Prognostic survival model for people diagnosed with invasive cutaneous melanoma
Baade, Peter D
Youl, Philipa H
Weinstock, Martin A
Aitken, Joanne F
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CitationBaade, Peter D, Patrick Royston, Philipa H Youl, Martin A Weinstock, Alan Geller, and Joanne F Aitken. 2015. “Prognostic survival model for people diagnosed with invasive cutaneous melanoma.” BMC Cancer 15 (1): 27. doi:10.1186/s12885-015-1024-4. http://dx.doi.org/10.1186/s12885-015-1024-4.
AbstractBackground: 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.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:14065368
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