Cancer Research Network Sites Research Articles

Improvement Initiative to Develop and Implement a Tool for Detecting Drug-Drug Interactions During Oncology Clinical Trial Enrollment Eligibility Screening.

Screening subjects for drug-drug interactions (DDIs) before enrollment in oncology clinical trials is integral to ensuring safety, but standard procedures or tools are not readily available to screen DDI in this setting. Our objectives were to develop a DDI screening tool for use during oncology clinical trial enrollment and to test usability in single-center and multicenter pilot studies. A multistage approach was used for this quality improvement intervention. Semistructured interviews with individuals responsible for DDI screening were conducted to develop a prototype tool. The tool was used for screening DDI in subjects enrolling in National Clinical Trials Network trials of commercially available agents during a single-center 3-month pilot. Improvements were made, and a 3-month multicenter pilot was conducted at volunteer SWOG Cancer Research Network sites. Participants were surveyed to determine tool usability and efficiency. A tool was developed from semistructured interviews. A critical feature was reporting which medications had specific pharmacokinetic and pharmacodynamic characteristics including transporter and cytochrome P450 substrates, inhibitors, or inducers and QT prolongation. In the 12-site study, average (SD) DDI screening time for each patient decreased by 15.7 (10.2) minutes (range, 3-35 minutes; P < 0.001). Users reported the tool highly usable, with >90% agreeing with all positive usability characterizations and disagreeing with all negative complexity characterizations. A DDI screening tool for oncology clinical trial enrollment was created and its usability confirmed. Further testing with more diverse investigator sites and study drugs during eligibility screening is warranted to improve safety and data accuracy within clinical trials.

Adjuvant endocrine therapy for breast cancer patients: impact of a health system outreach program to improve adherence.

Reports suggest that up to 50% of women with hormone receptor-positive (HR+) breast cancer (BC) do not complete the recommended 5years of adjuvant endocrine therapy (AET). We examined the impact of an outreach program at Kaiser Permanente Northern California (KPNC) on adherence and discontinuation of AET among patients who initiated AET. We assembled a retrospective cohort of all KPNC patients diagnosed with HR+, stage I-III BC initiating AET before (n = 4287) and after (n = 3580) implementation of the outreach program. We compared adherence proportions and discontinuation rates before and after program implementation, both crude and adjusted for age, race/ethnicity, education, income, and stage. We conducted a pooled analysis of data from six Cancer Research Network (CRN) sites that had not implemented programs for improving AET adherence, using identical methods and time periods, to assess possible secular trends. In the pre-outreach period, estimated adherence in years 1, 2, and 3 following AET initiation was 75.2%, 71.0%, and 67.3%; following the outreach program, the estimates were 79.4%, 75.6%, and 72.2% (p-values < .0001 for pairwise comparisons). Results were comparable after adjusting for clinical and demographic factors. The estimated cumulative incidence of discontinuation was 0.22 (0.21-0.24) and 0.18 (0.17-0.19) at 3 years for pre- and post-outreach groups (p-value < .0001). We found no evidence of an increase in adherence between the study periods at the CRN sites with no AET adherence program. Adherence and discontinuation after AET initiation improved modestly following implementation of the outreach program.

Monitoring Lung Cancer Screening Use and Outcomes at Four Cancer Research Network Sites.

