FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2281456422> ?p ?o ?g. }

• W2281456422 endingPage "1254" @default.
• W2281456422 startingPage "1247" @default.
• W2281456422 abstract "Basal cell and squamous cell carcinomas of the skin are the commonest cancers in humans, yet no validated tools exist to estimate future risks of developing keratinocyte carcinomas. To develop a prediction tool, we used baseline data from a prospective cohort study (n = 38,726) in Queensland, Australia, and used data linkage to capture all surgically excised keratinocyte carcinomas arising within the cohort. Predictive factors were identified through stepwise logistic regression models. In secondary analyses, we derived separate models within strata of prior skin cancer history, age, and sex. The primary model included terms for 10 items. Factors with the strongest effects were >20 prior skin cancers excised (odds ratio 8.57, 95% confidence interval [95% CI] 6.73–10.91), >50 skin lesions destroyed (odds ratio 3.37, 95% CI 2.85–3.99), age ≥ 70 years (odds ratio 3.47, 95% CI 2.53–4.77), and fair skin color (odds ratio 1.75, 95% CI 1.42–2.15). Discrimination in the validation dataset was high (area under the receiver operator characteristic curve 0.80, 95% CI 0.79–0.81) and the model appeared well calibrated. Among those reporting no prior history of skin cancer, a similar model with 10 factors predicted keratinocyte carcinoma events with reasonable discrimination (area under the receiver operator characteristic curve 0.72, 95% CI 0.70–0.75). Algorithms using self-reported patient data have high accuracy for predicting risks of keratinocyte carcinomas. Basal cell and squamous cell carcinomas of the skin are the commonest cancers in humans, yet no validated tools exist to estimate future risks of developing keratinocyte carcinomas. To develop a prediction tool, we used baseline data from a prospective cohort study (n = 38,726) in Queensland, Australia, and used data linkage to capture all surgically excised keratinocyte carcinomas arising within the cohort. Predictive factors were identified through stepwise logistic regression models. In secondary analyses, we derived separate models within strata of prior skin cancer history, age, and sex. The primary model included terms for 10 items. Factors with the strongest effects were >20 prior skin cancers excised (odds ratio 8.57, 95% confidence interval [95% CI] 6.73–10.91), >50 skin lesions destroyed (odds ratio 3.37, 95% CI 2.85–3.99), age ≥ 70 years (odds ratio 3.47, 95% CI 2.53–4.77), and fair skin color (odds ratio 1.75, 95% CI 1.42–2.15). Discrimination in the validation dataset was high (area under the receiver operator characteristic curve 0.80, 95% CI 0.79–0.81) and the model appeared well calibrated. Among those reporting no prior history of skin cancer, a similar model with 10 factors predicted keratinocyte carcinoma events with reasonable discrimination (area under the receiver operator characteristic curve 0.72, 95% CI 0.70–0.75). Algorithms using self-reported patient data have high accuracy for predicting risks of keratinocyte carcinomas." @default.
• W2281456422 created "2016-06-24" @default.
• W2281456422 creator A5016501781 @default.
• W2281456422 creator A5027765428 @default.
• W2281456422 creator A5027773194 @default.
• W2281456422 creator A5035678916 @default.
• W2281456422 creator A5042470315 @default.
• W2281456422 creator A5044247924 @default.
• W2281456422 creator A5046500631 @default.
• W2281456422 creator A5054431826 @default.
• W2281456422 creator A5077133619 @default.
• W2281456422 creator A5077862296 @default.
• W2281456422 creator A5087888345 @default.
• W2281456422 creator A5089932385 @default.
• W2281456422 date "2016-06-01" @default.
• W2281456422 modified "2023-10-16" @default.
• W2281456422 title "A Model to Predict the Risk of Keratinocyte Carcinomas" @default.
• W2281456422 cites W1509599022 @default.
• W2281456422 cites W1529230314 @default.
• W2281456422 cites W1852538637 @default.
• W2281456422 cites W2010541676 @default.
• W2281456422 cites W2017266007 @default.
• W2281456422 cites W2042703000 @default.
• W2281456422 cites W2051411536 @default.
• W2281456422 cites W2058819432 @default.
• W2281456422 cites W2062344922 @default.
• W2281456422 cites W2065949429 @default.
