1. Prostate cancer isn’t colorblind
Ruth Etzioni
Roman Gulati
Lurdes inouE
Dhamanpreet Kaur
Fred Hutchinson cancer research center

2. TODAY’S PRESENTATION Trends in prostate cancer incidence and mortality
What are the trends really telling us? A mathematical model
Prostate cancer disparities research needs and key questions
Discussion and brainstorming session

3. Prostate cancer trends in the us population a dramatic and persistent disparity
Cases
Deaths
52% decline
51% decline
convergence?
Screening begins
Screening begins

4. From: Trends and Patterns of Disparities in Cancer Mortality Among US Counties, 1980-2014
JAMA. 2017;317(4): doi: /jama

5. From: Trends and Patterns of Disparities in Cancer Mortality Among US Counties, 1980-2014
JAMA. 2017;317(4): doi: /jama

6. Trends in prostate cancer survival by race
2014

7. TODAY’S PRESENTATION Trends in prostate cancer incidence and mortality
What are the trends really telling us? A mathematical model
Prostate cancer disparities research needs and key questions
Discussion and brainstorming session

8. ten-year disease-specific survival differences: are disparities narrowing?

9. Survival disparities pre and post PSA

10. Changes in Survival disparities: reality versus artifact
Change in survival from diagnosis during the PSA era depends on:
Overdiagnosis
Lead time
Screening benefit
Treatment changes/benefit
If we knew overdiagnosis and lead time could we learn about how screening and treatment changes are truly benefitting men in the population setting?

11. The effects of overdiagnosis and lead time
Cases overdiagnosed cannot die of prostate cancer
Cases overdiagnosed inflate survival
Lead time
Time by which diagnosis is advanced by screening
Improves survival even if screening does lengthen life expectancy
Iead time

12. Estimate overdiagnosis and lead time from population incidence
Learn about overdiagnosis and lead time from
Height and width of peak in incidence after screening starts
Level of incidence after screening stabilizes
Use a disease model
Estimate risks of progression events that determine lead time and overdiagnosis
Onset, progression risks, other-cause death
Requires data on patterns of screening in the population

13. Patterns of PSA screening in the US
Source: NHIS + SEER- Medicare data
Mariotto et al Cancer 2007 Reconstructing PSA testing patterns between black and white men in the US from Medicare claims and the National Health Interview Survey

14. Fred hutch model of prostate cancer
Progressive natural history comprised of
Onset of low or high-grade disease
Progression to clinical presentation
Progression to distant stage
Estimate risks of onset and progression to distant stage and clinical diagnosis consisting with stage and grade specific incidence trends
Use results to derive fraction overdiagnosed and mean lead time under population screening patterns
Gulati, Gore, Etzioni Annals of Internal Medicine 2013; also Biostatistics 2010

15. Fred hutch model – All races fit to incidence by age and stage
Reduction in distant stage drives screening benefit

16. Lead time and overdiagnosis – all races

17. Prostate cancer, race and risk Observed and modelled incidence by race and stage
ALL MEN
BLACK MEN
Tsodikov, et al Cancer 2017

18. Lead time and overdiagnosis – all races and blacks
Kaur et al Cancer 2018 in press

19. Fraction of the change in survival that is artifact
Post-PSA
Pre-PSA
51%
100%
Pre-PSA +
LT+odx
Generate a survival time from grey curve
Add lead time from model
Add a fraction with survival=1
46%
98%
Kaur et al Cancer 2018 in press

20. Fraction of the change in survival due to artifact
All races
Black men

21. What is the real change in survival?
Survival during the PSA era can be expressed as pre-PSA survival modified by
Overdiagnosis and lead time
Real screening benefit for those not overdiagnosed
Real (non-screening benefit) for everyone e.g. due to treatment improvements

