Literature DB >> 21976316

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

David Hui1, 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.   

Abstract

Clinicians have limited accuracy in the prediction of patient survival. We assessed the accuracy of probabilistic clinician prediction of survival (CPS) and temporal CPS for advanced cancer patients admitted to our acute palliative care unit, and identified factors associated with CPS accuracy. Eight physicians and 20 nurses provided their estimation of survival on admission by (a) the temporal approach, "What is the approximate survival for this patient (in days)?" and (b) the probabilistic approach, "What is the approximate probability that this patient will be alive (0%-100%)?" for ≥24 hours, 48 hours, 1 week, 2 weeks, 1 month, 3 months, and 6 months. We also collected patient and clinician demographics. Among 151 patients, the median age was 58 years, 95 (63%) were female, and 138 (81%) had solid tumors. The median overall survival time was 12 days. The median temporal CPS was 14 days for physicians and 20 days for nurses. Physicians were more accurate than nurses. A higher accuracy of temporal physician CPS was associated with older patient age. Probabilistic CPS was significantly more accurate than temporal CPS for both physicians and nurses, although this analysis was limited by the different criteria for determining accuracy. With the probabilistic approach, nurses were significantly more accurate at predicting survival at 24 hours and 48 hours, whereas physicians were significantly more accurate at predicting survival at 6 months. The probabilistic approach was associated with high accuracy and has practical implications.

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Year:  2011        PMID: 21976316      PMCID: PMC3233300          DOI: 10.1634/theoncologist.2011-0173

Source DB:  PubMed          Journal:  Oncologist        ISSN: 1083-7159


  25 in total

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2.  Prognostic disclosure to patients with cancer near the end of life.

Authors:  E B Lamont; N A Christakis
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Review 4.  How accurate are physicians' clinical predictions of survival and the available prognostic tools in estimating survival times in terminally ill cancer patients? A systematic review.

Authors:  E Chow; T Harth; G Hruby; J Finkelstein; J Wu; C Danjoux
Journal:  Clin Oncol (R Coll Radiol)       Date:  2001       Impact factor: 4.126

5.  Extent and determinants of error in doctors' prognoses in terminally ill patients: prospective cohort study.

Authors:  N A Christakis; E B Lamont
Journal:  BMJ       Date:  2000-02-19

6.  Complexities in prognostication in advanced cancer: "to help them live their lives the way they want to".

Authors:  Elizabeth B Lamont; Nicholas A Christakis
Journal:  JAMA       Date:  2003-07-02       Impact factor: 56.272

7.  Physician factors in the timing of cancer patient referral to hospice palliative care.

Authors:  Elizabeth B Lamont; Nicholas A Christakis
Journal:  Cancer       Date:  2002-05-15       Impact factor: 6.860

8.  Relationship between cancer patients' predictions of prognosis and their treatment preferences.

Authors:  J C Weeks; E F Cook; S J O'Day; L M Peterson; N Wenger; D Reding; F E Harrell; P Kussin; N V Dawson; A F Connors; J Lynn; R S Phillips
Journal:  JAMA       Date:  1998-06-03       Impact factor: 56.272

9.  The SUPPORT prognostic model. Objective estimates of survival for seriously ill hospitalized adults. Study to understand prognoses and preferences for outcomes and risks of treatments.

Authors:  W A Knaus; F E Harrell; J Lynn; L Goldman; R S Phillips; A F Connors; N V Dawson; W J Fulkerson; R M Califf; N Desbiens; P Layde; R K Oye; P E Bellamy; R B Hakim; D P Wagner
Journal:  Ann Intern Med       Date:  1995-02-01       Impact factor: 25.391

10.  Evaluation and comparison of two prognostic scores and the physicians' estimate of survival in terminally ill patients.

Authors:  S Stiel; L Bertram; S Neuhaus; F Nauck; C Ostgathe; F Elsner; L Radbruch
Journal:  Support Care Cancer       Date:  2009-04-21       Impact factor: 3.603

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  26 in total

1.  In Reply.

Authors:  David Hui; Eduardo Bruera
Journal:  Oncologist       Date:  2015-08-07

2.  Clinical signs of impending death in cancer patients.

Authors:  David Hui; Renata dos Santos; Gary Chisholm; Swati Bansal; Thiago Buosi Silva; Kelly Kilgore; Camila Souza Crovador; Xiaoying Yu; Michael D Swartz; Pedro Emilio Perez-Cruz; Raphael de Almeida Leite; Maria Salete de Angelis Nascimento; Suresh Reddy; Fabiola Seriaco; Sriram Yennu; Carlos Eduardo Paiva; Rony Dev; Stacy Hall; Julieta Fajardo; Eduardo Bruera
Journal:  Oncologist       Date:  2014-04-23

3.  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

4.  Off-Label Medication Use in the Inpatient Palliative Care Unit.

Authors:  Jung Hye Kwon; Min Ji Kim; Sebastian Bruera; Minjeong Park; Eduardo Bruera; David Hui
Journal:  J Pain Symptom Manage       Date:  2017-05-04       Impact factor: 3.612

5.  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

6.  Frequency and factors associated with unexpected death in an acute palliative care unit: expect the unexpected.

Authors:  Sebastian Bruera; Gary Chisholm; Renata Dos Santos; Eduardo Bruera; David Hui
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7.  Impact of timing and setting of palliative care referral on quality of end-of-life care in cancer patients.

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Journal:  Cancer       Date:  2014-06-01       Impact factor: 6.860

8.  Targeted agent use in cancer patients at the end of life.

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9.  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

Review 10.  Clinical considerations for working with patients with advanced cancer.

Authors:  Megan Taylor-Ford
Journal:  J Clin Psychol Med Settings       Date:  2014-09
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