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Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER
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Use of the Oncology Beacon Module and Virtual Data Warehouse Data to Identify Variations in Treatment for Advanced Colorectal Cancer RITZWOLLER

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  • 1. Use of the Oncology Beacon ® Module and VDWData to Identify Variations in Treatment and Cost for Patients Diagnosed with Stage III/IV Colorectal Cancer18th Annual HMO Research Network Conference May 1, 2012 Debra P. Ritzwoller Institute for Health Research, Kaiser Permanente Colorado
  • 2. Project Team Co-Investigators: PMs: KPNW: Mark Hornbrook, KPCO: Kimberly Bischoff Maureen O’Keeffe-Rosetti KPNW: Jill Mesa KPNC: Heather Clancy KPNC: Larry Kushi Programmer/Analysts: KPCO: Tom Delate, Alex KPCO: Nikki Carroll, Capp Menter, Jared Freml Luckett KPNW: Mike Zimmerman, Karen Riedlinger KPNC: Karl Huang
  • 3. Background  Gaps exists in the literature related to the utilization and costs of chemotherapy agents for colorectal cancer (CRC) patients not captured by SEER- Medicare data or clinical trials  Key factors are needed  Treatment intent (curative vs palliative)  Use of evidence based protocols  Dosing  Treatment modifications and reasons for discontinuation  Use of second-line treatment  These data are now available from Epicare based Oncology Beacon® modules that now populate newly developed VDW infusion files
  • 4. Aimssing the wealth of cancer treatment data newlyavailable as a result of recent VDW infrastructuredevelopment efforts associated with infusion andchemotherapy utilization, in this PILOT project we…xamine the factors associated with the receipt ofchemotherapyxamine the variation in chemotherapy protocols andregimens administered to patients with advanced CRC
  • 5. Methods• Using VDW Tumor Registry and Enrollment files at KPCO, KPNC, and KPNW, we identified Stage III/IV CRC patients diagnosed in 2010 - after Beacon implementation  First diagnosed cancer  Survived at least 1 month after diagnosis  21 years of age and older• Linked cases to • VDW Demographics, Diagnosis, Census, pharmacy and procedure files • Infusion files derived from the Beacon modules• 1st line Chemotherapy ascertained within 120 days of diagnosis• Followed cases until death, disenrollment or end of 2011
  • 6. Results• 489 cases identified • 46% stage III, 54% stage IV• 47% < 65 years• 9% Hispanic, 9% African American, 10% Asian• 83% had 6 or more comorbidities• 68% (n=335) received chemotherapy • 308 had identifiable chemotherapy regimens
  • 7. Receipt of chemotherapy• Was inversely related to • Age • Stage • Number of comorbidities (not always significant)• Was not associated with • Gender • Race/ethnicity • Education (census track proxy)
  • 8. Distribution of Treatment Intent by Stage Treatment Intent Stage III Stage IVADJUVANT 58.5% 8.1% PALLIATIVE - FIRST LINE 1.4% 52.8% CAPECITABINE (assumed Adjuvantfor stage III) 23.8% 19.9%NEOADJUVANT 10.9% 4.3%CURATIVE - FIRST LINE 4.8% 5.6%Missing Treatment Intent 0.7% 6.8%PALLIATIVE - AFTER FIRST LINE 0.0% 2.5%P < .001
  • 9. Distribution of Protocols by Stage Protocol Name Stage III Stage IVONCA COLORECTAL COLON FOLFOX-6MODIFIED - ADJUVANT - PRL105 40.8% 23.0%CAPECITABINE 23.8% 19.9%ONCA COLORECTAL COLON FOLFOX-6MODIFIED BEVACIZUMAB - PRL106 0.0% 32.9%ONCA COLORECTAL RECTAL FLUOROURACIL(CI) WITH RT - PRL103 11.6% 1.9%ONCA COLORECTAL COLON CAPOX - PRL113 8.2% 1.9%ONCA COLORECTAL COLON FLUOROURACILLEUCOVORIN (ROSWELL PARK) - PRL132 4.1% 3.1%ONCA COLORECTAL COLON CAPOXBEVACIZUMAB - PRL114 0.0% 6.2%Other 11.6% 11.2% P < .001
