Literature DB >> 17043092

Predicting prognosis in patients with advanced cancer.

P C Stone1, S Lund.   

Abstract

BACKGROUND: Patients with advanced cancer and their carers frequently wish to know how long they can expect to live. Improved prognostication would enable patients and their carers to be better prepared for their impending death, and would allow clinicians to make better informed decisions about place of care. However, clinician estimates of survival are inaccurate and systematically overoptimistic. Recently, attempts have been made to improve upon clinician estimates of survival by devising prognostic scales incorporating clinical information with biochemical and haematological results.
DESIGN: A descriptive and critical review of palliative prognostic scales, on the basis of the recommendations of the European Association of Palliative Care prognosis working group (2005) supplemented by an Ovid Medline search 1966-March 2006 using the key words 'prognosis', 'neoplasms', 'palliative care' and 'terminal care'.
RESULTS: This paper reviews the advantages and limitations of the palliative prognostic score, the palliative prognostic index, the Chuang prognostic scale, the terminal cancer prognostic score and the poor prognostic indicator.
CONCLUSIONS: All the currently available prognostic scales have limitations, but nonetheless offer an improvement on unadjusted clinician estimates of survival. Further research is required to systematically develop a prognostic scale on the basis of all the known prognostic variables in patients with advanced cancer.

Entities:  

Mesh:

Year:  2006        PMID: 17043092     DOI: 10.1093/annonc/mdl343

Source DB:  PubMed          Journal:  Ann Oncol        ISSN: 0923-7534            Impact factor:   32.976


  37 in total

1.  Prospective comparison of prognostic scores in palliative care cancer populations.

Authors:  Marco Maltoni; Emanuela Scarpi; Cristina Pittureri; Francesca Martini; Luigi Montanari; Elena Amaducci; Stefania Derni; Laura Fabbri; Marta Rosati; Dino Amadori; Oriana Nanni
Journal:  Oncologist       Date:  2012-02-29

2.  A Framework to Improve Surgeon Communication in High-Stakes Surgical Decisions: Best Case/Worst Case.

Authors:  Lauren J Taylor; Michael J Nabozny; Nicole M Steffens; Jennifer L Tucholka; Karen J Brasel; Sara K Johnson; Amy Zelenski; Paul J Rathouz; Qianqian Zhao; Kristine L Kwekkeboom; Toby C Campbell; Margaret L Schwarze
Journal:  JAMA Surg       Date:  2017-06-01       Impact factor: 14.766

3.  Development and validation of a prognostic scale for hospitalized patients with terminally ill cancer in China.

Authors:  Yu Huang; Qingsong Xi; Shu Xia; Xushi Wang; Yong Liu; Chao Huang; Wei Zheng; Shiying Yu
Journal:  Support Care Cancer       Date:  2013-09-07       Impact factor: 3.603

4.  A prospective study comparing the predictions of doctors versus models for treatment outcome of lung cancer patients: a step toward individualized care and shared decision making.

Authors:  Cary Oberije; Georgi Nalbantov; Andre Dekker; Liesbeth Boersma; Jacques Borger; Bart Reymen; Angela van Baardwijk; Rinus Wanders; Dirk De Ruysscher; Ewout Steyerberg; Anne-Marie Dingemans; Philippe Lambin
Journal:  Radiother Oncol       Date:  2014-05-17       Impact factor: 6.280

5.  Survival prediction and frequency of anticancer treatment in cancer patients hospitalized due to acute conditions. Role of clinical parameters and PaP score.

Authors:  Gianmauro Numico; Marcella Occelli; Elvio G Russi; Nicola Silvestris; Raffaella Pasero; Elena Fea; Cristina Granetto; Gianna Di Costanzo; Ida Colantonio; Milena Gasco; Ornella Garrone; Valentina Polla; Marco C Merlano
Journal:  Support Care Cancer       Date:  2011-05-11       Impact factor: 3.603

6.  New symptom-based predictive tool for survival at seven and thirty days developed by palliative home care teams.

Authors:  Maria Nabal; Mar Bescos; Miquel Barcons; Pilar Torrubia; Javier Trujillano; Antonio Requena
Journal:  J Palliat Med       Date:  2014-06-12       Impact factor: 2.947

7.  [End-of-life therapy for patients dying with cancer: a retrospective database study].

Authors:  Fabiola Fuchs; Martin Robausch
Journal:  Wien Med Wochenschr       Date:  2018-03-13

8.  Predictors of inpatient mortality in an acute palliative care unit at a comprehensive cancer center.

Authors:  Ahmed Elsayem; Masanori Mori; Henrique A Parsons; Mark F Munsell; David Hui; Marvin O Delgado-Guay; Timotheos Paraskevopoulos; Nada A Fadul; Eduardo Bruera
Journal:  Support Care Cancer       Date:  2009-04-07       Impact factor: 3.603

Review 9.  Aggressiveness of cancer care near the end of life: is it a quality-of-care issue?

Authors:  Craig C Earle; Mary Beth Landrum; Jeffrey M Souza; Bridget A Neville; Jane C Weeks; John Z Ayanian
Journal:  J Clin Oncol       Date:  2008-08-10       Impact factor: 44.544

10.  A computer-assisted model for predicting probability of dying within 7 days of hospice admission in patients with terminal cancer.

Authors:  Jui-Kun Chiang; Yu-Hsiang Cheng; Malcolm Koo; Yee-Hsin Kao; Ching-Yu Chen
Journal:  Jpn J Clin Oncol       Date:  2010-01-22       Impact factor: 3.019

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