Literature DB >> 18715969

Development and validation of a prognostic scale for use in patients with advanced cancer.

P Stone1, L Kelly, R Head, S White.   

Abstract

The aim of this study was to develop a new prognostic indicator to help predict survival in advanced cancer patients more accurately. Data on 329 patients obtained from a multi-centre study in London were analysed. A multifactorial Cox regression model was applied and validated using bootstrapping techniques. Predictive scores were calculated and used to produce a new prognostic index. The value of the index in predicting 14-day survival was then assessed. Four variables were found to be associated with worse survival: primary lung cancer, secondary liver cancer, raised C-Reactive protein and poor performance status (ECOG 4). Survival curves showed that patients designated as 'high' risk by the resulting index had significantly shorter survival than those designated as 'low' risk. A high score on the newly derived prognostic index is associated with poorer survival, but its clinical utility is limited by the relatively low predictive probability of the score.

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Year:  2008        PMID: 18715969     DOI: 10.1177/0269216308095200

Source DB:  PubMed          Journal:  Palliat Med        ISSN: 0269-2163            Impact factor:   4.762


  8 in total

1.  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

2.  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

3.  The average lifespan of patients discharged from hospital with heart failure.

Authors:  David A Alter; Dennis T Ko; Jack V Tu; Therese A Stukel; Douglas S Lee; Andreas Laupacis; Alice Chong; Peter C Austin
Journal:  J Gen Intern Med       Date:  2012-05-02       Impact factor: 5.128

4.  Clinical changes in terminally ill cancer patients and death within 48 h: when should we refer patients to a separate room?

Authors:  In Cheol Hwang; Hong Yup Ahn; Sang Min Park; Jae Yong Shim; Kyoung Kon Kim
Journal:  Support Care Cancer       Date:  2012-09-07       Impact factor: 3.603

5.  High SARC-F score predicts poor survival of patients with cancer receiving palliative care.

Authors:  Naoharu Mori; Keisuke Maeda; Yasuyuki Fukami; Remi Matsuyama; Tomoyuki Nonogaki; Ryoko Kato; Yuria Ishida; Akio Shimizu; Junko Ueshima; Ayano Nagano
Journal:  Support Care Cancer       Date:  2022-01-22       Impact factor: 3.603

6.  Development of prognosis in palliative care study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study.

Authors:  Bridget Gwilliam; Vaughan Keeley; Chris Todd; Matthew Gittins; Chris Roberts; Laura Kelly; Stephen Barclay; Patrick C Stone
Journal:  BMJ       Date:  2011-08-25

7.  A proposed prognostic 7-day survival formula for patients with terminal cancer.

Authors:  Jui-Kun Chiang; Ning-Sheng Lai; Mei-Huang Wang; Shi-Chi Chen; Yee-Hsin Kao
Journal:  BMC Public Health       Date:  2009-09-29       Impact factor: 3.295

8.  Predicting 7-day survival using heart rate variability in hospice patients with non-lung cancers.

Authors:  Jui-Kun Chiang; Terry B J Kuo; Chin-Hua Fu; Malcolm Koo
Journal:  PLoS One       Date:  2013-07-23       Impact factor: 3.240

  8 in total

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