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Assessing Minority Participation in Clinical Trials: Setting Attainable Goals. The Minority and Women Clinical Trials Recruitment Program Department of Health Disparities Research Division of Cancer Prevention and Population Sciences Presented to 2009 CCOP Annual Investigators’ Meeting
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Assessing Minority Participation in Clinical Trials: Setting Attainable Goals The Minority and Women Clinical Trials Recruitment Program Department of Health Disparities Research Division of Cancer Prevention and Population Sciences Presented to 2009 CCOP Annual Investigators’ Meeting 03/28/09 Lynne H. Nguyen, MPH
Overview • Reported clinical trial participation rates • Selecting a methodology • The impact of population demographics • Determining success
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
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
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
Reportable cancers**N=17,282 Interventional trial Pp n=6,302 (6,302/17,282=36%) Malignant N=19,597 FY07 all new pts* N=21,647 Non-Interventional trial Pp n=6,403(6,403/17,282=37%) Superficial cancers N=2,315 Non-malignant N=2,050 Not Pp, n=4,577 (4,577/17,282=26%) Estimating Patient Participation Rate ICD-O codes ending in 2 or 3 * Excludes non-patients on trials, i.e. for behavioral and some epidemiologic trials ** Reportable cancers includes 2nd opinions, consults, and preventive screenings)
MDACC Patient Participation on Clinical Trials, FY07 Snapshot
Is this REASONABLE?! Core Grant reviewer comment (2002): “Goal should be to achieve accrual that approaches the City of Houston catchment area population.”
Impact of Population Demographics Who is at highest risk for cancer? OLD people! Who is old in Texas?
Percent of Texas Population by Age Groupand Ethnicity, 2000 TX State Data Center
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
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
Assessing Reasonableness Who comes into the Center Who gets on a trial Who gets cancer
Assessing Accrual of Non-patients to Prevention/Behavioral Trials
Other Variables to Consider • Race/ethnicity • Age • Gender • Geography • Cancer site, stage • Clinical trial type/phase
A modified option, to assess non-therapeutic CT participation • 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. Everyone who comes into the Center Everyone who gets on a trial Who gets cancer
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!