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PROgnostic Model for Advanced Cancer (PRO-MAC).

Allyn Hum1,2, Yoko Kin Yoke Wong3, Choon Meng Yee1,2

  • 1Palliative Care Centre for Excellence in Research and Education, Singapore.

BMJ Supportive & Palliative Care
|April 6, 2019
PubMed
Summary
This summary is machine-generated.

A new prognostic model, PRO-MAC, accurately predicts survival for advanced cancer patients using functional status and symptom data. This tool aids physicians in early identification of high-risk individuals for timely supportive care.

Keywords:
advanced cancerpalliative careprediction model

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Area of Science:

  • Oncology
  • Palliative Care
  • Biostatistics

Background:

  • Advanced cancer patients require accurate survival prediction for timely care planning.
  • Existing prognostic tools may not fully capture the complexity of advanced cancer prognosis.
  • Early identification of high-risk patients is crucial for optimizing supportive and palliative interventions.

Purpose of the Study:

  • To develop and validate a simple prognostic tool for early survival prediction in advanced cancer patients.
  • To identify key predictors of survival in a tertiary care setting.
  • To create a model that facilitates early identification of patients needing enhanced supportive care.

Main Methods:

  • Prospective cohort study with 2 years of follow-up involving 840 advanced cancer patients.
  • Data randomly split into training (n=560) and validation (n=280) sets.
  • Cox regression modeling used to develop the PROgnostic Model for Advanced Cancer (PRO-MAC), incorporating functional status (Palliative Performance Scale, PPS V.2), symptoms (Edmonton Symptom Assessment System, ESASr), clinical factors, and demographics.

Main Results:

  • The PRO-MAC model demonstrated good predictive accuracy, with an area under the receiver operating characteristic curve between 0.69 and 0.75.
  • The model stratified patients into three risk groups with distinct median survival times: low-risk (79 days), medium-risk (42 days), and high-risk (15 days).
  • Key predictors included Palliative Performance Scale (PPS V.2) and Edmonton Symptom Assessment System (ESASr) scores.

Conclusions:

  • The PRO-MAC tool effectively predicts 90-day mortality in advanced cancer patients.
  • PRO-MAC integrates patient and disease factors to aid physicians in early risk stratification.
  • This model supports timely initiation of supportive care and facilitates multidisciplinary decision-making.