{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T11:17:28Z","timestamp":1777375048299,"version":"3.51.4"},"reference-count":28,"publisher":"Wiley","issue":"3-5","license":[{"start":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T00:00:00Z","timestamp":1770854400000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001349","name":"National Medical Research Council","doi-asserted-by":"publisher","award":["MOH\u2010001487"],"award-info":[{"award-number":["MOH\u2010001487"]}],"id":[{"id":"10.13039\/501100001349","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Prior event rate ratio (PERR) is a method shown to perform well in mitigating confounding and is gaining popularity in real\u2010world evidence research. However, it depends on several model assumptions. We propose an analytic strategy to correct biases arising from violation of two model assumptions, namely, population homogeneity and event\u2010independent treatment. We propose a reformulation of PERR estimation by embedding a treatment\u2010by\u2010period interaction term in the Andersen\u2010Gill model for recurrent event data, which is robust to bias arising from unobserved heterogeneity. Based on this model, we propose a set of methods to examine the presence of event\u2010dependent treatment and to correct the resultant bias. We evaluate the proposed methods by simulation and apply it to a de\u2010identified dataset on palliative care and emergency department visits in patients with advanced cancer. Simulation results showed that the proposed method could mitigate the two sources of bias in PERR. In the palliative care study, analysis by the Cox model showed that patients who had started receiving palliative care had higher incidence of emergency department visits than their match controls (hazard ratio 3.31; 95% confidence interval 2.78\u20133.94). Using PERR without the proposed bias control strategy indicated a 19% reduction of the incidence (0.81; 0.64\u20131.02). However, there was evidence of event\u2010dependent treatment. The proposed correction method showed no effect of palliative care on ED visits (1.00; 0.79\u20131.26). In conclusion, the proposed analytic strategy can control two sources of biases in the PERR approach. It enriches the armamentarium for real\u2010world evidence research.<\/jats:p>","DOI":"10.1002\/sim.70441","type":"journal-article","created":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T12:56:47Z","timestamp":1770901007000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Strategy to Control Biases in Prior Event Rate Ratio Method, With Application to Palliative Care in Patients With Advanced Cancer"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6526-1226","authenticated-orcid":false,"given":"Xiangmei","family":"Ma","sequence":"first","affiliation":[{"name":"Centre for Quantitative Medicine, Duke\u2010NUS Medical School National University of Singapore  Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0915-6007","authenticated-orcid":false,"given":"Grace Meijuan","family":"Yang","sequence":"additional","affiliation":[{"name":"Division of Supportive and Palliative Care National Cancer Centre Singapore  Singapore"},{"name":"Lien Centre for Palliative Care, Duke\u2010NUS Medical School National University of Singapore  Singapore"},{"name":"Programme in Health Services and Systems Research, Duke\u2010NUS Medical School National University of Singapore  Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8770-9968","authenticated-orcid":false,"given":"Qingyuan","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Division of Supportive and Palliative Care National Cancer Centre Singapore  Singapore"},{"name":"Data and Computational Science Core National Cancer Centre Singapore  Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0517-7625","authenticated-orcid":false,"given":"Yin Bun","family":"Cheung","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Duke\u2010NUS Medical School National University of Singapore  Singapore"},{"name":"Programme in Health Services and Systems Research, Duke\u2010NUS Medical School National University of Singapore  Singapore"},{"name":"Tampere Center for Child, Adolescent and Maternal Health Research Tampere University  Tampere Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,2,12]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2018.10136"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.23.02399"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.b81"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2020.03.007"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1183\/13993003.02795-2020"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1093\/cid\/ciab578"},{"issue":"1","key":"e_1_2_9_8_1","first-page":"481","article-title":"Estimating the Risk of Acute Kidney Injury Associated With Use of Diuretics and Renin Angiotensin Aldosterone System Inhibitors: A Population Based Cohort Study Using the Clinical Practice Research Datalink","volume":"20","author":"Scott J.","year":"2019","journal-title":"BioMed Central Nephrology"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2022.06.018"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0275642"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780071105"},{"key":"e_1_2_9_12_1","volume-title":"Survival Analysis Using SAS: A Practical Guide","author":"Allison P. 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