1. Social Epidemiologic Methods in International Population Health and Health Services Research A Research Agenda Using Cancer Care as a Sentinel Indicator: By Kevin M. Gorey

2. Kevin M. Gorey Kevin is a social epidemiologist and social welfare researcher interested in advancing understandings about how health care policies affect health. He is particularly interested in the impacts of various under- and uninsured statuses in the US. His web page is: www.uwindsor.ca/gorey www.uwindsor.ca/gorey

3. Cancer Survival in Canadian and United States Metropolitan Areas: A Series of Studies Between-Country Effect Modification by Socioeconomic Status (Health Insurance)

4. Research Team and Reports Kevin Gorey, University of Windsor Eric Holowaty & Gordon Fehringer, CCO Erich Kliewer, Cancer Care Manitoba Ethan Laukkanen, WRCC and Colleagues Study series reports: Am J Public Health 1997 & 2000 Can J Public Health 1998; Milbank Q 1999 J Public Health Med 2000 J Health Care Poor Underserved 2003 Ann Epidemiol 2003

5. Introduction Mid-1980s to Mid-1990s: Historical and Theoretical Contexts

6. Historical Context -Canada: Universal single payer -US: Multi-tiered—uninsured and underinsured, Medicaid, Medicare, continuum of private coverages -Time of great systemic changes -Managed care proliferation (US) -Federal-provincial shift (Canada)

7. Politics Versus Science -Political debates tend to mythologize anecdotal outcomes. -Rhetoric often not substantiated (e.g., 2 Manitoba studies) -Waits for 10 surgical procedures stable or decreased 5 yrs post-downsizing -Access to surgery actually increased after hospital downsizing (maintaining quality [mortality, readmissions])

8. Cancer Survival is a Sentinel Health Care Outcome -Relatively common over the life course -Diverse constellation of diseases -Many with good prognoses and high quality of survivable life -Diverse screens (including primary care) and treatments exist and matter -Timely access, referral and follow-up matter

9. Theoretical Context: Systematic Literature Review -In the US, ethnicity and SES are strongly associated with health insurance statuses (odds ratios [OR] 2.0 to 15.0). -All are also strongly associated with cancer screens, stages at diagnosis and access to treatments (ORs 2.0 to 5.0). -Such Canadian associations tend to be attenuated or nonexistent. For example: -US SES-cancer survival OR = 1.56 -Canadian OR = 1.04 (NS) to 1.18

10. SES: A Key Effect Modifier? Therefore, any Canada-US cancer outcome study that does not incorporate SES is unlikely to observe the truth. -SES is so intimately connected with health in North America that it must be incorporated into all such studies. -If an interaction exists, interpretations of main effects alone can be misleading.

11. SES: An Effect Modifier? E.G. -One previous study of Canada-US cancer survival (GAO, 1994) -Found no between-country differences -But, did not account for SES -We have observed a substantially different picture within SES strata. -Consistent Canadian advantages within the lowest SES strata

12. A Country By SES Interaction Hypothesis Guided Our Series Relatively poor Canadian cancer patients (better insured) would enjoy advantaged survival over their similarly poor counterparts in the United States. -We think this a better guide to policy- interesting and important research questions in North America than those provided by main effect country-based hypotheses.

13. Methods A Focused Series of Cancer Survival Comparisons Among Relatively Poor Residents of Canadian and American Metropolitan Areas

14. Comparative Series Overview Toronto, Ontario vs Detroit, Michigan An ecological exemplar Toronto vs San Francisco, Seattle, Hartford Adjustment for absolute income Toronto vs Honolulu, HI Health insurance hypothesis test Winnipeg, Manitoba vs Des Moines, Iowa Replicate among smaller cities Comparisons of Subsamples < 65 yoa Health insurance hypothesis test

15. Sampling—Persons/Cancer Patients -Ontario and Manitoba Registries, SEER -First, primary invasive cancer cases -MC, not DC or autopsy only -With minimum 5 years follow-up -Began 15 most common cancers -Since focused on most significant -Estimated case ascertainments, MC, and follow-ups all > 95% (DCO/Autopsy < 1%) - Even better among the most public health-significant cancer types

