The Ontario Cancer Registry moves to the 21 st Century

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2 The Ontario Cancer Registry moves to the 21 st Century Rebuilding the OCR Public Health Ontario Grand Rounds Oct. 14, 2014 Diane Nishri, MSc Mary Jane King, MPH, CTR

3 Outline 1. What is the Ontario Cancer Registry? 2. Purpose of the Cancer Registry 3. CCO and the OCR 4. Data Sources and Key Processes 5. Impact 6. Key Terms and Disease Coding 7. Counting Rules and Source Hierarchy 8. Note on Staging 9. Next Steps 10. Questions

4 What is the OCR? 4 Major Data Sources A computerized database of information about all Ontario residents who have been diagnosed with cancer ( Incidence ) or who have died of cancer ( Mortality ). Cancerrelated CIHI DAD and NACRS (surgical) Regional Cancer Centres (ALR/ Data Book) Pathology reports (emarc) Death Certificates Earliest Incidence Data: 1964 Earliest Mortality Data: 1950

5 History of the OCR Ontario Cancer Treatment and Research Foundation created to manage 3 regional cancer centres OCTRF took over ownership of OCR OCRIS updated in mid-1990s s 1990 s OCR created and managed by what was then Department of Health OCR was manually curated until the early 1980s when an automated system (OCRIS) was built

6 Purpose of the OCR The OCR facilitates reporting of: MISSION To generate, analyze and disseminate timely, high quality information describing all cases of cancer diagnosed among Ontario residents. Incidence The number or rate of new cancer diagnoses over a specified period of time in a known population. Mortality The number or rate of deaths from cancer over a specified period of time in a known population. Survival The proportion of people diagnosed with cancer that are still alive after a given time period, most commonly 1 to 5 years after diagnosis. Prevalence The number of people who have been diagnosed with cancer during a specified time period and who are still alive at a point in time.

7 The many uses and users of the OCR Research Surveillance Who uses/receives data? Public Researchers Public Health Clinicians Regional Programs & Planning CCO Clinical Programs CCO Prevention & Cancer Control CCO Public Affairs CCO Informatics Familial Genetics Registries Source Data Providers National Organizations (CPAC, CCS, etc.) Central Registries (CCR, NAACCR) International Organizations (IACR) What data? Cancer Incidence & Mortality Population Characteristics Cancer Stage Cancer Treatment Geography Disease Site Clinical Outcomes/Quality Improvements Monitoring Data Integrity Source Data Quality How used? Rates Trends Projections SEER*Stat Survival & Prevalence Linkage Cohort Identification Audit trails

8 CCO and the OCR: Canadian context Every province and territory has its own registry. Each provincial/territorial registry is slightly different in terms of starting date, scope, legislation, custodial responsibility, etc. All registries submit data to Statistics Canada to form the Canadian Cancer Registry. Almost 39% of Canadians live in Ontario - 13,372,996. Ontario s registry (OCR) is owned and managed by CCO.

9 Data Source 1: Hospitals Provided by CIHI since April 1986 Coded in ICD-10-CA / ICD-O-2 since April 2002 morphologies only provided for ~5% of records Coverage: Discharge Abstract Database (DAD): all years Same Day Surgeries (SDS): April 1993-March 2001 National Ambulatory Care Reporting System (NACRS): April 2001 to present

10 Data Source 2: Regional Cancer Centres This data source also includes PMH and records from other provincial registries (Out of Province) Coding: RCCs: ICD-10 / ICD- O-3 starting in 2002 PMH: ICD-O-3 starting in 1999

11 Data Source 3: Pathology Phases: : Implementation & expansion : Continued growth : PIMS electronic pathology system 2011: Switch to emarc (synoptic path reports) Coding: : ICD-9 / ICD-O : ICD-O : ICD-O-3

