{"doi":"10.3414/me0450","title":"Flexible Modeling of Malignant Melanoma Survival","abstract":"<jats:title>Summary</jats:title><jats:p>\n          \n            Objectives:\n           This paper compares the diagnostic capabilities of flexible ensemble methods modeling the survival time of melanoma patients in comparison to the well established proportional hazards model. Both a random forest type algorithm for censored data as well as a model combination of the proportional hazards model with recursive partitioning are investigated.</jats:p><jats:p>\n          \n            Methods:\n          Benchmark experiments utilizing the integrated Brier score as a measure for goodness of prediction are the basis of the performance assessment for all competing algorithms. For the purpose of comparing regression relationships represented by the models under test, we describe fitted conditional survival functions by a univariate measure derived from the area under the curve. Based on this measure, we adapt a visualization technique useful for the inspection and comparison of model fits.</jats:p><jats:p>\n          \n            Results:\n           For the data of malignant melanoma patients the predictive performance of the competing models is on par, allowing for a fair comparison of the fitted relationships. Newly introduced MODplots visualize differences in the fitting structure of the underlying models.</jats:p><jats:p>\n          \n            Conclusion:\n           The paper provides a framework for comparing the predictive and diagnostic performance of a parametric, a non-parametric and a combined approach.</jats:p>","journal":"Methods of Information in Medicine","year":2008,"id":677399,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1769960,"name":"A. Pfahlberg","orcid":null,"position":1,"is_corresponding":false},{"id":1530287,"name":"O. Gefeller","orcid":null,"position":2,"is_corresponding":false},{"id":1769961,"name":"T. Hothorn","orcid":null,"position":3,"is_corresponding":false},{"id":1769958,"name":"K. T. Eckel","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Flexible Modeling of Malignant Melanoma Survival","abstract":"<jats:title>Summary</jats:title><jats:p>\n          \n            Objectives:\n           This paper compares the diagnostic capabilities of flexible ensemble methods modeling the survival time of melanoma patients in comparison to the well established proportional hazards model. Both a random forest type algorithm for censored data as well as a model combination of the proportional hazards model with recursive partitioning are investigated.</jats:p><jats:p>\n          \n            Methods:\n          Benchmark experiments utilizing the integrated Brier score as a measure for goodness of prediction are the basis of the performance assessment for all competing algorithms. For the purpose of comparing regression relationships represented by the models under test, we describe fitted conditional survival functions by a univariate measure derived from the area under the curve. Based on this measure, we adapt a visualization technique useful for the inspection and comparison of model fits.</jats:p><jats:p>\n          \n            Results:\n           For the data of malignant melanoma patients the predictive performance of the competing models is on par, allowing for a fair comparison of the fitted relationships. Newly introduced MODplots visualize differences in the fitting structure of the underlying models.</jats:p><jats:p>\n          \n            Conclusion:\n           The paper provides a framework for comparing the predictive and diagnostic performance of a parametric, a non-parametric and a combined approach.</jats:p>","is_dataset_classified":null,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"18213427","pmcid":null,"openalex_id":"https://openalex.org/W2154851274","authors":[],"funders":[],"total_grants":0,"fwci":0.2887,"citation_percentile":0.65458979,"influential_citations":0,"citation_trend":[{"year":2014,"count":1},{"year":2025,"count":1}],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://www.thieme-connect.de/products/ejournals/pdf/10.3414/ME0450.pdf","host_type":"publisher"},{"url":"https://doi.org/10.3414/me0450","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/18213427","host_type":"repository"}],"fields_of_study":["Statistical Methods and Inference","Cutaneous Melanoma Detection and Management","Statistical Methods and Bayesian Inference"],"mesh_terms":["Adult","Algorithms","Female","Humans","Male","Melanoma","Middle Aged","Models, Biological","Prognosis","Models, Statistical","Proportional Hazards Models","Benchmarking"],"keywords":["Univariate","Brier score","Computer science","Proportional hazards model","Measure (data warehouse)","Benchmark (surveying)","Recursive partitioning","Parametric model","Goodness of fit","Data mining","Parametric statistics","Statistics","Artificial intelligence","Machine learning","Mathematics","Multivariate statistics"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Life in Land"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-17T04:04:48.360533Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}