• W2281456422 cites W2065974896 @default.
• W2281456422 cites W2098000728 @default.
• W2281456422 cites W2110467884 @default.
• W2281456422 cites W2124381672 @default.
• W2281456422 cites W2134146304 @default.
• W2281456422 cites W2147333897 @default.
• W2281456422 cites W2154553317 @default.
• W2281456422 cites W2166155963 @default.
• W2281456422 cites W2169161052 @default.
• W2281456422 cites W2470592308 @default.
• W2281456422 doi "https://doi.org/10.1016/j.jid.2016.02.008" @default.
• W2281456422 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26908057" @default.
• W2281456422 hasPublicationYear "2016" @default.
• W2281456422 type Work @default.
• W2281456422 sameAs 2281456422 @default.
• W2281456422 citedByCount "27" @default.
• W2281456422 countsByYear W22814564222017 @default.
• W2281456422 countsByYear W22814564222018 @default.
• W2281456422 countsByYear W22814564222019 @default.
• W2281456422 countsByYear W22814564222020 @default.
• W2281456422 countsByYear W22814564222021 @default.
• W2281456422 countsByYear W22814564222022 @default.
• W2281456422 countsByYear W22814564222023 @default.
• W2281456422 crossrefType "journal-article" @default.
• W2281456422 hasAuthorship W2281456422A5016501781 @default.
• W2281456422 hasAuthorship W2281456422A5027765428 @default.
• W2281456422 hasAuthorship W2281456422A5027773194 @default.
• W2281456422 hasAuthorship W2281456422A5035678916 @default.
• W2281456422 hasAuthorship W2281456422A5042470315 @default.
• W2281456422 hasAuthorship W2281456422A5044247924 @default.
• W2281456422 hasAuthorship W2281456422A5046500631 @default.
• W2281456422 hasAuthorship W2281456422A5054431826 @default.
• W2281456422 hasAuthorship W2281456422A5077133619 @default.
• W2281456422 hasAuthorship W2281456422A5077862296 @default.
• W2281456422 hasAuthorship W2281456422A5087888345 @default.
• W2281456422 hasAuthorship W2281456422A5089932385 @default.
• W2281456422 hasBestOaLocation W22814564221 @default.
• W2281456422 hasConcept C121608353 @default.
• W2281456422 hasConcept C126322002 @default.
• W2281456422 hasConcept C142724271 @default.
• W2281456422 hasConcept C143998085 @default.
• W2281456422 hasConcept C151956035 @default.
• W2281456422 hasConcept C156957248 @default.
• W2281456422 hasConcept C16005928 @default.
• W2281456422 hasConcept C170964787 @default.
• W2281456422 hasConcept C202751555 @default.
• W2281456422 hasConcept C2777074287 @default.
• W2281456422 hasConcept C2777789703 @default.
• W2281456422 hasConcept C2778804307 @default.
• W2281456422 hasConcept C3019992690 @default.
• W2281456422 hasConcept C44249647 @default.
• W2281456422 hasConcept C54355233 @default.
• W2281456422 hasConcept C58471807 @default.
• W2281456422 hasConcept C71924100 @default.
• W2281456422 hasConcept C72563966 @default.
• W2281456422 hasConcept C86803240 @default.
• W2281456422 hasConceptScore W2281456422C121608353 @default.
• W2281456422 hasConceptScore W2281456422C126322002 @default.
• W2281456422 hasConceptScore W2281456422C142724271 @default.
• W2281456422 hasConceptScore W2281456422C143998085 @default.
• W2281456422 hasConceptScore W2281456422C151956035 @default.
• W2281456422 hasConceptScore W2281456422C156957248 @default.
• W2281456422 hasConceptScore W2281456422C16005928 @default.
• W2281456422 hasConceptScore W2281456422C170964787 @default.
• W2281456422 hasConceptScore W2281456422C202751555 @default.
• W2281456422 hasConceptScore W2281456422C2777074287 @default.
• W2281456422 hasConceptScore W2281456422C2777789703 @default.
• W2281456422 hasConceptScore W2281456422C2778804307 @default.
• W2281456422 hasConceptScore W2281456422C3019992690 @default.
• W2281456422 hasConceptScore W2281456422C44249647 @default.
• W2281456422 hasConceptScore W2281456422C54355233 @default.

• next