FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4225316261> ?p ?o ?g. }

• W4225316261 endingPage "513" @default.
• W4225316261 startingPage "504" @default.
• W4225316261 abstract "Assessing overall tumor burden on the basis of tumor number and size may assist in prognostic stratification of patients after resection of colorectal liver metastases (CRLM). We sought to define the prognostic accuracy of tumor burden by using machine learning (ML) algorithms compared with other commonly used prognostic scoring systems.Patients who underwent hepatectomy for CRLM between 2001 and 2018 were identified from a multi-institutional database and split into training and validation cohorts. ML was used to define tumor burden (ML-TB) based on CRLM tumor number and size thresholds associated with 5-year overall survival. Prognostic ability of ML-TB was compared with the Fong and Genetic and Morphological Evaluation scores using Cohen's d.Among 1,344 patients who underwent resection of CRLM, median tumor number (2, interquartile range 1 to 3) and size (3 cm, interquartile range 2.0 to 5.0) were comparable in the training (n = 672) vs validation (n = 672) cohorts; patient age (training 60.8 vs validation 61.0) and preoperative CEA (training 10.2 ng/mL vs validation 8.3 ng/mL) was also similar (p > 0.05). ML empirically derived optimal cutoff thresholds for number of lesions (3) and size of the largest lesion (1.3 cm) in the training cohort, which were then used to categorize patients in the validation cohort into 3 prognostic groups. Patients with low, average, or high ML-TB had markedly different 5-year overall survival (51.6%, 40.9%, and 23.1%, respectively; p < 0.001). ML-TB was more effective at stratifying patients relative to 5-year overall survival (low vs high ML-TB, d = 2.73) vs the Fong clinical (d = 1.61) or Genetic and Morphological Evaluation (d = 0.84) scores.Using a large international cohort, ML was able to stratify patients into 3 distinct prognostic categories based on overall tumor burden. ML-TB was noted to be superior to other CRLM prognostic scoring systems." @default.
• W4225316261 created "2022-05-05" @default.
• W4225316261 creator A5016519845 @default.
• W4225316261 creator A5023140410 @default.
• W4225316261 creator A5026797981 @default.
• W4225316261 creator A5043112957 @default.
• W4225316261 creator A5053538488 @default.
• W4225316261 creator A5057140415 @default.
• W4225316261 creator A5065551581 @default.
• W4225316261 creator A5067905052 @default.
• W4225316261 creator A5074822109 @default.
• W4225316261 creator A5077468333 @default.
• W4225316261 date "2022-03-15" @default.
• W4225316261 modified "2023-09-28" @default.
• W4225316261 title "Machine Learning Approach to Stratifying Prognosis Relative to Tumor Burden after Resection of Colorectal Liver Metastases: An International Cohort Analysis" @default.
• W4225316261 cites W1574994718 @default.
• W4225316261 cites W1765193236 @default.
• W4225316261 cites W1943526660 @default.
• W4225316261 cites W1970844261 @default.
• W4225316261 cites W1981845767 @default.
• W4225316261 cites W1987403189 @default.
• W4225316261 cites W1988969830 @default.
• W4225316261 cites W1989175303 @default.
• W4225316261 cites W2000445173 @default.
• W4225316261 cites W2007900522 @default.
• W4225316261 cites W2021031183 @default.
• W4225316261 cites W2040117720 @default.
• W4225316261 cites W2043049566 @default.
• W4225316261 cites W2048241019 @default.
• W4225316261 cites W2064799866 @default.
• W4225316261 cites W2067482493 @default.
• W4225316261 cites W2074811887 @default.
• W4225316261 cites W2084470612 @default.
• W4225316261 cites W2085070000 @default.
• W4225316261 cites W2092679286 @default.
• W4225316261 cites W2094002672 @default.
• W4225316261 cites W2098370829 @default.
• W4225316261 cites W2101815035 @default.
• W4225316261 cites W2119190881 @default.
• W4225316261 cites W2121656227 @default.
• W4225316261 cites W2131745440 @default.
• W4225316261 cites W2144326782 @default.
• W4225316261 cites W2536071775 @default.
• W4225316261 cites W2536674525 @default.
• W4225316261 cites W2730324631 @default.
• W4225316261 cites W2771103542 @default.
• W4225316261 cites W2801227536 @default.
• W4225316261 cites W2922128086 @default.
• W4225316261 cites W3009963727 @default.
• W4225316261 cites W3048386033 @default.
• W4225316261 cites W3094558370 @default.
• W4225316261 cites W3115572683 @default.
• W4225316261 cites W3143583795 @default.
• W4225316261 cites W1969590998 @default.
• W4225316261 doi "https://doi.org/10.1097/xcs.0000000000000094" @default.
• W4225316261 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35290269" @default.
• W4225316261 hasPublicationYear "2022" @default.
• W4225316261 type Work @default.
• W4225316261 citedByCount "0" @default.
• W4225316261 crossrefType "journal-article" @default.
• W4225316261 hasAuthorship W4225316261A5016519845 @default.
• W4225316261 hasAuthorship W4225316261A5023140410 @default.
• W4225316261 hasAuthorship W4225316261A5026797981 @default.
• W4225316261 hasAuthorship W4225316261A5043112957 @default.
• W4225316261 hasAuthorship W4225316261A5053538488 @default.
• W4225316261 hasAuthorship W4225316261A5057140415 @default.
• W4225316261 hasAuthorship W4225316261A5065551581 @default.
• W4225316261 hasAuthorship W4225316261A5067905052 @default.
• W4225316261 hasAuthorship W4225316261A5074822109 @default.
• W4225316261 hasAuthorship W4225316261A5077468333 @default.
• W4225316261 hasConcept C119060515 @default.
• W4225316261 hasConcept C126322002 @default.
• W4225316261 hasConcept C126838900 @default.
• W4225316261 hasConcept C141071460 @default.
• W4225316261 hasConcept C143998085 @default.
• W4225316261 hasConcept C159110652 @default.
• W4225316261 hasConcept C2776909242 @default.
• W4225316261 hasConcept C3019894029 @default.
• W4225316261 hasConcept C71924100 @default.
• W4225316261 hasConcept C72563966 @default.
• W4225316261 hasConceptScore W4225316261C119060515 @default.
• W4225316261 hasConceptScore W4225316261C126322002 @default.
• W4225316261 hasConceptScore W4225316261C126838900 @default.
• W4225316261 hasConceptScore W4225316261C141071460 @default.
• W4225316261 hasConceptScore W4225316261C143998085 @default.
• W4225316261 hasConceptScore W4225316261C159110652 @default.
• W4225316261 hasConceptScore W4225316261C2776909242 @default.
• W4225316261 hasConceptScore W4225316261C3019894029 @default.
• W4225316261 hasConceptScore W4225316261C71924100 @default.
• W4225316261 hasConceptScore W4225316261C72563966 @default.
• W4225316261 hasIssue "4" @default.
• W4225316261 hasLocation W42253162611 @default.
• W4225316261 hasLocation W42253162612 @default.
• W4225316261 hasOpenAccess W4225316261 @default.
• W4225316261 hasPrimaryLocation W42253162611 @default.
• W4225316261 hasRelatedWork W2047967234 @default.
• W4225316261 hasRelatedWork W2061253854 @default.
• W4225316261 hasRelatedWork W2151531885 @default.

• next