Surveillance and SEER Where are we going? NAACCR Meeting June 23, 2017 Lynne Penberthy MD, MPH

Transcription

1 Surveillance and SEER Where are we going? NAACCR Meeting June 23, 2017 Lynne Penberthy MD, MPH

2 Presentation Objectives Describe Future Role of Registries & Registrars Challenges to cancer surveillance Discuss specific activities of how SEER is addressing those challenges

3 WHAT IS THE FUTURE OF REGISTRIES AND REGISTRARS? 3 3

4 Registries and registrars in research? The data from registries is increasingly recognized as an adjudicated, CURATED and accurate base for many research platforms o As investigators struggle with interpreting, paying for and abstracting data from medical records o Struggle with acquiring data from unstructured and conflicting text documents o Increasing interest by NCI, FDA and others in real world data by such sources as FlatIron, CancerLinQ and Tempus Significant limitations of those sources as convenience samples of incomplete and nonconsolidated information It is essential that the registries be an active participant in the discussions about the use of real world data 4

5 Challenges and Proposed Solutions for Cancer Surveillance 5 5

6 Cancer Surveillance Challenges: Data Collection Complexity of cancer care and delivery of care Expanding data characterizing each cancer (precision medicine/ genomic data) o Panels often encompass hundreds of mutations tested Changing requirements (e.g. AJCC 8 th Ed) Long term survival requires data on initial and subsequent events and treatments o To support better understanding of events between the initial diagnosis and death

7 Cancer Surveillance Challenges: Data Sources Dispersion of cancer diagnosis and treatment across multiple health care providers/locations (no longer only hospital-based) Lack of access by registrars to new clinically important information o Diagnosis and treatment from community oncology practices o Pharmacy provided oral treatment o Complex genomic tests (multigene panels) Difficult to manually capture and interpretation challenging o Lack of access to recurrence information Requires accessing information outside traditional registration sources Pathology labs Physician offices Pharmacies Freestanding integrated specialty practices Urology Radiation oncology

8 Genomics Hospital data Oncology Practice data Claims CancerLinQ Pharmacy data PROs Radiation Oncology THE EVOLUTION OF SEER 8 8

9 What are the critical missing pieces for SEER to address the challenges and better support research? Detailed AND longitudinal treatment Outcomes other than survival o Recurrence and disease progression o Patient generated health data Genomic information 9 9

10 MISSING DETAILED TREATMENT 10

11 Two categories of missing treatment Orally Administered Anti-neoplastics Traditional Infusion Chemotherapy Require different approaches o Oral treatments provided at pharmacies o Infusion often provided in the outpatient (community oncology practice) setting with limited access by registrars Solution: linkages o Data can be automatically added does not require registrars capturing the complex and multitude of agents o Often consistent and/or standardized format o Provides both initial and subsequent therapy o Potential to monitor compliance 11

12 Treatment Linkages: Oral agents 25%+ systemic Rx and growing No population based information (CTs/case series data only) Capturing pharmacy data offers potential for o Supplementing treatment o Monitoring disparities in use and nonadherence o Identifying adverse events 12

13 Treatment Linkages: Oral agents solutions? Large pharmacy chain central repository linkages Signed DUA with CVS to report data to SEER In discussion with Walgreens Represent approximately 45% + prescriptions Link with pharmacy switchers (processors) Change Healthcare and QS1 data holds 30% of transactions from across multiple different pharmacy providers

14 Treatment Linkages: Claims data for infusion Rx Value of claims for treatment Standardized format and nomenclature from all providers High degree of accuracy and detail based on HCPCs for treatment Longitudinal data permits assessment of initial and subsequent therapy SEER- Medicare (65+) Linked since early 1990s >1600 publications Moonshot sponsored Claims Workshop in Sept 2017 o Propose to expand scope of integrated claims from multiple insurers accomplished in KY and Seattle to broader SEER program Central claims processors (oncology) Represent patient populations for all payers & all ages A single central processor for 25-45% of oncologists within 7 SEER registries Pilot in GA 6 of 12 oncology practices completed 4.5 years data capture ( 15% of cancer patients in GA) Implemented in 5 additional registries

