{"doi":"10.1016/j.jamcollsurg.2020.02.033","title":"Circumferential Resection Margin as a Hospital Quality Assessment Tool for Rectal Cancer Surgery","abstract":"BACKGROUND: Circumferential resection margin (CRM) status is an important predictor of outcomes after rectal cancer operation, and is influenced not only by operative technique, but also by incorporation of a multidisciplinary treatment strategy. This study sought to develop a risk-adjusted quality metric based on CRM status to assess hospital-level performance for rectal cancer operation. STUDY DESIGN: We conducted a retrospective observational cohort study of 58,374 patients with resected stage I to III rectal cancer within 1,303 hospitals who were identified from the National Cancer Database (2010 to 2015). The number of observed cases with a positive CRM (≤ 1 mm) was divided by the risk-adjusted expected number of cases with positive CRM to form the observed-to-expected (O/E) ratio. Secondary endpoint was overall survival. RESULTS: The overall rate of CRM positivity was 15.9%. Based on the O/E ratio for 1,139 hospitals, 147 (12.9%) and 103 (9.0%) were significantly worse and better performers, respectively. The majority of hospitals (n = 570) performed as expected. Positive CRMs using criteria of 0 mm and 0.1 to 1 mm were associated with a significantly shorter 5-year overall survival of 49% and 63.5% (hazard ratio 1.67; 95% CI, 1.57 to 1.76 and hazard ratio 1.19; 95% CI, 1.12 to 1.26) than negative CRM > 1 mm of 74.1% (all p < 0.001). CONCLUSIONS: CRM-based O/E ratio is a robust hospital-based quality measure for rectal cancer operation. It allows facilities to compare their performance with that of centers of similar characteristics and helps identify underperforming, at-risk, and high-performing centers. National quality-improvement initiatives for rectal cancer should focus on ensuring high-quality data collection and providing ready access to risk-adjusted comparative metrics.","journal":"Journal of the American College of Surgeons","year":2020,"id":70902,"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":18,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9525,"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":374744,"name":"Chung-Yuan Hu","orcid":"0000-0002-1246-6348","position":1,"is_corresponding":false},{"id":320948,"name":"Nader N. Massarweh","orcid":"0000-0001-7891-4134","position":2,"is_corresponding":false},{"id":375584,"name":"Nancy You","orcid":null,"position":3,"is_corresponding":false},{"id":374745,"name":"Ryan McCabe","orcid":"0000-0003-3752-6519","position":4,"is_corresponding":false},{"id":374746,"name":"David Dietz","orcid":"0000-0002-6927-9236","position":5,"is_corresponding":false},{"id":374747,"name":"Matthew A. Facktor","orcid":"0000-0002-8128-1996","position":6,"is_corresponding":false},{"id":374748,"name":"George J. Chang","orcid":"0000-0002-9758-5361","position":7,"is_corresponding":false},{"id":374743,"name":"Sameer H. Patel","orcid":"0000-0001-6442-1857","position":0,"is_corresponding":true}],"reference_count":22,"raw_metadata":null,"created_at":"2026-07-18T21:43:32.585486Z","pmid":"32142927","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":[]}