{"id":"W4387115048","doi":"10.1001/jamaoncol.2023.3867","title":"Anti-TIGIT Antibody Tiragolumab Alone or With Atezolizumab in Patients With Advanced Solid Tumors","year":2023,"lang":"en","type":"article","venue":"JAMA Oncology","topic":"Cancer Immunotherapy and Biomarkers","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Roche (Canada); Princess Margaret Cancer Centre","funders":"Daiichi Sankyo Europe; National Center for Advancing Translational Sciences; National Cancer Institute; EMD Serono; Genentech; European Society for Medical Oncology; Servier; Yonsei University; MacroGenics; LG Chem; Regeneron Pharmaceuticals; BeiGene; F. Hoffmann-La Roche; Handok; Gilead Sciences; Yuhan; Eli Lilly and Company; AstraZeneca; Celgene; TG Therapeutics; Pfizer","keywords":"Medicine; Atezolizumab; Internal medicine; TIGIT; Tolerability; Oncology; Clinical endpoint; Clinical trial; Phases of clinical research; Antibody; Adverse effect; Immunology; Pembrolizumab; Immunotherapy; Cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001545184,0.0004473044,0.001461752,0.0002809201,0.0001786402,0.0005013692,0.000339439,0.0005428536,0.001143599],"category_scores_gemma":[0.001323426,0.0002497916,0.0009996883,0.0003640759,0.0004039988,0.0004692699,0.0001736297,0.001194036,0.0002370808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005012467,"about_ca_system_score_gemma":0.0008152277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003910018,"about_ca_topic_score_gemma":0.001298951,"domain_scores_codex":[0.9995884,0.0002150453,0.00003663544,0.00005474586,0.00004872403,0.00005650701],"domain_scores_gemma":[0.9992879,0.0002165184,0.0002410242,0.00004185354,0.00004368463,0.0001690371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.6957657,0.01392051,0.0569133,0.00213464,0.002440773,0.0004374327,0.0001971404,0.002405356,0.02450963,0.000218196,0.003034393,0.1980229],"study_design_scores_gemma":[0.3589756,0.5064206,0.1176562,0.0001894693,0.002084052,0.0008301756,0.0001021404,0.003079568,0.005055963,0.000345399,0.005224141,0.00003680017],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917927,0.006102569,0.0002411372,0.0002309578,0.00007319661,0.000321938,0.0002381963,0.00002326879,0.0009759485],"genre_scores_gemma":[0.9969382,0.001418406,0.0004079793,0.0002621069,0.0000900345,0.0002298493,0.0002983859,0.000003671248,0.000351252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001545184,"threshold_uncertainty_score":0.008171856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0124915111144519,"score_gpt":0.3158602043763073,"score_spread":0.3033686932618554,"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."}}