Literature DB >> 18261876

Prospective validation of the palliative prognostic index in patients with cancer.

Carol A Stone1, Eoin Tiernan, Barbara A Dooley.   

Abstract

The Palliative Prognostic Index (PPI) was devised and validated in patients with cancer in a hospice inpatient unit in Japan. The aim of this study was to test its accuracy in a different population, in a range of care settings and in those receiving palliative chemotherapy and radiotherapy. The information required to calculate the PPI was recorded for patients referred to a hospital-based consultancy palliative care service, a hospice home care service, and a hospice inpatient unit. One hundred ninety-four patients were included in the study, 43% of whom were receiving chemotherapy /or radiotherapy or both. Use of the PPI split patients into three subgroups based on PPI score. Group 1 corresponded to patients with PPI<or=4, median survival 68 days (95% confidence interval [CI] 52, 115 days). Group 2 corresponded to those with PPI>4 and <or=6, median survival 21 days (95% CI 13, 33), and Group 3 corresponded to patients with PPI>6, median survival five days (95% CI 3, 11). Using the PPI, survival of less than three weeks was predicted with a positive predictive value of 86% and negative predictive value of 76%. Survival of less than six weeks was predicted with a positive predictive value of 91% and negative predictive value of 64%. The PPI is quick and easy to use, and can be applied to patients with cancer, in hospital, in hospice, and at home. It may be used by general physicians to achieve prognostic accuracy comparable, if not superior, to that of physicians experienced in oncology and palliative care, and by oncology and palliative care specialists, to improve the accuracy of their survival predictions.

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Year:  2008        PMID: 18261876     DOI: 10.1016/j.jpainsymman.2007.07.006

Source DB:  PubMed          Journal:  J Pain Symptom Manage        ISSN: 0885-3924            Impact factor:   3.612


  28 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 scoring system to guide the decision for a new systemic treatment after at least two lines of palliative chemotherapy for metastatic cancers: a prospective study.

Authors:  Brice Chanez; François Bertucci; Marine Gilabert; Anne Madroszyk; Frédérique Rousseau; Delphine Perrot; Patrice Viens; Jean-Luc Raoul
Journal:  Support Care Cancer       Date:  2017-03-28       Impact factor: 3.603

3.  Magnitude of score change for the palliative prognostic index for survival prediction in patients with poor prognostic terminal cancer.

Authors:  Chia-Yen Hung; Hung-Ming Wang; Chen-Yi Kao; Yung-Chang Lin; Jen-Shi Chen; Yu-Shin Hung; Wen-Chi Chou
Journal:  Support Care Cancer       Date:  2014-05-06       Impact factor: 3.603

Review 4.  Dealing with prognostic uncertainty: the role of prognostic models and websites for patients with advanced cancer.

Authors:  David Hui; John P Maxwell; Carlos Eduardo Paiva
Journal:  Curr Opin Support Palliat Care       Date:  2019-12       Impact factor: 2.302

5.  The accuracy of probabilistic versus temporal clinician prediction of survival for patients with advanced cancer: a preliminary report.

Authors:  David Hui; Kelly Kilgore; Linh Nguyen; Stacy Hall; Julieta Fajardo; Tonye P Cox-Miller; Shana L Palla; Wadih Rhondali; Jung Hun Kang; Sun Hyun Kim; Egidio Del Fabbro; Donna S Zhukovsky; Suresh Reddy; Ahmed Elsayem; Shalini Dalal; Rony Dev; Paul Walker; Sriram Yennu; Akhila Reddy; Eduardo Bruera
Journal:  Oncologist       Date:  2011-10-05

6.  Coming and going: predicting the discharge of cancer patients admitted to a palliative care unit: easier than thought?

Authors:  Eva K Masel; Patrick Huber; Sophie Schur; Katharina A Kierner; Romina Nemecek; Herbert H Watzke
Journal:  Support Care Cancer       Date:  2015-01-11       Impact factor: 3.603

7.  Usefulness of the Palliative Prognostic Index in patients with lung cancer.

Authors:  Minehiko Inomata; Ryuji Hayashi; Kotaro Tokui; Chihiro Taka; Seisuke Okazawa; Kenta Kambara; Tomomi Ichikawa; Kensuke Suzuki; Toru Yamada; Toshiro Miwa; Tatsuhiko Kashii; Shoko Matsui; Kazuyuki Tobe
Journal:  Med Oncol       Date:  2014-08-10       Impact factor: 3.064

8.  Phase angle for prognostication of survival in patients with advanced cancer: preliminary findings.

Authors:  David Hui; Swati Bansal; Margarita Morgado; Rony Dev; Gary Chisholm; Eduardo Bruera
Journal:  Cancer       Date:  2014-06-04       Impact factor: 6.860

Review 9.  Prognostication of Survival in Patients With Advanced Cancer: Predicting the Unpredictable?

Authors:  David Hui
Journal:  Cancer Control       Date:  2015-10       Impact factor: 3.302

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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