Early Identification of Patients for Clinical Trials and Special Studies with Custom Metafile NAACCR, June 18, 2009 Alan R. Houser, MA, MPH C/NET Solutions Berkeley, CA Linda K. Fine, CTR Loma Linda University Medical Center Loma Linda, CA

Thank you to Deb Hilton, RN Loma Linda University Medical Center

The Issue Clinical Trials need cancer patients Cancer Registries have cancer patients How do we get these two together?

Finding Clinical Trials ClinicalTrials.gov NCI website for searching clinical trials database by key words Works well for matching one patient to appropriate trials Requires separate searches when looking for multiple patients Requires active search to match trials to patients

Finding Clinical Trials - 2 How do Clinical Trials find patients? There is no web site for trials to find patients Matching patients manually is very time- consuming, especially for major sites Searching registry databases requires sophisticated queries, customized for each trial Changes require changes to queries, may not be simple in complex query statements

Why not use EDITS? The CDC EDITS tools (EditWriter, Edit Engine, GenEdits Plus) are designed for looking at standard cancer registry data set Portable – one metafile can be distributed to many registries One trial changes (open, close): only one edit needs to be changed

Why not use EDITS? - 2 Cancer patients may be eligible for some trials right after diagnosis For other trials, they might not be eligible until after first course therapy or after a recurrence Requires a flexible strategy to match patients against both types of trial and others that fall between

Feasibility Study (2007) Used a NAACCR export of breast, prostate, and lung cases from the California Cancer Registry (dx ) Five trials for each site: 4000 to 15,000 cases per site Edits Metafile reduced the number of patients to screen manually by 59% to 99% of cases for fourteen of the trials

Writing an Edit for a Clinical Trial Search Think backwards Only cases who “fail” an edit get listed Account for missing data Eliminate cases who don’t match but keep if don’t know Programmer needs to work with CTR

Pilot Study at Loma Linda Selected two breast cancer trials Chemotherapy With or Without Bevacizumab in Treating Women With Stage I, Stage II, or Stage IIIA Breast Cancer That Can Be Removed By Surgery (NSABP B-40) Anastrozole With or Without Fulvestrant as First-Line Therapy in Treating Postmenopausal Women With Metastatic Breast Cancer (SWOG S0226)

Going to work…. Created subfile of 372 living breast cancer cases diagnosed Applied batch edits to subfile 58 cases matched to SWOG S cases matched to NSABP B-40 6 cases matched to both trials 312 cases (84%) not matched to either trial

Results: NSABP B-40 8 patients identified by edit (2.2%) On manual review, 3 of these patients were already in this trial 3 of these patients were eligible for the trial 6 positive matches (75% of 8, 2.2% of 372)

Results: SWOG S patients identified by edit (16%) On manual review, 3 of these patients were already in this trial 7 of these patients were eligible for the trial 10 positive matches (17% of 58, 2.6% of 372)

Results: Hours/Case By screening 372 patients, we found 1 case for every 93 hours for B hours for SWOG S0226 By screening the filtered lists, we found 1 case for every 2 hours for B hours for SWOG S0226

Results: Non-matches 312 patients were not identified as eligible by either edit At ninety minutes to screen a case, this represents over 460 hours saved On manual review of 2008 cases previously screened, 3 cases already on trial were identified No cases not eligible were identified by metafile

Recap... NSABP B-40

Recap... SWOG S0226

Application to Registry Operations Before a new trial opens (feasibility) Batch processing While casefinding (electronic and manual) While abstracting While adding follow-up

Limitations to Metafile Screening Edits are limited to data fields collected by registry, e.g. Her2/neu status only collected in California Menopausal status Performance status Delayed identification by deferred abstracting

What’s Next? Looking at identifying eligible patients via electronic casefinding: Radiology reports Path reports Disease index EMR New data items in 2010

Summary - 1 Edits were written for screen breast cancer patients for two clinical trials and applied to registry records of all living breast cancer patients diagnosed 2007 to 2009

Summary % of the 372 patients were eliminated by the metafile, saving over 460 hours of manual screening

Summary patients already on trial and 10 patients eligible for the trials were detected by the metafile after manual screening of the remaining 60 cases.

For more information, Alan R. Houser C/NET Solutions