ArticleJournal of the American Statistical Association2017
Defining Cancer Subtypes With Distinctive Etiologic Profiles: An Application to the Epidemiology of Melanoma.
Article in Journal of the American Statistical Association, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Melanocyte lineage dynamics in development, growth and disease.Development (Cambridge, England) · 2024Review
- Aggregation of melanoma tumour site within Western Australian families.Cancer epidemiology · 2024Article
- Validity of a method for identifying disease subtypes that are etiologically heterogeneous.Statistical methods in medical research · 2021Article
- Risk factors for melanoma by anatomical site: an evaluation of aetiological heterogeneity.The British journal of dermatology · 2021Article
- Family Study Designs Informed by Tumor Heterogeneity and Multi-Cancer Pleiotropies: The Power of the Utah Population Database.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Evidence for Etiologic Subtypes of Breast Cancer in the Carolina Breast Cancer Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
We showcase a novel analytic strategy to identify sub-types of cancer that possess distinctive causal factors, i.e. sub-types that are "etiologically" distinct. The method involves the integrated analysis of two types of study design: an incident series of cases with double primary cancers with detailed information on tumor characteristics that can be used to define the sub-types; a case-series of incident cases with information on known risk factors that can be used to investigate the specific risk factors that distinguish the sub-types. The methods are applied to a rich melanoma dataset with detailed information on pathologic tumor factors, and comprehensive information on known genetic and environmental risk factors for melanoma. Identification of the optimal sub-typing solution is accomplished using a novel clustering analysis that seeks to maximize a measure that characterizes the distinctiveness of the distributions of risk factors across the sub-types and that is a function of the correlations of tumor factors in the case-specific tumor pairs. This analysis is challenged by the presence of extensive missing data. If successful, studies of this nature offer the opportunity for efficient study design to identify unknown risk factors whose effects are concentrated in defined sub-types.
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Registered trials
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