Refining humane endpoint detection by time-series forecasting and threshold definition using a multivariate severity score
Frontiers in Physiology, vol. 17, pp. 1869563
Abstract
Severity assessment in animal-based research is not only mandatory but also requires the identification of robust, objective, and model-specific parameters. The RELative Severity Assessment (RELSA) procedure enabled multivariate severity assessment, allowing interpretation of outcomes in the context of a predefined severity grading. This study expands the application of the RELSA score by combining it with an Autoregressive Integrated Moving Average (ARIMA)-based prediction model, which we call foRcast. To facilitate interpretation of severity, a kernel density estimate (KDE) was applied to define exploratory thresholds on the RELSA scale. Data of mice reaching humane endpoints across models representing a broad range of severity profiles were reanalyzed using transmitter-derived parameters (e.g., heart rate) and behavioral parameters (e.g., voluntary wheel running), depending on the model. The primary focus was predicting RELSA scores at the humane endpoint using foRcast. With an overall root mean square error of 0.069 and 96% of actual RELSA scores falling within the 95% prediction interval of the forecasts, this tool showed promising preliminary performance. KDE was performed on sepsis data, yielding candidate thresholds at RELSA = 0.337 and RELSA = 0.647, which could be used to define severity zones for classifying the animals' burden, although these should not be confused with regulatory severity gradings. This proof-of-concept study showed the potential of the foRcast tool to accurately predict RELSA scores across various animal models and interventions, demonstrating the possibility to identify individual animals at risk of reaching the humane endpoint. The data also emphasize the intrinsic limitation of ARIMA models: drastic changes in the course cannot be reliably predicted. This underscores the need for higher-resolution measurements to detect early changes in animal well-being. Overall, the definition of candidate severity thresholds on the RELSA scale and the foRcast model represent valuable additions to the range of severity tools for refining severity assessment in animal-based research.
Authors 11
-
Sara Lutscher corresponding
Medizinische Hochschule Hannover
Affiliation as printed
Institute for Laboratory Animal Science, Hannover Medical School
-
Medizinische Hochschule Hannover
Affiliation as printed
Institute for Laboratory Animal Science, Hannover Medical School
-
Medizinische Hochschule Hannover
Affiliation as printed
Institute for Laboratory Animal Science, Hannover Medical School
-
Ludwig-Maximilians-Universität München
Affiliation as printed
Institute of Pharmacology, Toxicology, and Pharmacy, Ludwig-Maximilians-Universität München
-
Medizinische Hochschule Hannover
Affiliation as printed
Institute for Laboratory Animal Science, Hannover Medical School
-
Medizinische Hochschule Hannover
Affiliation as printed
Institute for Laboratory Animal Science, Hannover Medical School
-
Affiliation as printed
Rudolf-Zenker-Institute for Experimental Surgery, Rostock University Medical Center
-
Ludwig-Maximilians-Universität München
Affiliation as printed
Institute of Pharmacology, Toxicology, and Pharmacy, Ludwig-Maximilians-Universität München
-
Affiliation as printed
Department of Anesthesiology, Intensive Care Medicine and Pain and Therapy, University Hospital Frankfurt
-
Medizinische Hochschule Hannover
Affiliation as printed
Institute for Laboratory Animal Science, Hannover Medical School
-
Medizinische Hochschule Hannover · Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
Institute for Laboratory Animal Science, Hannover Medical School
Institute of Medical Statistics, RWTH Aachen University Hospital
Cited by 0 stored of 0
No patents citing this paper on Lens.org (checked 2026-10-06).