Prognostic models for survival predictions in advanced cancer patients: a systematic review and meta-analysis
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View abstract on PubMed
Summary
This summary is machine-generated.This systematic review found that the Palliative Prognostic Score (PaP) may be a useful tool for predicting survival in advanced cancer patients. Further research is needed to confirm its effectiveness for palliative care planning.
Area Of Science
- Oncology
- Palliative Care
- Biostatistics
Background
- Accurate prognostication is vital for palliative care (PC) planning in advanced cancer.
- Clinical point-of-care prognostic models can aid clinician decision-making.
- Timely PC referral impacts patient outcomes but varies in practice.
Purpose Of The Study
- To systematically review and meta-analyze prognostic models for advanced cancer survival.
- To identify and evaluate the performance of various clinical prognostic tools.
- To inform the selection of models for palliative care decision support.
Main Methods
- Systematic literature search across major databases (Ovid Medline, Embase, CINAHL Ultimate, Scopus).
- Inclusion criteria: incurable solid tumors, prognostic model validation, performance measurement.
- Risk of bias assessed using PROBAST; meta-analysis of pooled C-statistics for survival prediction.
Main Results
- 35 studies evaluated 35 prognostic models; Palliative Prognostic Index (PPI), Palliative Prognostic Score (PaP), and Objective Prognostic Score (OPS) were common.
- Pooled C-statistics for 30-day survival: PPI=0.68, PaP=0.76, OPS=0.69.
- PaP showed higher pooled C-statistics for 21-day (0.80) and 30-day (0.76) survival prediction.
- All included studies exhibited a high risk of bias.
Conclusions
- The Palliative Prognostic Score (PaP) demonstrates promising performance for survival prognostication.
- Further validation and implementation studies are necessary.
- High risk of bias in current studies necessitates cautious interpretation.
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