15 Preliminary Data from 6 Months Claims in 4 Georgia Oncology Practices: Common Regimens for Treatment of Initial and Recurrent Breast Cancer Administration frequency for chemotherapy regimens commonly used for initial breast cancer treatment (6 months of data) Common Regimens Initial treatment of Breast Cancer 4 regimens - 4,676 administrations Frequency of Administration Common Regimens Treatment of Recurrent or Metastatic Breast Cancer 9 regimens -1,262 administrations Administration frequency for chemotherapy regimens commonly used for treatment of recurrent or metastatic breast cancer (6 months of data) Frequency of Administration

16 Other opportunities to capture treatment Link with oncology practice intermediaries Radiation Oncology/EMRs Metrik/Mosaic (45%) & Varian (50%) o Pilots in development/ implementation in KY o Opportunity to capture more detailed radiation information Both for initial as well as subsequent therapy (eg. Treatment of metastatic lesions) Oncology Practice EMR data o MOU for data exchange with ASCO CancerLinQ (CLQ) to automatically report data to registries from oncology practices Pilot protocol in process (9 practices in 3 states- IA, GA, UT) CLQ has agreements with >2000 oncologists currently and growing Opportunity to capture both systemic and orally administered treatment and supplement other data (recurrence) 16 16

17 MISSING OUTCOMES OTHER THAN SURVIVAL 17 17

18 Capturing outcomes other than survival: Recurrence Identifying patients with distant recurrent disease is critical with >18 million cancer survivors for whom we cannot describe the risk of recurrence Identification of recurrence is complex It can be diagnosed via multiple methods which vary by: o cancer site o time to recurrence o diagnosing physician type primary care, oncologist, radiation oncologist, radiologist etc. o diagnostic method (biopsy, imaging, serology) Accurate measurement of recurrence requires capture of multiple layered, combined data sources and new methods (NLP) to provide comprehensive capture of recurrence(s).

19 Capturing outcomes other than survival: Patient Generated Health Data Certain categories of information can ONLY be collected from the patient Symptoms/ QOL Health History Working with partners to test solutions, e.g., patient portals, direct patient reporting, and patient-generated data sources MBCA/ACS/NCI funded activities for Focus groups on patient reporting to registries Financial toxicity as an important outcome NCI funded registry study in 4 registries to explore methods for patients to provide data to registries via electronic formats

20 GENOMIC DATA TO CHARACTERIZE EACH CANCER 20

21 Genomic data now critical to understand each patient s cancer The increased availability of targeted agents and Proliferation of genomic testing of tumors relevant for both prognosis and predicting response to therapy Represents a special challenge to registrars. o Many individual biomarkers- which may or may not be available to registrars in the EMR o Genomic panels can consist of hundreds of mutation tests with varying structure and actionable information o It is not feasible for registrars to capture all these data so alternative methods must be considered. 21

22 Capturing Genomics Data in SEER through NLP and automation These are often in unstructured path reports o we cannot continuously increase the number of required data items registrars must collect o targeted NLP and machine learning can supplement the work registrars do o human assisted machine learning may be the optimal method (using machines where possible but will always require human adjudication for many things) Tools and methods developed using path reports can be applied to other unstructured text in the EMR (radiology dictations, clinical notes etc) 22

23 Capturing Genomics Data in SEER through Linkages: targeting high volume/ high relevance sources o GHI Oncotype DX 21 and 16 gene assay completed and repeating annually Added 43% of test results not seen in hospital reported data sent to MD office o BRCA panels for Breast and Ovarian Pilot linkage in GA/ CA completed for data Processes for linkage confirmation/data access in development Goal link data across all SEER o Syapse Genomic data acquisition specialist (analogous to the Claims vendor) Receive and store data from >15 genomic testing labs for clinical client access Developing pilot in GA for linkage with selected genomic lab data o GenomeDX and Foundation Medicine Pilots in discussion to link panels with SEER data 23

24 OncotypeDx Population-based results corroborating CTs in a real world setting (n=38,568) Risk Score predicted Breast cancer mortality Known chemo use followed reccs.* 7% of RS <18 34% of RS 18-30, 69% of RS 31 No significant association of RS with non-breast cancer mortality (p=0.66) Low RS Group Intermediate RS Group High RS Group *Chemotherapy known to be underreported in SEER 24

