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Göteborgs universitets publikationer

Optimized design and analysis of preclinical intervention studies in vivo

Författare och institution:
T. D. Laajala (-); M. Jumppanen (-); R. Huhtaniemi (-); V. Fey (-); A. Kaur (-); M. Knuuttila (-); E. Aho (-); R. Oksala (-); J. Westermarck (-); S. Makela (-); Matti Poutanen (Institutionen för medicin); T. Aittokallio (-)
Publicerad i:
Scientific Reports, 6 s. Article number: 30723
ISSN:
2045-2322
Publikationstyp:
Artikel, refereegranskad vetenskaplig
Publiceringsår:
2016
Språk:
engelska
Fulltextlänk:
Sammanfattning (abstract):
Recent reports have called into question the reproducibility, validity and translatability of the preclinical animal studies due to limitations in their experimental design and statistical analysis. To this end, we implemented a matching-based modelling approach for optimal intervention group allocation, randomization and power calculations, which takes full account of the complex animal characteristics at baseline prior to interventions. In prostate cancer xenograft studies, the method effectively normalized the confounding baseline variability, and resulted in animal allocations which were supported by RNA-seq profiling of the individual tumours. The matching information increased the statistical power to detect true treatment effects at smaller sample sizes in two castration-resistant prostate cancer models, thereby leading to saving of both animal lives and research costs. The novel modelling approach and its open-source and web-based software implementations enable the researchers to conduct adequately-powered and fully-blinded preclinical intervention studies, with the aim to accelerate the discovery of new therapeutic interventions.
Ämne (baseras på Högskoleverkets indelning av forskningsämnen):
MEDICIN OCH HÄLSOVETENSKAP ->
Klinisk medicin
Nyckelord:
dynamic allocation methods, distance functions, clinical-trials, randomization, similarity, mouse, mice
Postens nummer:
241177
Posten skapad:
2016-09-02 09:18
Posten ändrad:
2016-09-08 15:37

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