{"id":{"repo_id":"tdl","oai_identifier":"oai:tdl-ir.tdl.org:2152.3/11585"},"canonical_url":"https://search.dev.ndltd.org/etd/tdl/oai:tdl-ir.tdl.org:2152.3/11585","repository":{"repo_id":"tdl","name":"Texas Digital Library","base_url":"https://tdl-ir.tdl.org/server/oai/request"},"display":{"title":"Data Mining for Signal Detection of Targeted Therapy Related Drug Toxicity in Breast Cancer Patients","abstract":"Application of signal detection methods using claims data can improve post-marketing drug surveillance. The aim of this study is to compare two routinely used approaches, the proportional reporting ratio (PRR) and Gamma Poisson Shrinker (GPS) with a tree-based scan statistic (TBSS). Using data from the Texas Cancer Registry and Surveillance, Epidemiology and End Results linked to Medicare from 2010-2014 we identified 8,949 patients with breast cancer treated with chemotherapy and 2,542 patients treated with trastuzumab in addition to chemotherapy. Inpatient and outpatient visits up to 1 year from start of therapy were used to identify adverse events (AEs). For each method two signaling thresholds were evaluated. Across all methods we found a total of 34 signals associated with use of trastuzumab. Clinical review determined that most identified signals represented known AEs or confounding. GPS on the highest signaling threshold failed to detect a well-established AE when time of follow-up was less than 6 months. Overall there was considerable agreement between methods with GPS being the most conservative. PRR and TBSS may be more appropriate in exploratory drug safety studies using this dataset.","abstract_html":"Application of signal detection methods using claims data can improve post-marketing drug surveillance. The aim of this study is to compare two routinely used approaches, the proportional reporting ratio (PRR) and Gamma Poisson Shrinker (GPS) with a tree-based scan statistic (TBSS). Using data from the Texas Cancer Registry and Surveillance, Epidemiology and End Results linked to Medicare from 2010-2014 we identified 8,949 patients with breast cancer treated with chemotherapy and 2,542 patients treated with trastuzumab in addition to chemotherapy. Inpatient and outpatient visits up to 1 year from start of therapy were used to identify adverse events (AEs). For each method two signaling thresholds were evaluated. Across all methods we found a total of 34 signals associated with use of trastuzumab. Clinical review determined that most identified signals represented known AEs or confounding. GPS on the highest signaling threshold failed to detect a well-established AE when time of follow-up was less than 6 months. Overall there was considerable agreement between methods with GPS being the most conservative. PRR and TBSS may be more appropriate in exploratory drug safety studies using this dataset.","abstract_has_math":false,"creators":["Polychronopoulou, Efstathia"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-27T21:19:13Z","subjects":["data mining, adverse events, pharmacovigilance"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2152.3/11585","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Polychronopoulou, Efstathia"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-08-05T15:07:46Z","2026-06-09T21:29:51Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-08-05T15:07:46Z"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["data mining, adverse events, pharmacovigilance"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2152.3/11585"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2152.3/11585"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Application of signal detection methods using claims data can improve post-marketing drug surveillance. The aim of this study is to compare two routinely used approaches, the proportional reporting ratio (PRR) and Gamma Poisson Shrinker (GPS) with a tree-based scan statistic (TBSS). Using data from the Texas Cancer Registry and Surveillance, Epidemiology and End Results linked to Medicare from 2010-2014 we identified 8,949 patients with breast cancer treated with chemotherapy and 2,542 patients treated with trastuzumab in addition to chemotherapy. Inpatient and outpatient visits up to 1 year from start of therapy were used to identify adverse events (AEs). For each method two signaling thresholds were evaluated. Across all methods we found a total of 34 signals associated with use of trastuzumab. Clinical review determined that most identified signals represented known AEs or confounding. GPS on the highest signaling threshold failed to detect a well-established AE when time of follow-up was less than 6 months. Overall there was considerable agreement between methods with GPS being the most conservative. PRR and TBSS may be more appropriate in exploratory drug safety studies using this dataset."]},{"key":"dc:title","label":"Title","values":["Data Mining for Signal Detection of Targeted Therapy Related Drug Toxicity in Breast Cancer Patients"]}]}],"canonical_facts":{"dc:creator":["Polychronopoulou, Efstathia"],"dc:date.accessioned":["2022-08-05T15:07:46Z","2026-06-09T21:29:51Z"],"dc:date.available":["2022-08-05T15:07:46Z"],"dc:description.abstract":["Application of signal detection methods using claims data can improve post-marketing drug surveillance. The aim of this study is to compare two routinely used approaches, the proportional reporting ratio (PRR) and Gamma Poisson Shrinker (GPS) with a tree-based scan statistic (TBSS). Using data from the Texas Cancer Registry and Surveillance, Epidemiology and End Results linked to Medicare from 2010-2014 we identified 8,949 patients with breast cancer treated with chemotherapy and 2,542 patients treated with trastuzumab in addition to chemotherapy. Inpatient and outpatient visits up to 1 year from start of therapy were used to identify adverse events (AEs). For each method two signaling thresholds were evaluated. Across all methods we found a total of 34 signals associated with use of trastuzumab. Clinical review determined that most identified signals represented known AEs or confounding. GPS on the highest signaling threshold failed to detect a well-established AE when time of follow-up was less than 6 months. Overall there was considerable agreement between methods with GPS being the most conservative. PRR and TBSS may be more appropriate in exploratory drug safety studies using this dataset."],"dc:identifier":["https://hdl.handle.net/2152.3/11585"],"dc:identifier.uri":["https://hdl.handle.net/2152.3/11585"],"dc:subject":["data mining, adverse events, pharmacovigilance"],"dc:title":["Data Mining for Signal Detection of Targeted Therapy Related Drug Toxicity in Breast Cancer Patients"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:19:13Z"}