Utility of an Early Case Capture Pediatric Cancer Registry

Transcription

1 Utility of an Early Case Capture Pediatric Cancer Registry Mary Puckett, PhD Epidemic Intelligence Service Officer Comprehensive Cancer Control Branch National Center for Chronic Disease Prevention and Health Promotion Division of Cancer Prevention and Control

2 Pediatric Cancer 13,500 children are diagnosed with cancer each year 1 2,100 children die each year from cancer 1 1. CDC Wonder Cancer Statistics

3 Cancer Mortality Trends among Children <20 Years of Age, United States, Mortality Rate (Deaths/100,000/yr) Year Surveillance, Epidemiology, and End Results (SEER) Program ( Underlying mortality data provided by NCHS (

4 Caroline Pryce Walker Conquer Childhood Cancer Act (2008) Advance pediatric cancer research and clinical trials Ensure public awareness CDC activities: Enhance and expand infrastructure to track pediatric cancer Include occurrences of pediatric cancer within weeks of diagnosis

5 Early Case Capture (ECC) for Pediatric Cancer Pilot Sites

6 ECC Pediatric Cancer Registry Logic Model Inputs Pediatric patient diagnosed with cancer Hospitals Clinics Laboratories

7 ECC Pediatric Cancer Registry Logic Model Inputs Activities Pediatric patient diagnosed with cancer States promote ECC reporting infrastructure Hospitals Clinics Case reported to state health department within 30 days Laboratories Data sent to CDC twice a year

8 ECC Pediatric Cancer Registry Logic Model Inputs Activities Outputs Pediatric patient diagnosed with cancer Hospitals Clinics Laboratories States promote ECC reporting infrastructure Case reported to state health department within 30 days Data sent to CDC twice a year Increased electronic reporting and reporting relationships Rapid access to cancer data

9 ECC Pediatric Cancer Registry Logic Model Inputs Activities Outputs Outcomes Pediatric patient diagnosed with cancer Hospitals Clinics Laboratories States promote ECC reporting infrastructure Case reported to state health department within 30 days Data sent to CDC twice a year Increased electronic reporting and reporting relationships Rapid access to cancer data Expansion to other registries More timely research Better treatment/ decreased mortality Increased enrollment in clinical trials

10 Research ECC for Pediatric Cancer Increase availability of pediatric data for surveillance activities Public health Increase electronic reporting (epath) Clinical Increase clinical research enrollment Increase follow-up for late effects of disease and treatment

11 OBJECTIVES AND METHODS

12 Objectives Assess current ECC practices Identify challenges with implementation Identify goals for data use Identify benefits Analyze data quality and representativeness Data submitted at one year Routinely reported national data

13 Design Qualitative assessment Quantitative assessment ECC practices from state perspective Quality and usefulness of data Understand utility of ECC

14 ECC Data Demographic variables o Age at diagnosis o Sex o Race o Ethnicity Methods: Quantitative Data Sources Tumor characteristic variables o Primary site o Tumor behavior (benign, malignant, etc.) o Diagnostic confirmation (microscopically/clinically confirmed)

15 ECC Data January 2012 December 2012

16 ECC Data January 2012 December 2012 Full year submission

17 ECC Data January 2012 June 2012 December 2012 ECC submission

18 ECC Completeness and Concordance ECC January 2012 June 2012 December 2012 Full year January 2012 June 2012 December 2012

19 United States Cancer Statistics NPCR SEER USCS All cases ages cases

20 ECC Representativeness ECC January 2012 June 2012 December yr States ECC states January 2006 December 2010

21 ECC Representativeness ECC 5-yr USCS January 2012 June 2012 All states December 2012 January 2006 December 2010

22 Methods: Quantitative Question Data Source Compared Statistical Test What is the percent of missing data in Jan June 2012 cases? What is the concordance of cases in both Jan June 2012 datasets? Full year submission (Jan June 2012 cases only) Full year submission (Jan June 2012 cases only) % Missing % Concordance How representative is ECC data of all state-level data? USCS (ECC states) Χ 2, t-test How representative is ECC data of nationwide data? USCS (All states) Χ 2, t-test

23 Methods: Qualitative Grounded theory approach 1 Structured focus group telephone interviews Registry employees in seven states Recorded and transcribed verbatim Codebook developed Code Brief and full definitions When to use/not to use/rules Example 1. Strauss, A. and Cobin, J. Basics of Qualitative Research: Grounded Theory Procedures and Techniques

24 Methods: Qualitative Transcripts coded and analyzed Constant comparative method Three independent coders Consensus reached for all codes Codes condensed to themes Theme A Code 1 Code 2 Theme B Code 2 Code 3 Code 4 Theme C Code 5 Code 6 Code 7

25 RESULTS

26 ECC Data Completeness % Missing % Concordance* ECC Full year Demographics State of Diagnosis County of Diagnosis Race Ethnicity Sex Age at Diagnosis Date of Birth Tumor Characteristics Primary Site Laterality Diagnostic Confirmation Type of Reporting Source Histologic Type Behavior Code *Excludes State E.

