Assessing Minority Participation in Clinical Trials: Setting Attainable Goals The Minority and Women...

Assessing Minority Participation in Clinical Trials: Setting Attainable Goals

The Minority and Women Clinical Trials Recruitment Program

Department of Health Disparities ResearchDivision of Cancer Prevention and Population SciencesPresented to 2009 CCOP Annual Investigators’ Meeting03/28/09

Lynne H. Nguyen, MPH

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Overview• Reported clinical trial participation rates• Selecting a methodology• The impact of population demographics• Determining success

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Clinical Trial Participation: The Assertions• Only 3% of adults with cancer

participate on cancer clinical trials – NCI

• …even smaller number of patients come from minority backgrounds – Galen, 2009

• Hispanics participate at far below their representation in the population – FDA, 2001

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Clinical Trial Participation: The Evidence• NCI estimate based on ratio of patients on NCI cooperative group

trials (NCI-sponsored) to all Americans with cancer (SEER registry)… “only 2.5% of all cancer patients enter cooperative group clinical trials”

• Participation rates (all): 2.5%Non-Hispanic whites: 2.4%Non-Hispanic blacks: 2.6%Hispanics: 4.2%

• Need to compare apples to apples . . . people in trials to people with the disease

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The True Participation Rate…?

“Of patients medically eligible for a trial, and were offered a trial, what percentage agreed to go on the trial?” Some challenges:• Who to include in the denominator?• CT not the best treatment option for all patients• CT not available for all pts • What trials are available?• Participation includes both accrual and retention• Race/ethnicity and other data (lack of)• How to assess accrual effectiveness for non-patients? • Resources to track data

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FY07 all new pts* N=21,647

Malignant N=19,597

Reportable cancers**N=17,282

Interventional trial Pp n=6,302

(6,302/17,282=36%)

Non-Interventional trial Pp n=6,403

(6,403/17,282=37%)

Not Pp, n=4,577(4,577/17,282=26%)

Superficial cancers N=2,315

Non-malignant N=2,050

ICD-O codes ending in 2 or

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Estimating Patient Participation Rate

* Excludes non-patients on trials, i.e. for behavioral and some epidemiologic trials

** Reportable cancers includes 2nd opinions, consults, and preventive screenings)

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MDACC Patient Participation on Clinical Trials, FY07 Snapshot

36 37

32

36

27

37 3836

38

26

0

5

10

15

20

25

30

35

40

All White Sp surname Black Other

Per

cent

Intvn Non-Intvn

Is this REASONABLE?!

Core Grant reviewer comment (2002): “Goal should be to achieve accrual that approaches the City of Houston catchment area population.”

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Impact of Population DemographicsWho is at highest risk for cancer?

OLD people!

Who is old in Texas?

47%

69% 69%

17%20%

38%

11%8%

11%

3%3%4%

0%

20%

40%

60%

80%

TX Pop 2008 TX Pop 65+ TX ca pts 01-05

White

Hispanic

Black

Other

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Percent of Texas Population by Age Groupand Ethnicity, 2000

39.541.6

45.0 45.043.1 44.4

47.8

53.0

57.260.2

63.566.4 67.1

72.6

44.041.3

38.0 38.440.5

38.635.3

30.5

26.724.2

22.420.6 20.3

16.7

< 5

year

s

5 to

9 y

ears

10 to

14

year

s

15 to

19

year

s

20 to

24

year

s

25 to

29

year

s

30 to

34

year

s

35 to

39

year

s

40 to

44

year

s

45 to

49

year

s

50 to

54

year

s

55 to

59

year

s

60 to

64

year

s

65 +

yea

rs0.0

20.0

40.0

60.0

80.0Percent

Anglo HispanicTX State Data Center

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Other Impacts of Population Demographics• New immigrants (from w/in and outside U.S.)

Tend to be younger, sometimes more males Protective immigrant effect (from outside U.S.) Cultural beliefs and behaviors which can impact cancer risks Health literacy and linguistic competency

• Occupation Health insurance coverage Occupational risk exposures

• Geographic dispersal Rural/urban Availability/access to services

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Selecting the Right Populations to Compare

• Define the community/catchment area• Look at cancer rates as well as proportions

Rates identify populations at higher risk. Proportions show your patient base.

• Define the denominator and numerator (patient population)

• Compare apples to apples

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Assessing Reasonableness

Who gets cancer

Who comes into the Center

Who gets on a trial

69%72%

75%

12%14%17%

9%10%11%

3%4%3%

0%

20%

40%

60%

80%

Catchment MDA pts CT Pps

White

Hispanic

Black

Other

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Assessing Accrual of Non-patients to Prevention/Behavioral Trials

47%42%

39%

12%

6%

69% 69%

17%20%

38%

11%8%

11%

3%3%4%

0%

20%

40%

60%

80%

TX Pop2008

TX Pop 65+ TX ca pts01-05

Trial Pp

White

Hispanic

Black

Other

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Other Variables to Consider

Race/ethnicity Age Gender Geography Cancer site, stage Clinical trial type/phase

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A modified option, to assess non-therapeutic CT participation

Who gets cancer

Everyone who comes into the

Center

Everyone who gets on a trial

• People in the numerator not necessarily in the denominator.

• This provides a snapshot in time. Not “real” numbers, but useful for looking at trend over time.

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In Conclusion…• There are more than one way to assess

effectiveness at recruiting to clinical trials. • Know the intricacies and limitations of your

data – precise definition of what is collected, what isn’t, and how it’s collected

• Understand your catchment area demographics, trends and drivers

• Collect the right data!

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THANK YOU!