16. Honolulu, Breast Cancer, 1986-1990 SESMC%DCO/Autopsy% High100.00.0 100.00.0 98.50.7 97.90.0 Low98.90.0

17. Sampling—Places: Rationales For Metropolitan Sampling -Maximize internal validity -Higher: MC, follow-up, geocoding rates -Lower: DCO or autopsy only -Maximize external validity -Vast majority of NAs urban residents -1 of 3 Ontarians and 1 of 7 Canadians reside in Toronto -Control for service availability

18. Sampling—Places: Ecological Measures of SES Neighborhoods No NA registries coded personal SES. -Census tracts joined cases at diagnosis to income data (US Census, Stats Can) -Neighborhood prevalence poor -Theory, insurance, practical sig. -Poverty (US), low income (Canada) -Both household income-based and tied to the consumer price index -Though Canadian criterion more liberal -Used to form relative SES quantiles

19. Comparison of SES Quintiles: 1990/91, US$ WinnipegDes Moines SESMdn $Mdn $ High$47,090$44,050 39,11036,370 32,26530,165 26,04326,890 Low17,50019,570 Lowest US SES quintile: 20% poor, another 45% near poor; estimated (vs highest) uninsured PR = 10.0, underinsured PR = 15.0

20. Results Female Breast Cancer—5-Year Survival—As Exemplar Throughout

21. SRRs With 95% CIs, 1984 to 1994 SESTorontoDetroit High1.00…1.00… 1.00(0.94,1.06)0.94(0.88,1.01) Low0.98(0.93,1.04)0.80(0.75,0.85) No significant between-country differences in the middle or high income areas Low income areas: Between-country SRR = 1.30 (1.23,1.38), Canadian patients advantaged

22. SRRs With 95% CIs, 1986 to 1996 SESTorontoHonolulu High1.00…1.00… 1.01(0.93,1.10)0.94(0.82,1.07) 1.01(0.95,1.08)0.93 (0.81,1.06) 1.03(0.96,1.11)0.97 (0.86,1.09) 1.04(0.97,1.12)0.93(0.81,1.07) 0.97(0.90,1.04)0.80(0.69,0.93) 1.00(0.81,1.24)0.90(0.79,1.02) 1.03(0.95,1.11)0.97 (0.87,1.09) 1.05(0.98,1.13)0.91(0.80, 1.04) Low1.02(0.95,1.10)0.78(0.67,0.91)

23. Toronto-Honolulu Between- Country Survival Outcomes The only significant decile difference was for the lowest income area: SRR = 1.20 (1.06, 1.36) Canadian patients advantaged Among those < 65 yoa: SRR = 1.28 (1.07,1.53)

24. Discussion The Screened/Developed Health Insurance Hypothesis Versus Alternative Explanations

25. Summary: Health Insurance -Consistent SES-cancer survival associations in US, but not Canada -Consistent country-SES interactions -Canada advantage lowest SES strata -Particularly among those < 65 yoa -Consistency of pattern across diverse contexts—people and places—points toward a pervasive systemic effect -285 of 319 between-country comparisons were in support of the health insurance hypothesis

26. Alt 1 —Income Gap or Inequality Larger in the United States? -For some of our studies, the economic divide is actually larger in the Canadian sample. -E.g., Winnipeg vs Des Moines

27. Alt 2 —Ethnic or Cultural Explanations? -Similar pattern of findings observed among various ethnic mixes -North American studies of race/ethnicity and cancer screening have implicated knowledge (education), rather than race, per se. -Consistent indictment of America: Inequitable distribution of key social resources—education and health care

28. Alt 3 —Lifestyle Factors (LS): Exercise, Diet, BMI, Tobacco and Alcohol Consumption? -Associations with cancer survival tend to be extremely small -Larger associations with incidence -Survival findings consistent across cancers with diverse component causes -Some LS factors very sig., others not -Income is associated with lifestyle in both countries, but no income-survival gradients were observed in Canada -Little to no Canada-US LS prevalence differences (2%) have been observed

29. Alt 4 —Different Case Mixes by Stage of Disease at Diagnosis? -Stage differences may account for some, but probably not all of the between- country survival differences. -In within-US stage-adjusted analyses, treatment differences still account for roughly 50% of survival variabilities.

