USING REAL-WORLD CLAIMS DATA FOR PLANNING ONCOLOGY CLINICAL TRIALS

Author(s)

Foley KA*1, Hansen LG2 1Truven Health Analytics, Cambridge, MA, USA, 2Truven Health Analytics, Northwood, NH, USA

OBJECTIVES: To understand the value of quickly estimating the impact of certain inclusion/exclusion criteria on a potential clinical trial population using real-world administrative data. METHODS: Using the Treatment Pathways tool and data from an 8-year oncology subset of the 2004 – 2012 MarketScan®databases, we identified patients with castrate-resistant prostate cancer (CRPC) with at least six months of history. From these patients, we identified cohorts with definitive exclusions (brain metastasis or other primary cancer) and time-dependent exclusions (based on radiation or treatments).  Seven of 12 exclusion criteria were identifiable within the claims database. RESULTS: Inclusion criteria identified 2,329 patients with CRPC based on two prostate cancer diagnoses, medical or surgical castration and receipt of docetaxel. Of them, 1370 (59%) had 6 months of follow-up data for evaluation of exclusion criteria.  Among the 1370 patients, 248 (18%) met none of the exclusion criteria, while 482 patients (35%) had  brain metastasis and/or other cancers. The remaining 640 (47%) had at least one time-dependent exclusion, including 534 receiving corticosteroids, 136 receiving androgen receptor and reductase inhibitors, 86 receiving radiation and 31 with ketoconazole.  These patients could be trial-eligible depending on the timing of treatment cessation and trial recruitment. CONCLUSIONS: This study demonstrates a method to understand the impact of specific inclusion/exclusion criteria on a potential clinical trial population in just a few hours using an online pathway creation tool and administrative data representing millions of patients. Using this method, trial planners can evaluate different scenarios to quickly and easily determine estimated attrition rates helping them to maximize potential recruitment success. Limitations exist due to the timing of exclusions and data on lab results included in the exclusion criteria that were unavailable in this subset of claims data.

Conference/Value in Health Info

2013-05, ISPOR 2013, New Orleans, LA, USA

Value in Health, Vol. 16, No. 3 (May 2013)

Code

PRM213

Topic

Study Approaches

Disease

Oncology

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