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A Curated Cancer Clinical Outcomes Database (C3OD) for accelerating patient recruitment in cancer clinical trials.

ABSTRACT: Data used to determine patient eligibility for cancer clinical trials often come from disparate sources that are typically maintained by different groups within an institution, use differing technologies, and are stored in different formats. Collecting data and resolving inconsistencies across sources increase the time it takes to screen eligible patients, potentially delaying study completion. To address these challenges, the Biostatistics and Informatics Shared Resource at The University of Kansas Cancer Center developed the Curated Cancer Clinical Outcomes Database (C3OD). C3OD merges data from the electronic medical record, tumor registry, bio-specimen and data registry, and allows querying through a single unified platform. By centralizing access and maintaining appropriate controls, C3OD allows researchers to more rapidly obtain detailed information about each patient in order to accelerate eligibility screening. This case report describes the design of this informatics platform as well as initial assessments of its reliability and usability.

SUBMITTER: Mudaranthakam DP

PROVIDER: S-EPMC6241508 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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A Curated Cancer Clinical Outcomes Database (C3OD) for accelerating patient recruitment in cancer clinical trials.

Mudaranthakam Dinesh Pal DP Thompson Jeffrey J Hu Jinxiang J Pei Dong D Chintala Shanthan Reddy SR Park Michele M Fridley Brooke L BL Gajewski Byron B Koestler Devin C DC Mayo Matthew S MS

JAMIA open 20180710 2

Data used to determine patient eligibility for cancer clinical trials often come from disparate sources that are typically maintained by different groups within an institution, use differing technologies, and are stored in different formats. Collecting data and resolving inconsistencies across sources increase the time it takes to screen eligible patients, potentially delaying study completion. To address these challenges, the Biostatistics and Informatics Shared Resource at The University of Ka ...[more]

PMID: 30474074

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Project description:BackgroundRecruitment for clinical trials continues to be a challenge, as patient recruitment is the single biggest cause of trial delays. Around 80% of trials fail to meet the initial enrollment target and timeline, and these delays can result in lost revenue of as much as US $8 million per day for drug developing companies.ObjectiveThis study aimed to conduct a systematic review and meta-analysis examining the effectiveness of online recruitment of participants for clinical trials compared with traditional in-clinic/offline recruitment methods.MethodsData on recruitment rates (the average number of patients enrolled in the study per month and per day of active recruitment) and conversion rates (the percentage of participants screened who proceed to enroll into the clinical trial), as well as study characteristics and patient demographics were collected from the included studies. Differences in online and offline recruitment rates and conversion rates were examined using random effects models. Further, a nonparametric paired Wilcoxon test was used for additional analysis on the cost-effectiveness of online patient recruitment. All data analyses were conducted in R language, and P<.05 was considered significant.ResultsIn total, 3861 articles were screened for inclusion. Of these, 61 studies were included in the review, and 23 of these were further included in the meta-analysis. We found online recruitment to be significantly more effective with respect to the recruitment rate for active days of recruitment, where 100% (7/7) of the studies included had a better online recruitment rate compared with offline recruitment (incidence rate ratio [IRR] 4.17, P=.04). When examining the entire recruitment period in months we found that 52% (12/23) of the studies had a better online recruitment rate compared with the offline recruitment rate (IRR 1.11, P=.71). For cost-effectiveness, we found that online recruitment had a significantly lower cost per enrollee compared with offline recruitment (US $72 vs US $199, P=.04). Finally, we found that 69% (9/13) of studies had significantly better offline conversion rates compared with online conversion rates (risk ratio 0.8, P=.02).ConclusionsTargeting potential participants using online remedies is an effective approach for patient recruitment for clinical research. Online recruitment was both superior in regard to time efficiency and cost-effectiveness compared with offline recruitment. In contrast, offline recruitment outperformed online recruitment with respect to conversion rate.

Project description:BackgroundClinical trial participation can improve overall survival and mitigate healthcare disparities for gynecologic cancer patients in low-volume community centers. This study aimed to assess the effectiveness of a centrally regulated but administratively decentralized electronic screening log system to identify eligible patients across a large catchment area for a National Cancer Institute (NCI)-designated cancer center's open clinical trials.MethodsElectronic screening log data collected between 2014 and 2021 from ten community partner sites in a single NCI-designated cancer center's catchment area were reviewed retrospectively. Clinical factors assessed included cancer site, primary versus recurrent disease status, and histology. Identification efficiency (the ratio of patients screened identified with an available trial) was calculated. Identification inefficiencies (failures to identify patients with a potentially relevant trial) were assessed, and etiologies were characterized.ResultsAcross ten community partner sites, 492 gynecologic cancer patients were screened for seven open clinical trials during the study period. This included 170 (34.5 %) ovarian cancer patients, 156 (31.7 %) endometrial cancer patients, and 119 (24.2 %) cervical cancer patients. Over 40 % had advanced stage disease, and 10.6 % had recurrent disease. Only three patients were identified as having a relevant open trial; none ultimately enrolled due to not meeting trial eligibility criteria. An additional 2-52 patients were retrospectively found to have a relevant trial available despite not being identified as such within the electronic screening log system. Up to 14.4 % of patients had one or more missing minimum data elements that hindered full evaluation of clinical trial availability. Re-screening patients when new trials open may identify 12-15 additional patients per recurrent disease trial.ConclusionsAn electronic screening log system can increase awareness of gynecologic oncology clinical trials at a NCI-designated cancer center's community partner sites. However, it is inadequate as a single intervention to increase clinical trial enrollment. Providing adequate support staff, documenting clinical factors consistently, re-screening patients at relevant intervals, and coordinating with central study personnel may increase its utility.

Dataset Information

A Curated Cancer Clinical Outcomes Database (C3OD) for accelerating patient recruitment in cancer clinical trials.

Publications

A Curated Cancer Clinical Outcomes Database (C3OD) for accelerating patient recruitment in cancer clinical trials.

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