Literature DB >> 25499420

Independent validation of the modified prognosis palliative care study predictor models in three palliative care settings.

Mika Baba1, Isseki Maeda2, Tatsuya Morita3, Takayuki Hisanaga4, Tatsuhiko Ishihara5, Tomoyuki Iwashita6, Keisuke Kaneishi7, Shohei Kawagoe8, Toshiyuki Kuriyama9, Takashi Maeda10, Ichiro Mori11, Nobuhisa Nakajima12, Tomohiro Nishi13, Hiroki Sakurai14, Satofumi Shimoyama15, Takuya Shinjo16, Hiroto Shirayama17, Takeshi Yamada18, Shigeki Ono19, Taketoshi Ozawa20, Ryo Yamamoto21, Satoru Tsuneto22.   

Abstract

CONTEXT: Accurate prognostic information in palliative care settings is needed for patients to make decisions and set goals and priorities. The Prognosis Palliative Care Study (PiPS) predictor models were presented in 2011, but have not yet been fully validated by other research teams.
OBJECTIVES: The primary aim of this study is to examine the accuracy and to validate the modified PiPS (using physician-proxy ratings of mental status instead of patient interviews) in three palliative care settings, namely palliative care units, hospital-based palliative care teams, and home-based palliative care services.
METHODS: This multicenter prospective cohort study was conducted in 58 palliative care services including 16 palliative care units, 19 hospital-based palliative care teams, and 23 home-based palliative care services in Japan from September 2012 through April 2014.
RESULTS: A total of 2426 subjects were recruited. For reasons including lack of followup and missing variables (primarily blood examination data), we obtained analyzable data from 2212 and 1257 patients for the modified PiPS-A and PiPS-B, respectively. In all palliative care settings, both the modified PiPS-A and PiPS-B identified three risk groups with different survival rates (P<0.001). The absolute agreement ranged from 56% to 60% in the PiPS-A model and 60% to 62% in the PiPS-B model.
CONCLUSION: The modified PiPS was successfully validated and can be useful in palliative care units, hospital-based palliative care teams, and home-based palliative care services.
Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Prognosis palliative care study predictor models; modified; palliative setting; prognostic score; validation study

Mesh:

Year:  2014        PMID: 25499420     DOI: 10.1016/j.jpainsymman.2014.10.010

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


  12 in total

Review 1.  Chemotherapy at end-of-life: an integration of oncology and palliative team.

Authors:  Wing-lok Chan; Ka-on Lam; Wai-kwan Siu; Kwok-keung Yuen
Journal:  Support Care Cancer       Date:  2015-11-25       Impact factor: 3.603

Review 2.  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

3.  Surprise Questions for Survival Prediction in Patients With Advanced Cancer: A Multicenter Prospective Cohort Study.

Authors:  Jun Hamano; Tatsuya Morita; Satoshi Inoue; Masayuki Ikenaga; Yoshihisa Matsumoto; Ryuichi Sekine; Takashi Yamaguchi; Takeshi Hirohashi; Tsukasa Tajima; Ryohei Tatara; Hiroaki Watanabe; Hiroyuki Otani; Chizuko Takigawa; Yoshinobu Matsuda; Hiroka Nagaoka; Masanori Mori; Naoki Yamamoto; Mie Shimizu; Takeshi Sasara; Hiroya Kinoshita
Journal:  Oncologist       Date:  2015-06-08

Review 4.  Prognostication in advanced cancer: update and directions for future research.

Authors:  David Hui; Carlos Eduardo Paiva; Egidio G Del Fabbro; Christopher Steer; Jane Naberhuis; Marianne van de Wetering; Paz Fernández-Ortega; Tatsuya Morita; Sang-Yeon Suh; Eduardo Bruera; Masanori Mori
Journal:  Support Care Cancer       Date:  2019-03-13       Impact factor: 3.603

5.  Glasgow prognostic score predicts prognosis for cancer patients in palliative settings: a subanalysis of the Japan-prognostic assessment tools validation (J-ProVal) study.

Authors:  Tomofumi Miura; Yoshihisa Matsumoto; Takashi Hama; Koji Amano; Yo Tei; Ayako Kikuchi; Akihiko Suga; Takayuki Hisanaga; Tatsuhiko Ishihara; Mutsumi Abe; Keisuke Kaneishi; Shohei Kawagoe; Toshiyuki Kuriyama; Takashi Maeda; Ichiro Mori; Nobuhisa Nakajima; Tomohiro Nishi; Hiroki Sakurai; Tatsuya Morita; Hiroya Kinoshita
Journal:  Support Care Cancer       Date:  2015-03-17       Impact factor: 3.603

6.  Prognostic models of survival in patients with advanced incurable cancer: the PiPS2 observational study.

Authors:  Patrick Stone; Anastasia Kalpakidou; Chris Todd; Jane Griffiths; Vaughan Keeley; Karen Spencer; Peter Buckle; Dori-Anne Finlay; Victoria Vickerstaff; Rumana Z Omar
Journal:  Health Technol Assess       Date:  2021-05       Impact factor: 4.014

7.  C-reactive protein, symptoms and activity of daily living in patients with advanced cancer receiving palliative care.

Authors:  Koji Amano; Isseki Maeda; Tatsuya Morita; Mika Baba; Tomofumi Miura; Takashi Hama; Ichiro Mori; Nobuhisa Nakajima; Tomohiro Nishi; Hiroki Sakurai; Satofumi Shimoyama; Takuya Shinjo; Hiroto Shirayama; Takeshi Yamada; Shigeki Ono; Taketoshi Ozawa; Ryo Yamamoto; Naoki Yamamoto; Hideki Shishido; Hiroya Kinoshita
Journal:  J Cachexia Sarcopenia Muscle       Date:  2017-03-01       Impact factor: 12.910

8.  A systematically structured review of biomarkers of dying in cancer patients in the last months of life; An exploration of the biology of dying.

Authors:  Victoria Louise Reid; Rachael McDonald; Amara Callistus Nwosu; Stephen R Mason; Chris Probert; John E Ellershaw; Séamus Coyle
Journal:  PLoS One       Date:  2017-04-06       Impact factor: 3.240

9.  The Prognosis in Palliative care Study II (PiPS2): study protocol for a multi-centre, prospective, observational, cohort study.

Authors:  Anastasia K Kalpakidou; Chris Todd; Vaughan Keeley; Jane Griffiths; Karen Spencer; Victoria Vickerstaff; Rumana Z Omar; Patrick Stone
Journal:  BMC Palliat Care       Date:  2018-08-13       Impact factor: 3.234

10.  PALLIA-10, a screening tool to identify patients needing palliative care referral in comprehensive cancer centers: A prospective multicentric study (PREPA-10).

Authors:  Yann Molin; Caroline Gallay; Julien Gautier; Audrey Lardy-Cleaud; Romaine Mayet; Marie-Christine Grach; Gérard Guesdon; Géraldine Capodano; Olivier Dubroeucq; Carole Bouleuc; Nathalie Bremaud; Anne Fogliarini; Aline Henry; Nathalie Caunes-Hilary; Stéphanie Villet; Christine Villatte; Véronique Frasie; Valérie Triolaire; Véronique Barbarot; Jean-Marie Commer; Agnès Hutin; Gisèle Chvetzoff
Journal:  Cancer Med       Date:  2019-05-04       Impact factor: 4.452

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