A modeling study found that user variability when measuring subcutaneous tumors may affect whether animal model studies come to accurate conclusions. These findings were published in Cancer Informatics.

To measure tumor progression and response, subcutaneous xenograft models are used in clinical trials. The most common measurement modes include calipers, 3-dimensional (3D) imaging with a thermal signature, magnetic resonance imaging, or computed tomography. Previous study has found that study outcomes can be affected by user-related tumor measurement variability.

The objectives of this study were to evaluate the interoperator variability of tumor assessment. As true outcomes are nearly impossible to determine, the authors used a mathematical simulation approach to model user variability and focused on calipers and 3D imaging modalities. They created a control group and intervention group in which the only group difference was group volume averages. User measurement characteristics were defined for each measurement device on the basis of 15 users included in 9 in vivo rodent studies.


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For a range of scenarios, 3D imaging consistently outperformed calipers with regards to variability, in which the probability of incorrectly determining treatment efficacy ranged from 0.0% to 2.6% for 3D imaging compared with 0.7% to 18.5% for calipers.

Users who had larger standard deviations in measurements were more likely to produce incorrect results, with both higher rates of false positives and false negatives.

These findings should be confirmed in real-world studies.

The study authors concluded a 3D imaging technique and users with lower standard deviations had the potential to decrease risk for coming to erroneous conclusions in rodent-based cancer studies.

Disclosure: Some authors declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of disclosures.

Reference

Murkin JT, Amos HE, Brough DW, Turley KD. In silico modeling demonstrates that user variability during tumor measurement can affect in vivo therapeutic efficacy outcomes. Cancer Inform. Published online November 29, 2022. doi:10.1177/11769351221139257