12 Data Source 4: Death Certificates Extreme delays in the receipt of coded death certificates from the Registrar General of Ontario hamper timeliness of registration 2008 deaths rec d January 2011 (10 months) 2009 deaths rec d March 2012 (14 months) 2010 deaths received April 2013 (13 months) 2011 deaths rec d February 2014 (11 months) Coded in ICD-10-CA since 2000

13 Source Accrual Patterns Reporting sources for 2007 incident cases in OCRIS, Oct Hospital discharges 73% Day surgery 35% Deaths 33% Cancer Tx clinics 62% Path reports 82% % Single Source Hosp only 4% Path only 5% DC only 2% Clinics only 3% (Day surgery only 2%)

14 OCR Key Processes Patient Linkage Combination of deterministic and probabilistic linkage routines to aggregate a person s source records (what was submitted to CCO) into a best of linked person record. Generates a single composite/representative record representing that individual. Case Resolution Consolidates records from multiple data sources into one or more primary cases of cancer Generates a single resolved record representing each primary case.

15 OCR: Summary to Date User community for registry data has expanded beyond traditional user base. Need to modernize, align to federal and North American standards, increase reporting and business intelligence capabilities. Multi-phase initiative to rebuild OCR within CCO s Enterprise Data Warehouse. This is the first rebuild of OCR since the creation of original automated system. Final phase completed in Formal announcement of new OCR planned for Oct. 29, 2014.

16 OCR Processes Impact Different eras = different data OCRIS cases EDW cases N.B.: If your report or analysis spans the cut-over from OCRIS to EDW cases, special care must be taken to reconcile the different data sets

17 OCR Processes Impact Incident Cases by Site, by Year Number of Incident Cases

18 OCR Processes Impact Why has the number of cases increased in the new OCR? More liberal rules for multiple primaries Additional source records Records that were ignored before are now being included in Case Resolution OCRIS was based on very conservative, modified IACR MP rules. -No timing, laterality and no similar histologies -Grouping of organs as same site

19 Key Terms Term Topography Histology Morphology Definition In ICD-O-3 coding, these are codes that map the human body, indicating the site of origin of a neoplasm (abnormal mass of tissue). The study of tissues and cells under a microscope. At CCO, we use the following definition in relation to disease coding Histology is the architecture of the cells of neoplastic tissue seen microscopically. Histology describes the different appearance and arrangement of cells for different neoplasms. A code describing the type of cell that has become neoplastic and its biologic activity. 4 digits cell type (histology) 1 digit behaviour

20 ICD-O-3 Topography Topography maps the body using codes

21 Disease Coding OCRIS resolved cases in ICD-9/ICD-O-1. ICD (9 and 10) is a system of codes for all medical conditions. A subset is for neoplasms. Histology codes are available but not required and are not current. Breast cancer: ICD-9 = 174_ ICD-10 = C50_ (in situ use D codes) ICD-O-3 is derived from ICD-10 and is specifically for Oncology coding. ICD-O-3 requires histology and a separate behaviour code. The C codes are only body part identifiers (topography) Breast cancer: ICD-O-3 = topography C50_, histology 8500, behaviour 3

22 Disease Coding Cancer ICD 9 ICD 10 ICD-O-3 Female breast, central portion C50.1, sex=f or 2 C50.1, sex=f or 2*, behaviour=3 Multiple myeloma C90.0 C42.1, 9732/3 Prostate 185 C61 C61.9*, behaviour=3 Carcinoma in situ of cervix uteri D06.9 C53.9, 8010/2 *excluding hematopoetics, mesothelioma & Kaposi sarcoma

23 SEER standards allow multiple primaries in more situations SEER rules have a more permissive standard for determining multiple primaries than was used in OCRIS OCRIS multiples had to have both a different topography and a different morphology Criteria OCRIS OCR Data Mart Same topography/different morphology Different topography/same morphology No (in general) No (in general) Yes Yes Laterality No Yes Timing No Yes (in general)

