{"id":16184,"date":"2023-04-04T10:56:00","date_gmt":"2023-04-04T14:56:00","guid":{"rendered":"https:\/\/www.ices.on.ca\/?post_type=journal_article&p=16184"},"modified":"2023-06-28T10:08:04","modified_gmt":"2023-06-28T14:08:04","slug":"is-cancer-stage-data-missing-completely-at-random-a-report-from-a-large-population-based-cohort-of-non-small-cell-lung-cancer","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/is-cancer-stage-data-missing-completely-at-random-a-report-from-a-large-population-based-cohort-of-non-small-cell-lung-cancer\/","title":{"rendered":"Is cancer stage data missing completely at random? A report from a large population-based cohort of non-small cell lung cancer"},"content":{"rendered":"

Introduction<\/strong> \u2014 Population-based datasets are often used to estimate changes in utilization or outcomes of novel therapies. Inclusion or exclusion of unstaged patients may impact on interpretation of these studies.<\/p>\n

Methods<\/strong> \u2014 A large population-based dataset in Ontario, Canada of non-small cell lung cancer patients was examined to evaluate the characteristics and outcomes of unstaged patients compared to staged patients. Multivariable Poisson regression was used to evaluate differences in patient-level characteristics between groups. Kaplan-Meier estimates of survival and log-rank statistics were utilized.<\/p>\n

Results<\/strong> \u2014 In our Ontario cohort of 51,152 patients with NSCLC, 11.2% (n=5,707) were unstaged, and there was evidence that stage data was not missing completely at random. Those without assigned stage were more likely than staged patients to be older (RR [95%CI]), (70-79 vs. 20-59: 1.51 [1.38-1.66]; 80+ vs. 20-59: 2.87 [2.62-3.15]), have a higher comorbidity index (Score 1-2 vs 0: 1.19 [1.12-1.27]; 3 vs. 0: 1.49 [1.38-1.60]), and have a lower socioeconomic class (4 vs. 1 (lowest): 0.91 [0.84-0.98]; 5 vs. 1 (lowest): 0.89 [0.83-0.97]). Overall survival of unstaged patients suggested a mixture of early and advanced stage, but with a large proportion that are probably stage IV patients with more rapid death than those with reported stage IV disease.<\/p>\n

Conclusion<\/strong> \u2014 In this case study, evaluation of stage-specific healthcare utilization and outcomes for staged patients with stage IV disease at the population level may have a bias as a distinct subset of stage IV patients with rapid death are likely among those without a documented stage in administrative data.<\/p>\n","protected":false},"excerpt":{"rendered":"

Introduction \u2014 Population-based datasets are often used to estimate changes in utilization or outcomes of novel therapies. Inclusion or exclusion of unstaged patients may impact on interpretation of these studies. Methods \u2014 A large population-based dataset in Ontario, Canada of non-small cell lung cancer patients was examined to evaluate the characteristics and outcomes of unstaged […]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[38,59,65],"migration-helper-qa-sample-set":[],"class_list":["post-16184","journal_article","type-journal_article","status-publish","hentry","topic-cancer-and-cancer-screening","topic-data-science","topic-statistics"],"acf":{"citation":"Robinson AG, Nguyen P, Goldie CL, Jalink M, Hanna TP. Front Oncol<\/em>. 2023; 13:1146053. 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