{"doi":"10.1200/jco.2020.38.4_suppl.488","title":"IGF-1 Child-Turcotte-Pugh score as a predictor of overall survival to therapy in CTP-A, BCLC stage C patients with advanced hepatocellular carcinoma.","abstract":"488 Background: Child-Turcotte-Pugh (CTP) A is the standard population for active HCC therapy. The IGF-CTP score, comprises levels of type 1 insulin-like growth factor (IGF-1), bilirubin, INR, and albumin, significantly improved the prediction of overall survival (OS) in recently published studies. Our current study aimed to investigate the accuracy of the IGF-CTP score in predicting OS in HCC Child-Pugh A patients (pts) treated with local and/or systemic therapies (tx). The overall hypothesis is that the IGF-CTP score can further distinguish CP-A pts in terms of overall survival, PFS. Methods: Between 2014 and 2018, a total of 274 pts with new advanced HCC BCLC stage who had available baseline plasma IGF-1 level were retrospectively enrolled. Clinicopathologic features and treatment history were collected. We calculated IGF-CTP scores, used Kaplan-Meier method and log rank test to estimate and compare time to event outcomes between subgroups of patients. Results: 198 pts were CTP Class A, 209 patient underwent systemic tx, 65 underwent local tx [see table]; 161 were re-classified as IGF-CTP-A with a median OS of 16.09 months (95% CI = 13.06 to 23.29 months) (p <0.0001), whereas 37 patients were reclassified as intermediate risk (IGF-CTP-B) and had significantly shorter OS of 10.66 months (95% CI = 5.49 to 26.51) (p <0.0001). Conclusions: The results of this study support our biologically-driven hypothesis that IGF-CTP score is predictive of overall survival to therapy in advanced HCC treated with local and/or systemic therapy. Among HCC pts with CTP-A class, some are reclassified as IGF-CP-B/C and were found to have significantly poorer prognosis in terms of shorter OS. Future validation of the predictive ability of our IGF-1 score may lead to adopting it as a stratification tool in clinical trials as well as to predict HCC outcome and guide therapy decision in routine practice. [Table: see text]","journal":"Journal of Clinical Oncology","year":2020,"id":128836,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9598,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":573502,"name":"Aliya Qayyum","orcid":"0000-0003-1590-9041","position":1,"is_corresponding":false},{"id":420932,"name":"Manal M. Hassan","orcid":"0000-0002-8413-449X","position":2,"is_corresponding":false},{"id":419794,"name":"Lianchun Xiao","orcid":"0000-0003-0972-2766","position":3,"is_corresponding":false},{"id":238100,"name":"Dan G. Duda","orcid":"0000-0001-7065-8797","position":4,"is_corresponding":false},{"id":573503,"name":"Rikita Hatia","orcid":"0000-0003-2591-5963","position":5,"is_corresponding":false},{"id":573504,"name":"Sunyoung S. Lee","orcid":"0000-0002-5954-5991","position":6,"is_corresponding":false},{"id":395090,"name":"Robert A. Wolff","orcid":"0000-0002-6614-1610","position":7,"is_corresponding":false},{"id":579535,"name":"Roberto Carmagnani Pestana","orcid":"0000-0002-1141-7608","position":8,"is_corresponding":false},{"id":261811,"name":"Jeffrey S. Morris","orcid":"0000-0002-8520-6088","position":9,"is_corresponding":false},{"id":368861,"name":"James C. Yao","orcid":"0000-0002-1875-3962","position":10,"is_corresponding":false},{"id":473838,"name":"Hesham M. Amin","orcid":"0000-0002-7973-6699","position":11,"is_corresponding":false},{"id":54196,"name":"Ahmed O. Kaseb","orcid":"0000-0002-9491-0587","position":12,"is_corresponding":false},{"id":580094,"name":"Yehia I. Abugabal","orcid":null,"position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-18T23:15:42.522809Z","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":[]}