22. Primary treatment frequencies
Source – SEER

23. What is the real change in survival?
Survival during the PSA era can be expressed as pre-PSA survival modified by
Overdiagnosis and lead time
Real screening benefit for those not overdiagnosed
Real (non-screening benefit) for everyone e.g. due to treatment improvements
Real screening benefit
(Mortality rate ratio)
Non-screening benefit (treatment): Blacks
Non-screening benefit (treatment): All races
0.5
0.73
0.74
0.6
0.70
0.71
0.7
0.67
0.68
0.8
0.65
0.66
0.9
0.62
0.64
1.0
0.60
Benefits expressed as rate ratios
Kaur et al Cancer 2018 in press

24. Are the disparities narrowing?
Absolute mortality disparities are narrowing
Relative mortality disparities have remained relatively constant
Survival disparities are narrowing
Much of the observed change is due to screening artifacts particularly in older men
The real improvements seem to be similar in black men and the general population
In a certain sense disparities are not narrowing as much as we think
Mortality rate in blacks still double that in whites
What can be done?
Annual age-adjusted prostate cancer mortality among blacks and whites from
O’Keefe et al Frontiers in Public Health 2015

25. Is prostate cancer different in black men?

26. Prostate cancer, race and risk Observed and modelled incidence by race and stage
ALL MEN
BLACK MEN
ALL MEN
BLACK MEN
Onset in lifetime
29%
45%
Mets at dx given onset 6%
10%
Mean lead time
7.3 years
7.4 years
Fraction overdiagnosed
43%
40%
Tsodikov, Gulati, …. Etzioni Cancer 2017

27. Implications of model results for screeninG
Cumulative incidence* of latent prostate cancer that would be lethal if left untreated
USPSTF 2017: US men age 55 should discuss prostate screening with their MD
Among blacks incidence of potentially lethal disease reaches a level at age 45 that matches all races at age 55
Implications for black men
Discuss with their MD’s at age 45
Potentially screen more frequently subject to careful harm-benefit analysis
*Survival in the absence of screening or treatment is based on pre-PSA-era diagnoses by race

28. More frequent screening and overdiagnosis in a high-risk population
Results from Fred Hutch model of prostate cancer progression and survival
Treatment distributions for blacks and all races based on SEER 2012 data
Similar treatment efficacy for blacks and all races
More frequent screening modestly increases lives saved but also increases overdiagnosis

29. Conclusions
Major improvements in prostate cancer mortality attributable to combination of screening and treatment advances
Black men have adopted screening at almost the same frequency as the general population especially younger men
Curative treatment frequencies are similar but less frequent RP in older black men
Unclear whether quality of delivered screening and treatment is similar
Prostate cancer is different in black men
Black men have higher risk of onset at all ages and greater risk of progressing to metastatic disease without screening
May need different screening approaches and potentially also different treatment approaches
Ultimately quality of research and recommendations will depend on the quality and extent of the data that can be sourced to inform about differences in treatment and outcomes across the continuum of care

30. Disparities in quality of care example – bladder cancer
Black patients with BCa had lower use of experienced providers and institutions for BCa surgery. In addition, the quality of care for black patients was lower than that for whites even if they received treatment in a high-volume setting. This gap in quality of care requires further investigation

31. The problem of data
Need data on detection, treatment and outcomes across the continuum of care
Existing sources
CaPSURE
PCOS
NCDB
CRN?
Single (referral institutions)
JHU
Mayo Clinic
MSKCC
Problems: numbers, representativeness, comprehensiveness of clinical records
Other ideas?
An AA-(M)PC project?

32. Proposing a Fred Hutch Task Force on disparities in urologic health
Possible year 1 objectives
Apply for DOD funding for a disparities analytics project
Secure novel data resources for studying quality of surveillance and treatment
Establish connections with advocacy groups focuses on prostate cancer in African-American men
Fred Hutch task force on
Disparities in
Urologic
Health

33. acknowledgments Roman Gulati Lurdes Inoue Dhamanpreet Kaur
Alex Tsodikov (Michigan)
Harry de Koning (Erasmus)
Eveline Heijnsdijk (Erasmus)
Angela Mariotto (NCI)
Eric Feuer (NCI)