Literature DB >> 16218255

Clinical predictors of survival in advanced cancer.

Paul Glare1.   

Abstract

Prognostication is one of the three cardinal clinical skills. Although it has been undervalued by modern medicine compared with diagnostics and therapeutics, poor prognostication can have dire consequences for the patient with advanced cancer, almost as serious as the wrong diagnosis or treatment. Oncologists relying on their subjective judgment for predicting survival often will be inaccurate, usually as too optimistic, which may result in overly aggressive cancer treatment. Actuarial judgment, based on assessment of statistically derived key factors, has the potential to improve prognostic accuracy. These factors in patients with advanced cancer differ from those in patients with newly diagnosed disease; they include performance status, symptoms of the cancer cachexia syndrome, and patient-rated quality of life, rather than tumor size, tumor grade, or extent of disease. Laboratory markers such as leukocytosis or lymphopenia also appear to be useful. Novel markers include acute phase reactants (C-reactive protein, vitamin B12) and cytokines that may provide more objective evidence of survival prospects. Prognostic indices, nomograms, and web-based tools are in development for the advanced cancer population. Identifying the clinical markers predicting for short-term survival in patients with advanced cancer is important to help form the basis for teaching prognostication skills to physicians.

Entities:  

Mesh:

Year:  2005        PMID: 16218255

Source DB:  PubMed          Journal:  J Support Oncol        ISSN: 1544-6794


  26 in total

1.  Symptom clusters and prognosis in advanced cancer.

Authors:  Aynur Aktas; Declan Walsh; Lisa Rybicki
Journal:  Support Care Cancer       Date:  2012-02-24       Impact factor: 3.603

2.  Can oncologists predict survival for patients with progressive disease after standard chemotherapies?

Authors:  T K Taniyama; K Hashimoto; N Katsumata; A Hirakawa; K Yonemori; M Yunokawa; C Shimizu; K Tamura; M Ando; Y Fujiwara
Journal:  Curr Oncol       Date:  2014-04       Impact factor: 3.677

3.  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

4.  Effects of nutritional and psychological status of the patients with advanced stomach cancer on physical performance status.

Authors:  Jun Tian; Zhen-chun Chen; Li-Fang Hang
Journal:  Support Care Cancer       Date:  2009-01-27       Impact factor: 3.603

5.  Cachexia worsens prognosis in patients with resectable pancreatic cancer.

Authors:  Jeannine Bachmann; Mathias Heiligensetzer; Holger Krakowski-Roosen; Markus W Büchler; Helmut Friess; Marc E Martignoni
Journal:  J Gastrointest Surg       Date:  2008-03-18       Impact factor: 3.452

6.  Flexible modeling improves assessment of prognostic value of C-reactive protein in advanced non-small cell lung cancer.

Authors:  B Gagnon; M Abrahamowicz; Y Xiao; M-E Beauchamp; N MacDonald; G Kasymjanova; H Kreisman; D Small
Journal:  Br J Cancer       Date:  2010-03-16       Impact factor: 7.640

7.  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

8.  Longitudinal temporal and probabilistic prediction of survival in a cohort of patients with advanced cancer.

Authors:  Pedro E Perez-Cruz; Renata Dos Santos; Thiago Buosi Silva; Camila Souza Crovador; Maria Salete de Angelis Nascimento; Stacy Hall; Julieta Fajardo; Eduardo Bruera; David Hui
Journal:  J Pain Symptom Manage       Date:  2014-04-16       Impact factor: 3.612

9.  Treating metastatic disease: Which survival model is best suited for the clinic?

Authors:  Jonathan Agner Forsberg; Daniel Sjoberg; Qing-Rong Chen; Andrew Vickers; John H Healey
Journal:  Clin Orthop Relat Res       Date:  2013-03       Impact factor: 4.176

10.  Relationships between patient knowledge and the severity of side effects, daily nutrient intake, psychological status, and performance status in lung cancer patients.

Authors:  J Tian; L N Jia; Z C Cheng
Journal:  Curr Oncol       Date:  2015-08       Impact factor: 3.677

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