27 ECC Data Completeness % Missing % Concordance* ECC Full year Demographics State of Diagnosis County of Diagnosis Race Ethnicity Sex Age at Diagnosis Date of Birth Tumor Characteristics Primary Site Laterality Diagnostic Confirmation Type of Reporting Source Histologic Type Behavior Code *Excludes State E.

28 ECC Data Completeness % Missing % Concordance* ECC Full year Demographics State of Diagnosis County of Diagnosis Race Ethnicity Sex Age at Diagnosis Date of Birth Tumor Characteristics Primary Site Laterality Diagnostic Confirmation Type of Reporting Source Histologic Type Behavior Code *Excludes State E.

29 Representativeness of USCS ECC* 5-yr States* p value 5-yr USCS* p value Mean Age at Diagnosis (yrs) Sex (% Male) Race <0.01 <0.01 White (%) Black (%) Asian/Pacific Islander (%) Other (%) Unknown (%) Ethnicity (% Hispanic) <0.01 *Excludes state G

30 Representativeness of USCS ECC* 5-yr States* p value 5-yr USCS* p value Mean Age at Diagnosis (yrs) Sex (% Male) Race <0.01 <0.01 White (%) Black (%) Asian/Pacific Islander (%) Other (%) Unknown (%) Ethnicity (% Hispanic) <0.01 *Excludes State G

31 Representativeness of USCS 5-yr ECC 5-yr States USCS (%)* (%)* p value (%)* p value Site Leukemia/Lymphoma Brain & Other Nervous System Endocrine System Soft Tissue including Heart Bones and Joints Other Diagnostic Confirmation Microscopically Confirmed Laboratory/Clinical Diagnosis Unknown Behavior <0.01 <0.01 Benign Uncertain/Borderline In situ Malignant (invasive) *Excludes State G

32 *Excludes State G Representativeness of USCS 5-yr ECC 5-yr States USCS (%)* (%)* p value (%)* p value Site Leukemia/Lymphoma Brain & Other Nervous System Endocrine System Soft Tissue including Heart Bones and Joints Other Diagnostic Confirmation Microscopically Confirmed Laboratory/Clinical Diagnosis Unknown Behavior <0.01 <0.01 Benign Uncertain/Borderline In situ Malignant (invasive)

33 Representativeness of USCS data: State Comparisons States A B C D E F Overall Age <0.01 < Sex < Race < < <0.01 Site < Diagnostic Confirmation < Behavior < <0.01

34 Representativeness of USCS data: State Comparisons States A B C D E F Overall Age <0.01 < Sex < Race < < <0.01 Site < Diagnostic Confirmation < Behavior < <0.01

35 Qualitative Results Challenges Benefits Data Use Facilitators Improved Data in Data Staffing issues CDC TA Overall Registry Dissemination Potential Lack of Qualified Staff Electronic Reporting Existing Resources Data Use Staff Turnover Relationships Training Increased Commitment Work Burden Manual Abstraction Race Data Reinforcement- Reminders Timeliness

36 Qualitative Results Challenges Benefits Data Use Facilitators Improved Data in Data Staffing issues CDC TA Overall Registry Dissemination Potential Lack of Qualified Staff Electronic Reporting Existing Resources Data Use Staff Turnover Relationships Training Increased Commitment Work Burden Manual Abstraction Race Data Reinforcement- Reminders Timeliness

37 Qualitative Results Challenges Benefits Data Use Facilitators Staffing issues Improved Data in Data Overall Registry Dissemination CDC TA Potential Lack of Qualified Staff Electronic Reporting There is a shortage Data Use Existing Resources Staff of registry Turnover staff Relationships across the nation, and so we re contemplating Increased Commitment trying to figure out other ways to complete Training Work Burden Manual Abstraction Race the data activities, Reinforcement- perhaps with Reminders contractors. Timeliness

38 Qualitative Results Challenges Benefits Data Use Facilitators Improved Data in Data Staffing issues CDC TA Overall Registry Dissemination Potential Lack of Qualified Staff Electronic Reporting Existing Resources Data Use Staff Turnover Relationships Training We re doing extra Increased things to Commitment get race because they aren t on the path reports. Work Burden Manual Abstraction Race data Reinforcement- Reminders Timeliness