30. Alt 5 —Cancer Registry Death Clearance? National (US) vs Provincial (Canada) -Over the life of these studied cohorts, only 1-3% of Toronto residents moved out-of-province. -Likely fewer chronically ill moved -Ontario Cancer Registry comparisons of national and provincial death clearances found inconsequential differences.

31. Alt 6 —Competing Causes of Death (Observed vs Relative Survival)? -Life expectancy in Honolulu among both women and men is close to 3 years greater than in Toronto -Therefore, our between-country SRRs (Canadian advantage) may actually underestimate the truth

32. Alt 7 —Lead Time Bias? -Our findings were fairly consistent across different cancers probably with various pre-clinical phase lengths. -A systematic review of 87 studies (with adjustment for lead-time) observed stage and treatment effects (Richards et al., 1999, Lancet)

33. Alt 8 —Ecological Fallacy? -Even if it were merely an area effect, the consistently observed residence- survival association in the US, but not in Canada would still be instructive. -The compositional measure (% poor and near poor in neighborhoods) is well known to be intimately associated with under-and uninsured statuses in the US.

34. Future Research Needs Health Insurance Hypothesis Developed and Screened With An Ecological—Income—Proxy: More Definitive Testing Needed

35. Central Research Needs -Study more recent retrospective and prospective cohorts -Perform stage-stratified analyses -Incorporate treatment variables -Extend generalizability to smaller urban and rural-remote places -Develop construct validity of ecological SES measures in Canada

36. Our Research Agenda Over The Next 5 Years Endeavoring to Filling Some of This Field’s Central Knowledge Gaps

37. Social, Prognostic & Therapeutic Factors Associated With Cancer Survival in Canada and the US Health Care Access and Effectiveness in Diverse Urban and Rural Contexts, 1985 to 2010

38. Research Team Co-Investigators Kevin Gorey (PI) & Emma Bartfay (Epidemiology) Karen Fung (Biostatistics) Isaac Luginaah (Geography) Frances Wright (Surgical Oncology) Caroline Hamm & Sindu Kanjeekal (Medical Oncology) Eric Holowaty & William Wright (Cancer Surveillance & Registration)

39. To Address Identified Research Needs, It Will: -Study more recent retrospective and prospective cohorts -Perform stage-stratified analyses -Incorporate treatment variables -Extend generalizability to smaller urban and rural-remote places -Develop construct & predictive validities of ecological SES measures in Canada

40. Cohort Design Incident cohorts: 1985-1990 & 1995-2000 Followed until: 2000 2010 Cox models over 1-, 3-, 5- to 10-years In Canada and the US During a policy-interesting period -Federal-provincial shift in Canada -For-profit managed care proliferation & prevalent increases uninsured in US

41. Staged Analyses No Canadian cancer registry routinely codes stage of disease at diagnosis. -Thus, no previous study in this field has been able to account for case-mix. Stage will be abstracted for this study’s samples. Allowing for: -More comparable between-country comparisons -Examination of the relative weightiness of pre- (affect later diagnosis) and post- diagnostic (affect lack of access to best treatments and follow-up) social forces

42. Incorporation of Treatments No Canadian cancer registry routinely codes initial treatments. -Thus, no previous study in this field has been able to account for them in survival analyses. Detailed treatment variables will be abstracted for this study’s samples. -Surgery, radiation, chemotherapy and others - Initial course and follow-up - Type, dose, delays, timings/sequence between various therapies

43. Extending Generalizability: Contexualizing Knowledge Systematic Replications in: Ontario California Large cities Toronto San Fran/Oakland Small cities Windsor Salinas Rural/remote areas of Ontario & California 1,060 breast and colon cancer cases for each incident cohort in each type of place

44. Ecological Measurement Validity Ontarian and Californian cancer cases will be joined via their residential census tracts to the following data: -Income (poverty prevalence) and -Physician supplies (count/10,000 pop) - Primary care and specialists This will provide opportunities to better understand the meanings of such ecological measures, particularly in Canada, where little is yet known about them.

45. Hypotheses Related to Survival 1.Significant country by SES interaction (Canadian advantage low-income only) 1a.Advantage significantly increased over time 2.SES-survival significant in US (not in Canada) 2a.Age by SES interaction (Medicare advantage) 2b.US gradient significantly increased over time 3.Physician supplies-survival associations significant in both Canada & US (for both primary care and specialists supplies)