Indeterminate Data and Handling for Assessing Diagnostic Performance in Imaging Drug Developments
Volume 2, Issue 1 (2024), pp. 112–119
Pub. online: 22 August 2023
Type: Cancer Research
Open Access
Open Access
Accepted
13 April 2023
13 April 2023
Published
22 August 2023
22 August 2023
Abstract
In diagnostic imaging drug developments, the imaging scan read data in controlled imaging drug clinical trials includes test positive and test negative. Broadly speaking, the standard of reference data are either presence or absence of a disease or clinical condition. Together, these data are used to assess the diagnostic performance of an investigational imaging drug in a controlled imaging drug clinical trial. For those imaging scan read data that cannot be called positive/negative, the “indeterminate” category is commonly used to cover imaging results that may be considered intermediate, indeterminate, or uninterpretable. Similarly, for those standard of reference data that cannot be categorized into presence/absence including uncollected or unavailable reference standard data, the “indeterminate” category may be used. Historically, little attention has been paid to the indeterminate imaging scan read data as they are generally rare or considered irrelevant though they are related to scanned subjects and can be informative. Subjects lack the standard of reference are simply excluded as such the study only reports the analysis results in subjects with available standard of reference data, known as completer analysis, similar to evaluable subjects seen in controlled trials for drug developments.
To improve diagnostic clinical trial planning, this paper introduces five attributes of an estimand in diagnostic imaging drug clinical trials. The paper then defines the indeterminate data mechanisms and gives examples for each indeterminate mechanism that is specific to the clinical context of a diagnostic imaging drug clinical trial. Several imputation approaches to handling indeterminate data are discussed. Depending on the clinical question of primary interests, indeterminate data may be intercurrent events. The paper ends with discussions on imputations of intercurrent events occurring in indeterminate imaging scan read data and those occurring in indeterminate standard of reference data when encountered in diagnostic imaging clinical trials and provides points to consider of estimands for diagnostic imaging drug developments.
References
ICH E9 (R1) addendum. Estimands and sensitivity analysis in clinical trials to the guideline on statistical principles for clinical trials (2020). https://www.ema.europa.eu/en/documents/scientific-guideline/ich-e9-r1-addendum-estimands-sensitivity-analysis-clinical-trials-guideline-statistical-principles_en.pdf
Wharton, S., Astrup, A., Endahl, L., Lean, M. E. J., Satylganova, A., Skogaard, D., Wadden, T. A. and Wilding, J. P. H. (2021). Estimating and reporting treatment effects in clinical trials for weight management: using estimands to interpret effects of intercurrent events and missing data. International Journal of Obesity 45(5) 923–933.
Zhou, X. H., Obuchowski, N. A. and McClish, D. K. (2002). Statistical methods in diagnostic medicine. John Wiley and Sons, New York. https://doi.org/10.1002/9780470317082. MR1915698
Pepe, M. S. (2003). The statistical evaluation of medical tests for classification and prediction. Oxford University Press, New York. MR2260483
Ich E9 statistical principles for clinical trials (1998). https://www.ema.europa.eu/en/documents/scientific-guideline/ich-e-9-statistical-principles-clinical-trials-step-5_en.pdf.
Repici, A., Wallace, M. B., East, J. E., Sharma, P., Ramirez, F. C., Bruining, D. H., Young, M., Gatof, D., Canto, M. I. M., Marcon, N., Cannizzoro, R., Kiesslich, R., Rutter, M., Dekker, E., Siersema, P. D., Spaander, M., Kupcinskas, L., Jonaitis, L., Bisschops, R., Radaelli, F., Bhandari, P., Wilson, A., Early, D., Gupta, N., Vieth, M., Lauwers, G. Y., Rossini, M. and Hassan, C. (2019). Efficacy of per-oral methylene blue formulation for screening colonoscopy. Gastroenterology 156(8) 2198–2207.e1.
Gadavist (gadobutrol) injection, for intravenous use. Highlights of prescribing information. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/201277s018lbl.pdf. Accessed on November 17, 2021.
The NDA multi-disciplinary review and evaluation: NDA 212643, Gallium Ga 68 PSMA-11 injection. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2020/212643Orig1s000MultidisciplineR.pdf. Accessed on November 17, 2021.
Wang, S. J. 2023. Diagnostic test evaluation book chapter in “Translational Radiation Oncology: Handbook for Designing and Conducting Clinical and Translational Research” Editors: Adam EM Eltorai, Jeff Bakal, David E Wazer, Daniel Wonsoon Kim Elsevier Publisher. (Under gallery proof to be published in 2023). MR2828487
Vaneckova, M., Herman, M., Smith, M. P., Mechl, M., Maravilla, K. R., Weichet, J., Spampinato, M. V., ika, J., Wippold, F. J. II, Baima, J. J., Babbel, R., Bultmann, E., Huang, R. Y., Buhk, J. H., Bonafe, A., Colosimo, B. C., Liu, S., Kirchin, M. A., Shen, N., Pirovano, G. and Spinazzi, A. (2015). The benefits of high relaxivity for brain tumor imaging: results of a multicenter intraindividual crossover comparison of gadobenate dimeglumine with gadoterate meglumine (The BENEFIT study). American Journal of Neuroradiology 36(9) 1589–1598.
Little, R. J. A. and Rubin, D. B. (2019). Statistical analysis with missing data. 3rd ed. Wiley Series in Probability and Statistics. John Wiley and Sons, New York, NY. https://doi.org/10.1002/9781119013563. MR1925014
Van Buuren, S. and Groothuis-Oudshoorn, K. (2011). Multivariate imputation by chained equations in R. Journal of Statistical Software 45(3) 1–67. https://www.jstatsoft.org/v45/i03/.
National comprehensive cancer network (NCCN) clinical practice guidelines in oncology. https://www.nccn.org/guidelines/category_1. Accessed on January 15, 2022.
Little, R. J., D’Agostino, R., Cohen, M. L., Dickersin, K., Emerson, S. S., Farrar, J. T., Frangakis, C., Hogan, J. W., Molenberghs, G., Murphy, S. A., Neaton, J. D., Rotnitzky, A., Scharfstein, D., Shih, W. J., Siegel, J. P. and Stern, H. (2012). The prevention and treatment of missing data in clinical trials. New England Journal of Medicine 367(14) 1355–1360.
Lymphoseek (technetium Tc 99m tilmanocept) injection, for subcutaneous, intradermal, subareolar, or peritumoral use. Highlights of prescribing information. https://www.accessdata.fda.gov/drugsatfda_docs/label/2021/202207s012lbl.pdf. Accessed on November 17, 2021.
Wang, S. J. (2020). Recent advances in clinical trial design considerations in Thera “nostics”. Contemporary Clinical Trials 96 106100. https://doi.org/10.1016/j.cct.2020.106100.
Wang, S. J., Fotenos, A., Masters, S. C. and Marzella, L. (2022). Theranostics approach in drug development: is there study efficiency when the prevalence of the molecular target is very high? Theranostics 12(7) 3079–3083. https://www.thno.org/v12p3079.htm. https://doi.org/10.7150/thno.71788.
Pylarify (piflufolastat F18) injection, for intravenous use. Highlights of prescribing information. https://www.accessdata.fda.gov/drugsatfda_docs/label/2021/214793s000lbl.pdf. Accessed on November 17, 2021.
