Please be patient while the object screen loads.
USC
RESEARCH
BANK
USC Research Bank - University of the Sunshine Coast, Queensland, Australia
Home
About
Show
All
Contribute
Open Access
Copyright
Contact
USC Virtual Herbarium
Recent Additions
Browse USC Research Bank
+
Communities & Collections
By Resource Type
By Supervisor
By Title
by Author/Creator
By Subject
By Year
Search History
Clear Session
Show
Quick Collection
Advanced Search
Home
List Of Titles
Prognostic survival model for people diagnosed with invasive cutaneous melanoma
Add to Quick Collection
Description
Size
Format
PDF - Published Version (Open Access)
809 KB
Adobe Acrobat PDF
Download
Download All
PDF - Published Version (Open Access)
Title
Prognostic survival model for people diagnosed with invasive cutaneous melanoma
Author/Creator
Baade, P D
|
Royston, P
|
Youl, Philippa H
|
Weinstock, M A
|
Geller, A
|
Aitken, J F
Description
Background: The ability of medical practitioners to communicate risk estimates effectively to patients diagnosed with melanoma relies on accurate information about prognostic factors and their impact on survival. This study reports the development of one of the few melanoma prognostic models, called the Melanoma Severity Index (MSI), based on population-based cancer registry data. Methods: Data from the Queensland Cancer Registry for people (20-89 years) diagnosed with a single invasive melanoma between 1995 and 2008 (n = 28,654; 1,700 melanoma deaths). Additional clinical information about metastasis, ulceration and positive lymph nodes was manually extracted from pathology forms. Flexible parametric survival models were combined with multivariable fractional polynomial for selecting variables and transformations of continuous variables. Multiple imputation was used for missing covariate values. Results: The MSI contained the variables thickness (transformed, explained 40.6% of variation in survival), body site (additional 1.9% in variation), metastasis (1.8%), positive nodes (0.7%), ulceration (1.3%), age (1.1%). Royston and Sauerbrei's D statistic (measure of discrimination) was 1.50 (95% CI = 1.44, 1.56) and the corresponding RD2 (measure of explained variation) was 0.47 (0.45, 0.49), demonstrating strong explanatory performance. The Harrell-C statistic was 0.88 (0.88, 0.89). Lacking an external validation dataset, we applied internal-external cross validation to demonstrate the consistency of the prognostic information across geographically-defined subsets of the cohort. Conclusions: The MSI provides good ability to predict survival for melanoma patients. Beyond the immediate clinical use, the MSI may have important public health and research applications for evaluations of public health interventions aimed at reducing deaths from melanoma. © Baade et al.
Relation
BMC Cancer / Vol. 15, No. 1
Relation
http://dx.doi.org/10.1186/s12885-015-1024-4
Year
2015
Publisher
BioMed Central Ltd.
Subject
FoR 1112 (Oncology and Carcinogenesis)
|
melanoma
|
survival
|
prognostic model
|
thickness
|
population-based
|
risk
Resource Type
Journal Article
Identifier
ISSN: 1471-2407
Rights
Copyright © 2015 Baade et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain
Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,
unless otherwise stated.
Reviewed
375 Visitors
10 Downloads
Save/E-mail Citation
Citation Format
Plain Text Citation
HTML Citation
EndNote Format
E-mail Address
Subject
OR
© 2012 University of the Sunshine Coast, Queensland, Australia | ABN 28 441 859 157 | CRICOS Provider No. 01595D