Methodology of Conducting the Patterns of Ovarian Cancer Care and Survival in the Midwestern Region of the United States Wilhelmina Ross, PA, MPH, CTR - Westat Jeannette Jackson-Thompson, MSPH, PHD n- Missouri Cancer Registry and Research Center Diane Ng, MPH, Westat Maricarmen Traverso-Ortiz, MPH, CTR - Westat June 2019

Background Involvement of a gynecologic oncologist (GO) in the care of ovarian cancer patients leads to improved outcomes, perhaps related to greater adherence by GOs to guidelines-based procedures. Standard treatment adherence, mortality and survival outcomes are significantly and consistently greater when GOs are involved in treatment. Being seen by a GO is the most significant predictor of whether a woman with ovarian cancer will receive standard treatment

Background Guidelines-based treatment consists of: Extensive debulking surgery; also called cytoreduction Specific surgical staging techniques done during surgery Chemotherapy with a typical regimen a combination cisplatin and paclitaxel NCCN guidelines specifically recommend that ovarian cancer surgery be performed by GOs

There is an uneven distribution of GOs in the United States. Background There is an uneven distribution of GOs in the United States. GOs are more likely to be in urban cities. Region with fewer practicing GOs includes: Iowa, Kansas, Minnesota, Missouri, North Dakota, Nebraska, and South Dakota Based on the Society of Gynecologic Oncology registered GO professionals, the North Central Division of the Midwest region has fewer practicing GOs and has many rural areas.

Purpose and Objective This project pursued investigation of ovarian cancer treatment and survival in the Midwest region where the availability of GOs may be low when compared to other regions of the US.  The purpose of the study was to: Assess patterns of ovarian cancer care, treatment and survival; Identify factors associated with receipt of non-guidelines-based treatment. This presentation aims describe and analyze the methodology used throughout the study regarding study design and execution.

Subcontract with Westat Methods Recruitment Three Midwest central cancer registries (CCRs) participated in the study Iowa (SEER) Kansas (NPCR) Missouri (NPCR) Subcontract with Westat Data collected included existing information from each registry’s database as well as additional study-specific data items obtained from reporting facility medical records. CCR staff followed a protocol developed by CDC and Westat. Westat contracted with CDC on this project

Selection Criteria Inclusion Exclusion Primary Site: Ovary, C56.9; Fallopian Tube, C57.0; and Primary Peritoneal, C48.1-C48.8 Tumors of low malignant potential (ICD-O codes 8442, 8451, 8462, 8472, and 8473) Behavior: 3 (Malignant) Type of Reporting Source: Autopsy only and death certificate only Histology: 8000-8576 and 8930 – 9110 Synchronous tumors Year of Diagnosis*: 2011 and 2012 No records available to CCR Age at Diagnosis: >18 and < 90 Resident of state other than where CCR located Ovarian cancer must be the first primary cancer Synchronous tumors (defined as two or more tumors diagnosed within six months of each other) No records available to CCR (e.g., woman diagnosed/treated out-of-state; reporting facility unable to provide complete data)

drew a random sample of 450 cases Study Sample Random selection SAS Program was created by CDC and applied to an extraction of each participating registry's database to create samples for the study drew a random sample of 450 cases defined inclusion and exclusion criteria created a file that could be imported into Abstract Plus created SAS datasets of the eligible population and a random sample for CDC to review Random selection SAS Program was created by CDC and was applied to an extraction of each participating registry's database to create samples for the study drew a random sample of 450 cases (oversampled in the event that some cases had no data/follow-up sources) created a file that could be imported into Abstract Plus the data abstraction tool that contained North American Association of Central Cancer Registries (NAACCR) data elements extracted from the registry database

Training Webinar on study orientation and training given to each participating registry. CDC, Westat, and registries participated in training. Abstract Plus demonstration given for data collection tutorial. Participating registries received: Study Protocol Data dictionary Abstract Plus study specific software with v16 metafile that was modified with study-specific edits FAQs (living document)

Iowa n=334 Kansas Missouri n=335 Data Collection Occurred between October 2017 and July 2018 Abstract Plus data collection tool N=1004 incidence cases (432 recurrences) Iowa n=334 Kansas Missouri n=335 432 Recurrences