24 Multiple Primary and Histology Schema 1. Head and Neck 2. Colon 3. Lung 4. Skin Melanoma 5. Breast 6. Kidney (parenchyma) 7. Renal Pelvis, Ureter, Bladder and Other Urinary 8. Malignant Brain 9. Other Sites (solid tumour cancers of sites not included above) 10. Hematopoietic (lymphoma, leukemia and related diseases) AND 11. Benign and Borderline Brain Tumours

25 Multiple Primary Rules - Laterality Left vs right laterality tumours may now be counted as different primaries for paired sites, including: Breast Kidney Lung & Pleura Skin (Melanoma) Certain Head & Neck sites Bones Peripheral nerves Certain GYN sites Testis & associated structures Eye & adnexa Benign and borderline CNS tumours..but not malignant CNS tumours! Others - see definitive list, Appendix _ Laterality: for paired organs - which side of the body the tumour is on.

26 Multiple Primary Rules - Timing Tumours separated by time may now be counted as separate primaries Timing depends on site: Breast, Head & Neck sites = 5 years Kidney, Lung, Urinary sites, = 3 years Colon = 1 year Melanoma = 60 days Other sites = 1 year An invasive diagnosis following an in situ diagnosis by 60 days or more may also count as a separate primary Multiple Primary Rules if there is more than one tumour in the body part, under what conditions these are coded as one primary or multiple primaries Histology Rules specific instructions for selecting the best histology for a single primary (which may consist of a single or multiple tumours) best source - Path

27 Ranking Source Types Source type Rank in OCRIS Rank in OCR* Pathology 2 1 RCC/ALR 1 2 Out of Province 1 2 DAD 3 3 Death 4 3 NACRS 3 4 *For most comparisons.

28 Stage at Diagnosis TNM Tumour, Node, Metastasis System TNM is the most widely used classification, recognized as the international standard for describing the anatomic extent of disease; definitions are updated by the UICC and AJCC. Based on the extent of the primary tumour (T) extent of node involvement (N) & extent of metastases (M); each of these components is divided into numerical subsets (T0-T4, NO-3, M0-M1) which describe how advanced the malignancy is. Carried out by the responsible physician with the help of cancer registrars. TNM physician staging is available from the regional cancer centres only. Currently CCO only collects this when the case has not been assigned a Collaborative Stage

29 Stage at Diagnosis Collaborative Staging (CS) Different Collection Method CS is a new data collection tool for staging of cancer bringing together the principles of NCI/SEER Summary Stage, the TNM categories and stage groupings, and the SEER Extent of Disease coding structure. Collaborative Staging is not a new classification system. The Collaborative Staging System is a carefully selected set of data items that describe how far a cancer has spread at the time of diagnosis. Most of the data items have traditionally been collected by some cancer registries, including tumor size, extension, lymph node status, and metastatic status. New items were created to collect information necessary for the conversion algorithms (convert data to an actual stage), including the evaluation fields that describe how the collected data were determined, and site/histology-specific factors that are necessary to derive the final stage grouping for certain primary cancers. The TNM and Summary Stage are both generated by an electronic algorithm, based on the input data and the type of cancer..

30 Stage at Diagnosis CS Coverage CS is abstracted by OCR staff. Currently all cases of colorectal, breast, lung, prostate, GYN, skin melanoma, and thyroid have CS stage CS began with limited case finding in 2007 CS population level staging for breast, lung, CRC, prostate from 2010 onward CS population level staging for GYN and melanoma from 2011 onward CS population level staging for Thyroid from 2013 onward Where CS stage is present and complete, it is chosen as the stage of record for the case Stage of record (at diagnosis) hierarchy: CS if complete, otherwise TNM from cancer treatment centre if available

31 Next Steps Training Analytic methodological training will be made available shortly Information Currently working towards and updated SEER*Stat file To be released Jan-Feb 2015 Data through 2011 Will contain enhanced documentation

32 Questions? Further questions can be addressed to Diane Nishri and Mary Jane King at:

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