{"doi":"10.17615/9af2-7p11","title":"Frailty index developed from a cancer-specific geriatric assessment and the association with mortality among older adults with cancer","abstract":"Background: An objective measure is needed to identify frail older adults with cancer who are at increased risk for poor health outcomes. The primary objective of this study was to develop a frailty index from a cancer-specific geriatric assessment (GA) and evaluate its ability to predict all-cause mortality among older adults with cancer. Patients and Methods: Using a unique and novel data set that brings together GA data with cancer-specific and long-term mortality data, we developed the Carolina Frailty Index (CFI) from a cancer-specific GA based on the principles of deficit accumulation. CFI scores (range, 0-1) were categorized as robust (0-0.2), pre-frail (0.2-0.35), and frail (>0.35). The primary outcome for evaluating predictive validity was all-cause mortality. The Kaplan-Meier method and log-rank tests were used to compare survival between frailty groups, and Cox proportional hazards regression models were used to evaluate associations. Results: In our sample of 546 older adults with cancer, the median age was 72 years, 72% were women, 85% were white, and 47% had a breast cancer diagnosis. Overall, 58% of patients were robust, 24% were pre-frail, and 18% were frail. The estimated 5-year survival rate was 72% in robust patients, 58% in pre-frail patients, and 34% in frail patients (log-rank test, P<.0001). Frail patients had more than a 2-fold increased risk of all-cause mortality compared with robust patients (adjusted hazard ratio, 2.36; 95% CI, 1.51-3.68). Conclusions: The CFI was predictive of all-cause mortality in older adults with cancer, a finding that was independent of age, sex, cancer type and stage, and number of medical comorbidities. The CFI has the potential to become a tool that oncologists can use to objectively identify frailty in older adults with cancer.","journal":"UNC Libraries","year":2024,"id":498933,"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":0.883,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1345986,"name":"Greg Williams","orcid":"0000-0003-1955-8576","position":1,"is_corresponding":false},{"id":835145,"name":"K.A. Nyrop","orcid":null,"position":2,"is_corresponding":false},{"id":598312,"name":"Y. Chang","orcid":"0000-0002-9754-0825","position":3,"is_corresponding":false},{"id":803396,"name":"J.L. Lund","orcid":null,"position":4,"is_corresponding":false},{"id":1346567,"name":"H.K. Sanoff","orcid":null,"position":5,"is_corresponding":false},{"id":801409,"name":"A.M. Deal","orcid":null,"position":6,"is_corresponding":false},{"id":835142,"name":"H.B. Muss","orcid":null,"position":7,"is_corresponding":false},{"id":595712,"name":"Emily J. Guerard","orcid":null,"position":8,"is_corresponding":false},{"id":1346551,"name":"M. Pergolotti","orcid":null,"position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:09:45.971055Z","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":[]}