25 Impetus for Linking Genetic Test Data to Cancer Registries (GA & CA) These types of linkages are important because: o Results of germline genetic testing for pathogenic mutations in BRCA 1/2 being used to individualize treatment recommendations: Preventive surgery for reduced risk of ovarian cancer o Population-level BRCA mutation panels together with other registry data may help in determining potential importance of what are now VUS among population subgroups o Important predictors of response to therapy recently identified as related to BRCa mutations Increased use of platinum based chemotherapy (shown to target BRCA associated tumors) PARP inhibitors (ASCO 2017) o Increasingly important for understanding real world data to supplement efficacy data from CTs limited by small sample size and non reperesentativeness

26 ENHANCING THE UTILITY OF REGISTRIES THROUGH A SEER- LINKED VIRTUAL BIO-REPOSITORY 26 26

27 SEER-Linked Virtual Bio-Repository: Benefits Population based permitting comparison of subsets Available across a broad spectrum of health care facilities/pathology labs (not just academic centers) Access to rare cancers and exceptional outcomes Linked long term outcomes Existing annotation with clinical and demographic data Potential for custom annotation Renewable with > 400,000 incident cases annually

28 BioLinc: VTR Central resource for de-identified abstracts, path reports and path images - support investigator case selection Ability to search deidentified path reports linked to abstracts Static Images for QC Whole Slide Images for digital pathology research 28 28

29 SEER-Linked Virtual Bio-Repository Pilot 7 registries funded for pilot of pancreas and breast 9/15 Focus on exceptional survivors 431 early stage node negative breast cancer (< 2 yr survival) 224 pancreatic adenoca long term survivors (> 5 yr survival) Matched controls for both sets of cancers Purpose Assess best practices across multiple registries Estimate costs of supporting a SEER wide system Assess availability of specimens Understand human subjects/consent as requirements vary by registry and prepare for common rule changes In addition to primary objectives: Once completed pilot will provide a well annotated set of cancers with unusual responses that will be available for research purposes

30 THANK YOU FOR YOUR ATTENTION 30 30

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32 Cancer Research Data Ecosystem Cancer Moonshot NCI Blue Ribbon Panel Discovery Patient engaged Research Surveillance Big Data Implementation research Proteogenomics Imaging data Clinical trials Clinical Research Observational studies EHR, Lab Data, Imaging, PROs, Smart Devices, Decision Support Well characterized research data sets Cancer cohorts Patient data GDC Research information donor Active research participation SEER/NPCR Real World Data to support Learning from every cancer patient

33 Data Exchange SEER and CLQ oncology practices Oncology Practice via CLQ to Registries Registries to Practices via CLQ Data from CLQ to SEER registries enhances data completeness for information on: Treatment Recurrence Comorbidity Cancer cases that are diagnosed and treated exclusively as outpatients Data from Registries back to Practices via CLQ provides information critical to assessing quality of care and understanding their own practice patterns and outcomes Length of survival Cause of death Discrete, structured characterization of the cancer at the time of diagnosis Stage at diagnosis Surgery, Radiation Histopathology and biomarkers at diagnosis

34 Cancer Surveillance: What do we need to collect? Putting Putting the puzzle the together puzzle together for each for cancer each patient: cancer Data patient. Collection Diagnosis Death Initial + Subsequent Rx Orally Administered Agents Recurrence Progression Metastases PGI QOL Cancer Patient Subsequent Rx- Systemic/ radiation Genomic Characterization Molecular profiles Mutations Serologic & Tissue based predictive and prognostic Biomarkers Initial Rx Traditional Chemotherapy

35 Putting the puzzle together for each cancer patient: Data Sources Diagnosis Death Hospitals Radiation Centers Mosaic/ Metriq Varian Oncology Practices CancerLinQ Unlimited Systems Surgical Pathology Labs Clinical Path Labs LabCorp Quest Mayo Specialty Providers Urology Derm Private Industry Pharmacy Switchers/ Pharmacies Claims Insurers Claims Processors Radiology Diagnostic Imaging Results Genomic Testing Labs Survival/ Cause of Death NDI/SSDI Linkage with EMRs ALTOS McKesson Mosaic