39 Qualitative Results Challenges Benefits Data Use Facilitators Improved Data in Data Staffing issues CDC TA Overall Registry Dissemination Potential Lack of Qualified Staff Electronic Reporting Existing Resources Data Use Staff Turnover Relationships Training Increased Commitment Work Burden Manual Abstraction Race Data Reinforcement- Reminders Timeliness

40 Qualitative Results Challenges Benefits Data Use Facilitators Improved Data in Data Staffing issues CDC TA Overall Registry Dissemination Potential Lack of Qualified Staff Electronic Reporting Existing Resources Data Use Staff Turnover Relationships Training Increased Commitment Work Burden Manual Abstraction Race Data Reinforcement- Reminders Timeliness Where we identify a problem with getting data, it applies also to adult cancers

41 Qualitative Results Challenges Benefits Data Use Facilitators Improved Data in Data Staffing issues CDC TA Overall Registry Dissemination Potential Lack of Qualified Staff Electronic Reporting Existing Resources Data Use Staff Turnover Relationships Training Increased Commitment Work Burden Manual Abstraction Race Data Reinforcement- Reminders Timeliness

42 Qualitative Results Challenges Benefits Data Use Facilitators Staffing issues Improved Data in Overall Registry Data Dissemination CDC TA Lack of Qualified Staff Electronic Reporting Potential Data Use Existing Resources Staff Turnover Relationships Training Increased Commitment Work Burden Manual Abstraction Race data Reinforcement- Reminders Timeliness when I talk about the data sources that the registry has available, I will always talk about the early case capture cases.

43 Qualitative Results Challenges Benefits Data Use Facilitators Improved Data in Data Staffing issues CDC TA Overall Registry Dissemination Potential Lack of Qualified Staff Electronic Reporting Existing Resources Data Use Staff Turnover Relationships Training Increased Commitment Work Burden Manual Abstraction Race Data Reinforcement- Reminders Timeliness

44 Qualitative Results Challenges Benefits Data Use Facilitators Improved Data in Data Staffing issues CDC TA Overall Registry Dissemination Potential Lack of Qualified Staff Electronic Reporting Existing Resources Data Use We ve Staff Turnover Relationships discovered Training Increased Commitment Work Burden Manual Abstraction Race data Reinforcement- Reminders Timeliness some of the best cooperation by really just asking facilities to send this to us.

45 Common Themes ECC involves a significant work burden Increased time commitment Staffing issues Collection of race information Electronic reporting increased ECC utility Facilitated reporting when in place Addition benefited all registry reporting Added sustainability to ECC

46 DISCUSSION

47 Summary Data completeness Three variables do not meet standards High concordance with full year submission Representativeness Highly representative of full year submission data Moderately representative of USCS data Only two states were not representative for more than one variable Main issues observed were collection of race and some tumor information

48 Common themes Summary Rapid reporting places additional work burden on registries and reporting facilities Staffing issues and training can adversely affect ECC progress Manual abstraction of cases is time and labor intensive Electronic reporting facilitated timeliness Electronic reporting infrastructure improves registry Low current data usage but great potential

49 Limitations Only 7 states participated in ECC 2 states were excluded from parts of the quantitative analysis Only data from first ECC submission was analyzed Due to the lag time in cancer reporting, direct ECC- USCS comparisons could not be made Qualitative analysis was limited to interviews with state cancer registry staff

50 Public Health Impact Pediatric cancer is the 2 nd leading cause of mortality in children Pediatric ECC has potential to Increase the pool of timely data available for research Improve comprehensive cancer control planning in states Increase enrollment on clinical trials Improve identification of childhood cancer survivors ECC could serve as a model for future rapid reporting programs

51 Recommendations Increase number of states involved Improve representativeness and completeness Develop training modules Encourage epath in all facilities Communicate data availability Promote and evaluate data use Clinical research enrollment Academic research Expand ECC to adult cancers

52 Acknowledgements Division of Cancer Prevention and Control Comprehensive Cancer Control Branch o Dr. Antonio Neri o Dr. Mike Underwood o Dr. Elizabeth Rohan o Dr. Sherri Stewart Cancer Surveillance Branch o Castine Clerkin o Dr. Christie Eheman o Dr. Blythe Ryerson State Cancer Registries California Kentucky Louisiana Minnesota Nebraska New York Oklahoma Macro International

53 Thank you For more information please contact Centers for Disease Control and Prevention. You may contact me at 1600 Clifton Road NE, Atlanta, GA Telephone: CDC-INFO ( )/TTY: Visit: Contact CDC at: CDC-INFO or The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion Division of Cancer Prevention and Control