Lung cancer screening registries can monitor screening outcomes and improve quality of care. To describe nascent lung cancer screening programs and share efficient data collection approaches for mandatory registry reporting in four integrated health care systems of the National Cancer Institute-funded Cancer Research Network. We documented the distinctive characteristics of lung cancer screening programs, and we provide examples of strategies to facilitate data collection and describe early challenges and possible solutions. In addition, we report preliminary data on use and outcomes of screening with low-dose computed tomography at each of the participating sites. Programs varied in approaches to confirming patient eligibility, ordering screening low-dose computed tomographic scans, and coordinating follow-up care. Most data elements were collected from structured fields in electronic health records, but sites also made use of standardized order templates, local procedure codes, identifiable hashtags in radiology reports, and natural language processing algorithms. Common challenges included incomplete documentation of tobacco smoking history, difficulty distinguishing between scans performed for screening versus diagnosis or surveillance, and variable adherence with use of standardized templates. Adherence with eligibility criteria as well as the accuracy and completeness of data collection appeared to depend at least partly on availability of personnel and other resources to support the successful implementation of screening. To maximize the effectiveness of lung cancer screening, minimize the burden of data collection, and facilitate research and quality improvement, clinical workflow and information technology should be purposefully designed to ensure that patients meet eligibility criteria and receive appropriate follow-up testing.

Adolescent and Young Adult Cancer Data in the Cancer Research Network

Background: Cancer is the leading cause of disease-related death among U.S. persons aged 15–39 years. Certain cancers are more common in this adolescent/young adult (AYA) population than in younger children or older adults. Research supported by initiatives like the Cancer Research Network (CRN) is needed to address late effects of cancer and its treatments among AYA survivors. The CRN consortium is funded by the National Cancer Institute to support cancer research at a subset of Health Care Systems Research Network sites. The data collected and maintained by CRN sites facilitate a variety of AYA cancer research opportunities.

Survival after recurrence of stage I–III breast, colorectal, or lung cancer

BackgroundThe experiences of patients with recurrent cancer are assumed to reflect those of patients with de novo stage IV disease; yet, little is truly known because most registries lack recurrence status. Using two databases with excellent recurrence and death information, we examined determinants of survival duration after recurrence of breast (BC), colorectal (CRC), and lung cancers (LC). MethodsRecurrence status was abstracted from the medical records of patients who participated in the Cancer Care Outcomes Research and Surveillance study and who received care at two Cancer Research Network sites—the Colorado and Northwest regions of Kaiser Permanente. The analysis included 1653 patients who developed recurrence after completing definitive therapy for stages I–III cancer. Multivariable modeling identified independent determinants of survival duration after recurrence, controlling for other factors. ResultsThrough 60 months’ average follow-up, survival after recurrence for BC, CRC, and LC were 28.4, 23.1 and 16.1 months, respectively. Several factors were independently associated with shorter survival for all three cancers, including higher initial stage (III vs. I: BC −9.9 months; CRC −6.9 months; LC −7.4 months; P≤0.01). Factors associated with shorter survival for selected cancers included: distant/regional recurrence for BC and CRC; current/former smoker for LC; high grade for CRC; and <4-year time-to-recurrence for BC. ConclusionsInitial stage predicts survival duration after recurrence, whereas time-to-recurrence usually does not. The impact of biologic characteristics (e.g., grade, hormone-receptor status) on survival duration after recurrence needs further study. Predictors of survival duration after recurrence may help facilitate patient decision-making.

Development of Data Infrastructure to Monitor Lung Cancer Screening Use and Outcomes in Four Cancer Research Network Sites

Development of Data Infrastructure to Monitor Lung Cancer Screening Use and Outcomes in Four Cancer Research Network Sites

PC-FACS

PC-FACS

PS1-33: Cancer Screening Guideline Development, Implementation and Dissemination: Connection Points for Researchers and Health Care Delivery Systems for Comparative Effectiveness Research

Diana Buist1, Leah Tuzzio1, Robert Greenlee2, Terry Field3, Andrew Williams4, Sheila Weinmann5, Natasha Stout6, Aruna Kamineni1 and Chyke Doubeni3 1Group Health Cooperative 2Marshfield Clinic 3Meyers Primary Care Institute/University of Massachusetts Medical School 4Kaiser Permanente Hawaii 5Kaiser Permanente Northwest 6Harvard Pilgrim Health Care Institute, Harvard Medical School

