Prognostic tools for survival prediction in advanced cancer patients: A systematic review
- PMID: 33973382
- DOI: 10.1111/1754-9485.13185
Prognostic tools for survival prediction in advanced cancer patients: A systematic review
Abstract
Survival prediction for palliative cancer patients by physicians is often optimistic. Patients with a very short life expectancy (<4 weeks) may not benefit from radiation therapy (RT), as the time to maximal symptom relief after treatment can take 4-6 weeks. We aimed to identify a prognostic tool (or tools) to predict survival of less than 4 weeks and less than 3 months in patients with advanced cancer to guide the choice of radiation dose and fractionation. We searched Embase, Medline (EBSCOhost) and CINAHL (EBSCOhost) clinical databases for literature published between January 2008 and June 2018. Seventeen studies met the inclusion criteria and were included in the review. Prediction accuracy at less than 4 weeks and less than 3 months were compared across the prognostic tools. Reporting of prediction accuracy among the different studies was not consistent: the Palliative Prognostic Score (PaP), Palliative Prognostic Index (PPI) and Number of Risk Factors (NRF) best-predicted survival duration of less than 4 weeks. The PPI, performance status with Palliative Prognostic Index (PS-PPI), NRF and Survival Prediction Score (SPS) may predict 3-month survival. We recommend PPI and PaP tools to assess the likelihood of a patient surviving less than 4 weeks. If predicted to survive longer and RT is justified, the NRF tool could be used to determine survival probability less than 3 months which can then help clinicians select dose and fractionation. Future research is needed to verify the reliability of survival prediction using these prognostic tools in a radiation oncology setting.
Keywords: life expectancy; palliative care; prognosis; radiation treatment; systematic review.
© 2021 The Royal Australian and New Zealand College of Radiologists.
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References
-
- Jones JA, Lutz ST, Chow E, Johnstone PA. Palliative radiotherapy at the end of life: a critical review. CA Cancer J Clin 2014; 64: 295-310.
-
- Chen ATC, Mauro GP, Gabrielli F et al. PROGRAD - an observational study of the prognosis of inpatients evaluated for palliative radiotherapy. Radiother Oncol 2018; 127: 299-303.
-
- Krishnan MS. Issues in supportive and palliative radiation oncology. In: Krishnan MS, Racsa M, Yu H-HM (eds). Handbook of Supportive and Palliative Radiation Oncology. Academic Press, Boston, 2017; 12.
-
- Kress M-AS, Jensen RE, Tsai H-T, Lobo T, Satinsky A, Potosky AL. Radiation therapy at the end of life: a population-based study examining palliative treatment intensity. Radiat Oncol 2015; 10: 15.
-
- Chow E, Harris K, Fan G, Tsao M, Sze WM. Palliative radiotherapy trials for bone metastases: a systematic review. J Clin Oncol 2007; 25: 1423-36.
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