{"id":{"repo_id":"brock","oai_identifier":"oai:brocku.scholaris.ca:10464/3187"},"canonical_url":"https://search.dev.ndltd.org/etd/brock/oai:brocku.scholaris.ca:10464/3187","repository":{"repo_id":"brock","name":"Brock University","base_url":"https://brocku.scholaris.ca/server/oai/request"},"display":{"title":"The relationship between body mass index and breast cancer recurrence/progression and breast cancer-specific death","abstract":"The aim of this study was to describe the nonlinear association between body mass index (BMI) and breast cancer outcomes and to determine whether BMI improves prediction of outcomes. A cohort of906 breast cancer patients diagnosed at Henry Ford Health System, Detroit (1985-1990) were studied. The median follow-up was 10 years. Multivariate logistic regression was used to model breast cancer recurrence/progression and breast cancer-specific death. Restricted cubic splines were used to model nonlinear effects. Receiver operator characteristic areas under the curves (ROC AUC) were used to evaluate prediction. BMI was nonlinearly associated with recurrence/progression and death (p= 0.0230 and 0.0101). Probability of outcomes increased with increase or decrease ofBMI away from 25. BMI splines were suggestive of improved prediction of death. The ROC AUCs for nested models with and without BMI were 0.8424 and 0.8331 (p= 0.08). I f causally associated, modifying patients BMI towards 25 may improve outcomes.","abstract_html":"The aim of this study was to describe the nonlinear association between body mass index (BMI) and breast cancer outcomes and to determine whether BMI improves prediction of outcomes. A cohort of906 breast cancer patients diagnosed at Henry Ford Health System, Detroit (1985-1990) were studied. The median follow-up was 10 years. Multivariate logistic regression was used to model breast cancer recurrence/progression and breast cancer-specific death. Restricted cubic splines were used to model nonlinear effects. Receiver operator characteristic areas under the curves (ROC AUC) were used to evaluate prediction. BMI was nonlinearly associated with recurrence/progression and death (p= 0.0230 and 0.0101). Probability of outcomes increased with increase or decrease ofBMI away from 25. BMI splines were suggestive of improved prediction of death. The ROC AUCs for nested models with and without BMI were 0.8424 and 0.8331 (p= 0.08). I f causally associated, modifying patients BMI towards 25 may improve outcomes.","abstract_has_math":false,"creators":["Tosevski, Cedomir"],"institution":"Brock University","degree_name":"M.Sc. Applied Health Sciences","degree_level":"Masters","degree_discipline":"Faculty of Applied Health Sciences","degree_department":"Applied Health Sciences Program","school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-03-08","date_published":"2011-03-08","updated_at":"2026-07-24T01:23:05Z","subjects":["Obesity -- Health aspects","Breast -- Cancer"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10464/3187","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Applied Health Sciences Program"]},{"key":"dc:creator","label":"Author","values":["Tosevski, Cedomir"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2011-03-08T19:11:45Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2011-03-08T19:11:45Z"]},{"key":"dc:date.issued","label":"Date","values":["2011-03-08"]},{"key":"dc:type","label":"Dc Type","values":["Electronic Thesis or Dissertation"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Faculty of Applied Health Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.Sc. 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A cohort of906 breast cancer patients diagnosed at Henry Ford Health System, Detroit (1985-1990) were studied. The median follow-up was 10 years. Multivariate logistic regression was used to model breast cancer recurrence/progression and breast cancer-specific death. Restricted cubic splines were used to model nonlinear effects. Receiver operator characteristic areas under the curves (ROC AUC) were used to evaluate prediction. BMI was nonlinearly associated with recurrence/progression and death (p= 0.0230 and 0.0101). Probability of outcomes increased with increase or decrease ofBMI away from 25. BMI splines were suggestive of improved prediction of death. The ROC AUCs for nested models with and without BMI were 0.8424 and 0.8331 (p= 0.08). I f causally associated, modifying patients BMI towards 25 may improve outcomes."]},{"key":"dc:title","label":"Title","values":["The relationship between body mass index and breast cancer recurrence/progression and breast cancer-specific death"]}]}],"canonical_facts":{"dc:contributor.department":["Applied Health Sciences Program"],"dc:creator":["Tosevski, Cedomir"],"dc:date.accessioned":["2011-03-08T19:11:45Z"],"dc:date.available":["2011-03-08T19:11:45Z"],"dc:date.issued":["2011-03-08"],"dc:description.abstract":["The aim of this study was to describe the nonlinear association between body mass index (BMI) and breast cancer outcomes and to determine whether BMI improves prediction of outcomes. A cohort of906 breast cancer patients diagnosed at Henry Ford Health System, Detroit (1985-1990) were studied. The median follow-up was 10 years. Multivariate logistic regression was used to model breast cancer recurrence/progression and breast cancer-specific death. Restricted cubic splines were used to model nonlinear effects. Receiver operator characteristic areas under the curves (ROC AUC) were used to evaluate prediction. BMI was nonlinearly associated with recurrence/progression and death (p= 0.0230 and 0.0101). Probability of outcomes increased with increase or decrease ofBMI away from 25. BMI splines were suggestive of improved prediction of death. The ROC AUCs for nested models with and without BMI were 0.8424 and 0.8331 (p= 0.08). I f causally associated, modifying patients BMI towards 25 may improve outcomes."],"dc:identifier.uri":["http://hdl.handle.net/10464/3187"],"dc:language.iso":["eng"],"dc:subject":["Obesity -- Health aspects","Breast -- Cancer"],"dc:title":["The relationship between body mass index and breast cancer recurrence/progression and breast cancer-specific death"],"dc:type":["Electronic Thesis or Dissertation"],"thesis:degree_discipline":["Faculty of Applied Health Sciences"],"thesis:degree_level":["Masters"],"thesis:degree_name":["M.Sc. Applied Health Sciences"],"thesis:institution_name":["Brock University"]},"updated_at":"2026-07-24T01:23:05Z"}