Literature DB >> 10391577

The relative accuracy of the clinical estimation of the duration of life for patients with end of life cancer.

A Viganò1, M Dorgan, E Bruera, M E Suarez-Almazor.   

Abstract

BACKGROUND: Although the prediction of the duration of life of patients with end of life cancer most often relies on the clinical estimation of survival (CES) made by the treating physician, the accuracy and practical value of CES remains controversial.
METHODS: The authors prospectively evaluated the accuracy of CES in an inception and population-based cohort of 233 cancer patients who were seen at the onset of their terminal phase. They also systematically reviewed the literature on CES in advanced or end-stage cancer patients in MEDLINE, CANCERLIT, and EMBASE data bases, using two search strategies developed by a research librarian.
RESULTS: CES had low sensitivity in detecting patients who died within shorter time frames (< or =2 months), and a tendency to overestimate survival was noted. A moderate correlation was observed between actual survival (AS) and CES (Pearson correlation coefficient = 0.47, intraclass correlation coefficient = 0.46, weighted kappa coefficient = 0.42).
CONCLUSIONS: Treating physicians appear to overestimate the duration of life of end of life ill cancer patients, particularly those patients who die early in the terminal phase and who may potentially benefit from earlier participation in palliative care programs. CES should be considered one of many criteria, rather than a unique criterion, by which to choose therapeutic intervention or health care programs for patients in the end of life cancer phase.

Entities:  

Mesh:

Year:  1999        PMID: 10391577

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  41 in total

1.  Appropriate time frames for data collection in quality of life research among cancer patients at the end of life.

Authors:  Siew Tzuh Tang; Ruth McCorkle
Journal:  Qual Life Res       Date:  2002-03       Impact factor: 4.147

2.  Survival prediction for terminally ill cancer patients: revision of the palliative prognostic score with incorporation of delirium.

Authors:  Emanuela Scarpi; Marco Maltoni; Rosalba Miceli; Luigi Mariani; Augusto Caraceni; Dino Amadori; Oriana Nanni
Journal:  Oncologist       Date:  2011-10-31

3.  Development of a predictive model for 6 month survival in patients with venous thromboembolism and solid malignancy requiring IVC filter placement.

Authors:  Steven Y Huang; Bruno C Odisio; Sharjeel H Sabir; Joe E Ensor; Andrew S Niekamp; Tam T Huynh; Michael Kroll; Sanjay Gupta
Journal:  J Thromb Thrombolysis       Date:  2017-07       Impact factor: 2.300

4.  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

5.  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

6.  How palliative care professionals deal with predicting life expectancy at the end of life: predictors and accuracy.

Authors:  Sara Mandelli; Emma Riva; Mauro Tettamanti; Ugo Lucca; Davide Lombardi; Gianmaria Miolo; Simon Spazzapan; Rita Marson
Journal:  Support Care Cancer       Date:  2020-08-31       Impact factor: 3.603

7.  Accuracy of Oncologists' Life-Expectancy Estimates Recalled by Their Advanced Cancer Patients: Correlates and Outcomes.

Authors:  Jason Lambden; Baohui Zhang; Robert Friedlander; Holly G Prigerson
Journal:  J Palliat Med       Date:  2016-08-30       Impact factor: 2.947

8.  Resident physicians' life expectancy estimates and colon cancer screening recommendations in elderly patients.

Authors:  Carmen L Lewis; Charity G Moore; Carol E Golin; Jennifer Griffith; Alison Tytell-Brenner; Michael P Pignone
Journal:  Med Decis Making       Date:  2008-03-18       Impact factor: 2.583

9.  A longitudinal study of the role of patient-reported outcomes on survival prediction of palliative cancer inpatients in Taiwan.

Authors:  Jing-An Chang; Chia-Chin Lin
Journal:  Support Care Cancer       Date:  2009-02-12       Impact factor: 3.603

10.  Model-assisted predictions on prognosis in HNSCC: do we learn?

Authors:  Marc P van der Schroeff; Kim van Schie; Ton P M Langeveld; Caspar Looman; Robert J Baatenburg de Jong
Journal:  Eur Arch Otorhinolaryngol       Date:  2010-04-17       Impact factor: 2.503

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.