  • 10. Distribution of First-Line Regimens by Stage Regimen Stage III Stage IVFLUOROURACIL / LEUCOVORIN /OXALIPLATIN 39.5% 31.1%CAPECITABINE 23.8% 20.5%BEVACIZUMAB / FLUOROURACIL /LEUCOVORIN/ OXALIPLATIN 0.7% 23.6%FLUOROURACIL 12.9% 1.2%CAPECITABINE/ OXALIPLATIN 9.5% 3.1%FLUOROURACIL / LEUCOVORIN 8.2% 3.1%BEVACIZUMAB / CAPECITABINE /OXALIPLATIN 0.0% 5.0%Other 5.4% 12.4%P < .001
  • 11. Reasons for Discontinuation by Stage Reason Stage III Stage IVMissing Reason for Discontinuation 40.8% 30.4%Capecitabine 23.8% 19.9%Progression of disease 2.7% 24.8%Treatment plan completed 18.4% 7.5%Toxicity from treatment 6.1% 5.6%Patient/family preference 4.1% 4.3%Maximal response 0.0% 3.7%Other, please note reason in progress notes 1.4% 2.5%Current part of multi-part regimen completed 2.0% 0.0%Co-morbidity 0.0% 1.2% P < .001
  • 12. Results – Changes & Numbers Stage III Stage IV Mean (std) Mean (std) Number of changes in treatment intent 0.8 (0.4) 0.8 (0.5) Number of changes in protocol 0.8 (0.5) 0.9 (0.5) Number of different drug regimens 1.1 (0.4) 1.4 (0.7) Number of cycles of drug regimen 3.6 (3.0) 3.5 (2.6)
  • 13. Cost Estimation by Regimen and Dose Total AWP Patient Total AWP Cost Per example Cost Per Treatment Chemotherapy Dose Units AWPCost Regimen Plan A FLUOROURACIL - IVPB 2400 mg/m2/dose $ 27.99 FLUOROURACIL 648 mg $ 4.67 LEUCOVORIN 648 mg $ 38.88 OXALIPLATIN 137.7 mg $ 1,974.40 4 cycles $2,045.94 $8,183.75 B BEVACIZUMAB 453.5 mg $ 3,247.65 FLUOROURACIL -IVPB 2400 mg/m2/dose $ 35.77 FLUOROURACIL 828 mg $ 5.96 LEUCOVORIN 828 mg $ 49.68 OXALIPLATIN 176 mg $ 2,523.56 2 cycles $ 5,862.62 $11,725.24 C XELODA TAB 500MG 100 caps $ 329.24 $ 3,292.37 $3,292.37
  • 14. Summary of Results• The distributions associated with treatment intent, protocols, regimens, and reasons for discontinuation, varied significantly by stage.• The most common first line treatment was Oxaliplatin + Fluorouracil + Leucovorin.• First-line oral chemotherapy agents (e.g capecitabine) are not always captured in Beacon• Missing observations are common for some variables (e.g reason for discontinuation, treatment intent, etc)• Costs of chemotherapy vary by both regimen and dosage
  • 15. Conclusions Newly available VDW chemotherapy infusion data derived from the EpicCare and Oncology Beacon® files (along with other infusion data sources) is a rich cancer treatment data source that researchers can use to conduct clinical- and policy-relevant comparative effectiveness research studies in patients with colorectal cancer.
  • 16. Acknowledgements This pilot project was directly funded by Kaiser Permanente and theCenter for Safety and Effectiveness Research (CESR). Indirect support and support for preliminary analyses were provided by NCI Grant No. RC2CA148185, Building CER Capacity: Aligning CRN, CMS, and StateResources to Map Cancer Care, Co-PIs: Jane C. Weeks, MD and Debra P.Ritzwoller, PhD, and NCI Cooperative Agreement No. U19 CA79689,Increasing Effectiveness of Cancer Control Interventions (Cancer ResearchNetwork), PI: Edward H. Wagner, MD.pecial thanks to Drs. Jane Weeks and Deborah Schrag for their commentsand suggestions regarding the original study design.

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