Accuracy and Prognostic Significance of Oncologists' Estimates and Scenarios for Survival Time in Advanced Gastric Cancer.


Journal

The oncologist
ISSN: 1549-490X
Titre abrégé: Oncologist
Pays: England
ID NLM: 9607837

Informations de publication

Date de publication:
11 2019
Historique:
received: 20 09 2018
accepted: 01 03 2019
pubmed: 3 4 2019
medline: 2 7 2020
entrez: 3 4 2019
Statut: ppublish

Résumé

Worst-case, typical, and best-case scenarios for survival, based on simple multiples of an individual's expected survival time (EST), estimated by their oncologist, are a useful way of formulating and explaining prognosis. We aimed to determine the accuracy and prognostic significance of oncologists' estimates of EST, and the accuracy of the resulting scenarios for survival time, in advanced gastric cancer. Sixty-six oncologists estimated the EST at baseline for each of the 152 participants they enrolled in the INTEGRATE trial. We hypothesized that oncologists' estimates of EST would be unbiased (∼50% would be longer or shorter than the observed survival time [OST]); imprecise (<33% within 0.67-1.33 times the OST); independently predictive of overall survival (OS); and accurate at deriving scenarios for survival time with approximately 10% of patients dying within a quarter of their EST (worst-case scenario), 50% living within half to double their EST (typical scenario), and 10% living three or more times their EST (best-case scenario). Oncologists' estimates of EST were unbiased (45% were shorter than the OST, 55% were longer); imprecise (29% were within 0.67-1.33 times observed); moderately discriminative (Harrell's C-statistic 0.62, Oncologists' estimates of EST were unbiased, imprecise, moderately discriminative, and independently significant predictors of OS. Simple multiples of the EST accurately estimated worst-case, typical, and best-case scenarios for survival time in advanced gastric cancer. Results of this study demonstrate that oncologists' estimates of expected survival time for their patients with advanced gastric cancer were unbiased, imprecise, moderately discriminative, and independently significant predictors of overall survival. Simple multiples of the expected survival time accurately estimated worst-case, typical, and best-case scenarios for survival time in advanced gastric cancer.

Sections du résumé

BACKGROUND
Worst-case, typical, and best-case scenarios for survival, based on simple multiples of an individual's expected survival time (EST), estimated by their oncologist, are a useful way of formulating and explaining prognosis. We aimed to determine the accuracy and prognostic significance of oncologists' estimates of EST, and the accuracy of the resulting scenarios for survival time, in advanced gastric cancer.
MATERIALS AND METHODS
Sixty-six oncologists estimated the EST at baseline for each of the 152 participants they enrolled in the INTEGRATE trial. We hypothesized that oncologists' estimates of EST would be unbiased (∼50% would be longer or shorter than the observed survival time [OST]); imprecise (<33% within 0.67-1.33 times the OST); independently predictive of overall survival (OS); and accurate at deriving scenarios for survival time with approximately 10% of patients dying within a quarter of their EST (worst-case scenario), 50% living within half to double their EST (typical scenario), and 10% living three or more times their EST (best-case scenario).
RESULTS
Oncologists' estimates of EST were unbiased (45% were shorter than the OST, 55% were longer); imprecise (29% were within 0.67-1.33 times observed); moderately discriminative (Harrell's C-statistic 0.62,
CONCLUSION
Oncologists' estimates of EST were unbiased, imprecise, moderately discriminative, and independently significant predictors of OS. Simple multiples of the EST accurately estimated worst-case, typical, and best-case scenarios for survival time in advanced gastric cancer.
IMPLICATIONS FOR PRACTICE
Results of this study demonstrate that oncologists' estimates of expected survival time for their patients with advanced gastric cancer were unbiased, imprecise, moderately discriminative, and independently significant predictors of overall survival. Simple multiples of the expected survival time accurately estimated worst-case, typical, and best-case scenarios for survival time in advanced gastric cancer.

Identifiants

pubmed: 30936377
pii: theoncologist.2018-0613
doi: 10.1634/theoncologist.2018-0613
pmc: PMC6853097
doi:

Substances chimiques

Antineoplastic Agents 0
Phenylurea Compounds 0
Pyridines 0
regorafenib 24T2A1DOYB

Types de publication

Clinical Trial, Phase II Journal Article Multicenter Study Randomized Controlled Trial Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1102-e1107

Informations de copyright

© AlphaMed Press 2019.

Déclaration de conflit d'intérêts

Disclosures of potential conflicts of interest may be found at the end of this article.

Références

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Auteurs

Anuradha Vasista (A)

NHMRC Clinical Trials Centre, University of Sydney, New South Wales, Australia anuradha.vasista@ctc.usyd.edu.au.

Martin Stockler (M)

NHMRC Clinical Trials Centre, University of Sydney, New South Wales, Australia.

Andrew Martin (A)

NHMRC Clinical Trials Centre, University of Sydney, New South Wales, Australia.

Nick Pavlakis (N)

Royal North Shore Hospital, New South Wales, Australia.

Katrin Sjoquist (K)

NHMRC Clinical Trials Centre, University of Sydney, New South Wales, Australia.
St George Hospital, New South Wales, Australia.

David Goldstein (D)

Prince of Wales Hospital, New South Wales, Australia.

Sanjeev Gill (S)

The Alfred Hospital, Victoria, Australia.

Vikram Jain (V)

ICON Cancer Foundation, Queensland, Australia.

Geoffrey Liu (G)

University Health Network, Princess Margaret Hospital, Toronto, Canada.

George Kannourakis (G)

Ballarat Oncology and Haematology Services, Ballarat, Victoria, Australia.

Yeul Hong Kim (YH)

Korea University Hospital, South Korea.

Louise Nott (L)

Royal Hobart Hospital, Tasmania, Australia.

Stephanie Snow (S)

Queen Elizabeth II Health Sciences Centre, Nova Scotia, Canada.

Matthew Burge (M)

Royal Brisbane and Womens Hospital, Queensland, Australia.

Dean Harris (D)

Christchurch Hospital, Canterbury, New Zealand.

Derek Jonker (D)

Ottawa Health Research Institute, Ottawa, Canada.

Yu Jo Chua (YJ)

Canberra Hospital, Australian Capital Territory, Australia.

Richard Epstein (R)

The Kinghorn Cancer Centre, St Vincent's Hospital, New South Wales, Australia.

Antony Bonaventura (A)

Newcastle Private Hospital, New South Wales, Australia.

Belinda Kiely (B)

NHMRC Clinical Trials Centre, University of Sydney, New South Wales, Australia.

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Classifications MeSH