The high cost of source data verification (SDV), particularly in large trials, has made it a target of scrutiny over the last decade. In addition, the positive impact (ie, cost-benefit ratio of SDV) on overall data quality is often questioned. As a result, regulators and industry groups have started looking at alternative SDV approaches. This article evaluates the FDA-supported risk-based approach to SDV and provides a proposal on how to modify the SDV process without undermining the validity and integrity of the trial data. It summarizes alternative approaches to 100% SDV and evaluates the advantages and disadvantages of risk-based SDV (rSDV). The regulatory, data quality, and cost implications of each approach are considered. The economics of rSDV are discussed and the cost implications of rSDV are presented based on the results of exploratory analyses for four hypothetical trials in cardiology and oncology.
The use of a single central laboratory with universal references ranges is not always a viable option in clinical studies; examples are oncology studies where a rapid turnaround of clinical laboratory results is critical. However, the complexities associated with multiple sites, multiple laboratories, and multiple age and sex groups can lead to logistical nightmares across clinical trials and make handling laboratory data one of the most challenging, labor-intensive, and time-consuming tasks for clinical data managers, especially where different laboratories are used for the same patient. Also, evidence suggests that the reference ranges (RRs) used by the local laboratories often create a false sense of precision that is not always supported by science. Managing time-specific, demographic-specific, and site-specific RRs requires significant investment in time and labor. As a result, an alternative approach to management of local laboratory RRs that uses ''standard'' (sometimes called ''published'') ranges has been growing in popularity over the past several years. This article attempts to compare the pros and cons of this approach relative to the historic ways of handling local laboratory RRs. Scientific, operational, and economic perspectives are also presented.
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