{"id":"W2989903818","doi":"10.1007/s40273-019-00845-x","title":"Evaluating Partitioned Survival and Markov Decision-Analytic Modeling Approaches for Use in Cost-Effectiveness Analysis: Estimating and Comparing Survival Outcomes","year":2019,"lang":"en","type":"article","venue":"PharmacoEconomics","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bristol-Myers Squibb (Canada)","funders":"Bristol-Myers Squibb","keywords":"Markov model; Survival analysis; Everolimus; Medicine; Quality of Life Research; Markov chain; Quality-adjusted life year; Statistics; Time horizon; Cost effectiveness; Mathematics; Oncology; Public health; Mathematical optimization","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04766129,0.002039025,0.001968734,0.002434303,0.0003646481,0.00182783,0.001618668,0.001503396,0.003507008],"category_scores_gemma":[0.1325021,0.00116765,0.004588799,0.001057679,0.0007338612,0.001978289,0.002112636,0.00196771,0.0002267837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00383435,"about_ca_system_score_gemma":0.003964727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008316549,"about_ca_topic_score_gemma":0.005329793,"domain_scores_codex":[0.9634022,0.03354184,0.0007300244,0.0007433349,0.001244939,0.0003375605],"domain_scores_gemma":[0.807049,0.1818089,0.00582777,0.001807173,0.002824359,0.0006827582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002248508,0.0003121751,0.006844937,0.0005951569,0.002204732,0.00005378227,0.0001416188,0.9445749,0.0001759443,0.009757951,0.0003496677,0.03274059],"study_design_scores_gemma":[0.000362317,0.0009051692,0.0009569513,0.0001485513,0.0004222867,0.0000285904,0.00004021854,0.9877626,0.0001380468,0.008884404,0.0003255343,0.00002538231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3084962,0.00544928,0.6750721,0.001856307,0.0001701232,0.00292961,0.001597292,0.0003864555,0.0040426],"genre_scores_gemma":[0.8228574,0.00165791,0.1707776,0.0004391999,0.00007197563,0.002890018,0.0007481434,0.0000586663,0.0004990204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04766129,"threshold_uncertainty_score":0.25206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6806953585897056,"score_gpt":0.5257657187454701,"score_spread":0.1549296398442356,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}