C-C4-02: Using a Natural Language Processor to Remove All Elements of Personal Health Information (PHI) to Deidentify Clinical Annotations for the Specimen Retrieval System (SRS)

PHI in HMORN medical records must be systematically removed prior to use and sharing data with co-investigators at other institutions. The problem is particularly acute when one needs to link clinical and follow-up data with pathologic specimens from cancer patients in studies of prognostic and predictive tumor markers. Natural language processing (NLP) can be customized to identify and remove PHI in selected clinical records by substituting nonsense characters. Such a process of deidentification can proceed largely without human intervention and, if successful, can allow efficient linkage of clinical notes with similarly deidentified specimens for laboratory investigators at other institutions. The Shared Pathology Informatics Network (SPIN) was funded by the Cancer Diagnosis Program of the National Cancer Institute to develop a computerized program that would search pathology department text files and reports from several institutions and retrieve, in a database, all records that met search criteria. SPIN was designed to access information from each institution’s electronic records without affecting the records and collating data from several sites into a single report. Our current project, the Specimen Retrieval System, requires the identification of large numbers of cancer specimens of specific types from Kaiser Permanente Northwest (KPNW) and, subsequently, other Cancer Research Network sites, retrieval of those specimens and linkage with clinical annotations that describe staging, treatment and outcome. We have used the existing databases of the KPNW Tumor Registry and Department of Pathology to identify cases. The EPIC electronic medical record and several other computerized text files provided the clinical notes for these patients. Using SPIN technology we then processed text files to ‘scrub’ them of PHI. All records were then manually inspected to assess the completeness of the process, which elements of PHI persisted and which had been successfully ‘scrubbed’ of PHI. We processed several hundred files from more than 100 patients and will report detailed statistical analysis. This technology has demonstrated significant capability to facilitate searches for pathologic specimens and clinical annotations using conventional reports from pathology departments. It is a valuable tool to remove PHI, deidentify medical records and ease sharing of clinical information with investigators at other sites.

The influence of race and treatment choice in 16,508 men treated either conservatively, with radiotherapy, or surgically for clinically localized prostate cancer.

210 Background: There are known variations in cancer survival based on race and treatment choices. We report the long-term survival probability, based on race, in 16,508 men with localized prostate cancer treated either conservatively or by radiotherapy or radical prostatectomy. Methods: We extracted survival data from tumor registries of six Cancer Research Network sites in the United States. Patients were stratified into four racial groups: Caucasians, African Americans, Hispanics, and Asians. The Cox proportional-hazards regression model was used to compare long-term survival in the three treatment groups. Kaplan-Meier survival curves and competing risk analysis was also performed. Results: Survival was improved for patients who underwent radical prostatectomy compared to radiotherapy or watchful waiting. This was true for all patients combined (Table) as well as for all races individually. Radiotherapy had at least equivalent survival outcomes as watchful waiting in all groups. The differences between treatments were greater for overall survival than for prostate cancer specific survival in all groups, though the extent of the differences varied by race. Conclusions: Radical prostatectomy increases survival in men with localized prostate cancer compared to both radiotherapy and watchful waiting, especially for Caucasian men. Radiotherapy was at least equivalent to watchful waiting for all races. Racial disparities in outcome may influence treatment choices for men with clinically localized prostate cancer. [Table: see text] [Table: see text]

C-A4-01: Providing Care for Cancer Survivors in Integrated Delivery Systems: An Assessment of Current Practices and Future Opportunities

Jessica Chubak, PhD1, Clarissa Hsu, PhD2, Leah Tuzzio, MPH1, Beth Kirlin, BA1 and Larissa Nekhlyudov, MD, MPH3,4 1Group Health; 2Group Health Research Institute; 3Harvard Medical School; 4Harvard Vanguard Medical Associates

PS1-11: Specimen Collection Within the Cancer Research Network: A Critical Appraisal

