID:
30863893
DOI:
10.1007/s00520-019-04727-y

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center