Data Collection

Results

Results

Results

Results

Results

Results

individual state IRB review processes Challenges Recruitment issues timing funding mechanisms individual state IRB review processes Customization of collection tool Delayed delivery of Abstract Plus Reasons for difficulty with abstracting data related to chemotherapy Records had been archived and were difficult to retrieve. Physician offices where patients were seen had since closed. Some facilities had upgraded EHR systems and the records that were from the old EHR system could not be accessed without upper management approval. The timing of the study competed with the CCR standard annual data submission to CDC, limiting available staff resources to initiate work necessary to participate in the study. State-specific laws governing contractual agreement processes resulted in each state completing funding documentation and starting the project at different times. Additionally, addressing questions and incorporating protocol changes in response to five individual IRBs from CDC, Westat and within the state, took significant time and extra coordination. The customized data collection tool was delivered to the CCRs later than expected due to technical issues with re-programming Abstract Plus. A subsequent version of the program that fixed issues detected by CCRs during initial data collection was also required. Reasons for difficulty with abstracting data related to chemotherapy: A likely reason these problems were heightened was due to the diagnosis dates of the cases that were collected in the study. Other possible reasons included staff turnover at the clinician offices, change in reporting (e.g., facility outsourced reporting), and/or facility merged with another facility. Diagnosis years

The sample drawn is representative of the population in these states. Conclusion This study’s design, approach, and implementation was suitable overall for describing specific ovarian cancer treatment and survival in the Midwest. The sample drawn is representative of the population in these states. The data collection tool yielded high quality data for most items. A very rich data source to evaluate treatment adherence and outcomes now exists and can be used extensively to develop public health interventions to improve ovarian cancer burden. We wpuld like to think that the way the data was collected yielded high quality data. Training, data dictionary, quality assurance by both the sate and westat. Data collection provided a good method for collecting cancer registry and study specific data.

Conclusion Effectiveness of the data collection instrument The instrument performed well across many of the elements. We also learned important improvements that we can make in future similar data collection activities. Findings Provided critical lessons learned that can be applied to future data collection in this area and with regard to surgery, GO involvement and level of involvement, and second and third line chemotherapy can be collected from the medical records by cancer registries.

Conclusion Uncovered key issues with data collection, including incomplete or inadequate information. These data will allow the CDC to help identify groups of women who are not receiving the benefit of optimal surgery and GO care and provide critical data for improvements we can make in the lives of cancer patients moving forward. 

Funding This project was conducted by CDC, Westat and the state cancer registries of Iowa, Kansas, and Missouri, and funded under CDC contract 200-2014-61258. The Iowa Cancer Registry is also funded in part with Federal funds from NIH/NCI contract HHSN261201800012I and cancer center support grant NIH/NCI P30CA086862. The Kansas Cancer Registry is also funded by the Kansas Department of Health and Environment. The Missouri Cancer Registry core activities are supported in part by a cooperative agreement between the Centers for Disease Control and Prevention (CDC) and the Missouri Department of Health and Senior Services (DHSS) (U58DP006299-01/02) and a Surveillance Contract between DHSS and the University of Missouri.

Acknowledgements We’d like to acknowledge the work of the Ovarian Cancer Treatment Study Group: Lisa L. Hunter, Charles F. Lynch, Michele M. West (Iowa Cancer Registry); Sue-Min Lai, Sarma Garimella, John Keighley, Li Huang (Kansas Cancer Registry); Jeannette Jackson-Thompson, Nancy Hunt Rold, Chester L. Schmaltz, Saba Yemane (Missouri Cancer Registry); Wilhelmina Ross, Diane Ng, Maricarmen Traverso- Ortiz (Westat); Jennifer M. Wike (CDC contractor); Trevor D. Thompson, Sun Hee Rim, Angela Moore, Sherri L. Stewart (CDC)

Please contact the following for more information: Wilhelmina Ross, PA, MPH, CTR - WilhelminaRoss@Westat.com Jeannette Thompson-Jackson - jacksonthompsonj@health.missouri.edu Diane Ng, MPH - DianeNg@Westat.com Maricarmen Traverso-Ortiz, MPH, CTR - MaricarmenTraversoOrtiz@Westat.com Thank You Stay tuned for additional papers and presentations regarding the study.