Background and Aims: The Genomics Working Group (of the Cancer Research Network (CRN) Pharmacovigilance Project) explored single-site experiences with genomic studies to understand challenges and opportunities for collecting and using biological specimens. Its specific aims were to: describe the availability of existing biospecimens; document successful past specimen collection strategies; identify potential barriers to selected recruitment strategies; and develop standardized study documents for future genomic research. Methods: We distributed a survey on existing biospecimen availability to principal investigators at all CRN Pharmacovigilance sites. Information collected included the number of specimens, storage methods, and type of specimens available. Investigators were also asked to identify past and current studies at their institutions in order to collect information on successful specimen collection strategies. A literature review was conducted both to identify potential barriers to participation and to understand the feasibility of various recruitment procedures. Benefits and limitations of ‘opt-out’ and ‘opt-in’ specimen collection methods were examined. Lastly, we developed study documents, including recruitment letters and informed consent forms, for future saliva and blood specimen collection efforts. Results: Two of the CRN HMOs currently have large-scale banked blood or saliva specimens (>20,000) within existing repositories. One site has two large-scale studies (>20,000 participants each) with banked specimens able to provide DNA for future research. Whole blood or blood components are the most commonly collected specimen types, and multiple CRN sites have access to banked tumor blocks. There were 33 past or current studies that included biospecimen collection. There was a trade-off between intensive data collection requirements and recruitment yield, cost, and participation burden. Conclusions: There is great potential for collection, storage, and use of biospecimen samples for research within the CRN. For future collection efforts, ‘opt-out’ models allow fast sample accrual, but impact data de-identification requirements. ‘Opt-in’ models allow for broad data collection, but are resource and time intensive. Pathology time and support may be a barrier to future use of stored samples.

Automated inter-rater reliability assessment and electronic data collection in a multi-center breast cancer study

BackgroundThe choice between paper data collection methods and electronic data collection (EDC) methods has become a key question for clinical researchers. There remains a need to examine potential benefits, efficiencies, and innovations associated with an EDC system in a multi-center medical record review study.MethodsA computer-based automated menu-driven system with 658 data fields was developed for a cohort study of women aged 65 years or older, diagnosed with invasive histologically confirmed primary breast cancer (N = 1859), at 6 Cancer Research Network sites. Medical record review with direct data entry into the EDC system was implemented. An inter-rater and intra-rater reliability (IRR) system was developed using a modified version of the EDC.ResultsAutomation of EDC accelerated the flow of study information and resulted in an efficient data collection process. Data collection time was reduced by approximately four months compared to the project schedule and funded time available for manuscript preparation increased by 12 months. In addition, an innovative modified version of the EDC permitted an automated evaluation of inter-rater and intra-rater reliability across six data collection sites.ConclusionAutomated EDC is a powerful tool for research efficiency and innovation, especially when multiple data collection sites are involved.

Using Probabilistic Corrections to Account for Abstractor Agreement in Medical Record Reviews

The quality of medical record abstracts is often characterized in a reliability substudy. These results usually indicate agreement, but not the extent to which lack of agreement affects associations observed in the complete data. In this study, medical records were reviewed and abstracted for patients diagnosed with stage I or stage II breast cancer between 1990 and 1994 at one of six US Cancer Research Network sites. For a subsample, interrater reliability data were available. The authors calculated conventional hazard ratios and 95% confidence intervals for the association of demographic, tumor, and treatment characteristics with recurrence rate. These conventional estimates of effect were compared with three sets of estimates and 95% simulation intervals that took account of the uncertainty assessed by lack of agreement in the reliability substudy. The rate of recurrence was associated with increasing cancer stage and with treatment modality but not with demographic characteristics. The hazard ratios and simulation intervals that took account of the reliability data showed that the simulation interval grew wider as the sources of uncertainty taken into account grew more complete, but the associations expected a priori remained readily apparent. While many investigators use reliability data only as a metric for data quality, a more thorough approach can also quantitatively depict the uncertainty in the observed associations.