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020 _a9783031608438
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024 7 _a10.1007/978-3-031-60843-8
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072 7 _aMED090000
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100 1 _aYe, Jingjing.
_eauthor.
_0(orcid)ZORCID;HTTP://ORCID.ORG/0000-0003-0086-2228
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_987873
245 1 0 _aInnovative Designs and Analyses for Small Population Clinical Trials
_h[electronic resource] :
_bDevelopment Strategies and Operational Engagement for Pediatric and Rare Diseases /
_cby Jingjing Ye, Lei Nie.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXIX, 473 p. 50 illus., 48 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aICSA Book Series in Statistics,
_x2199-0999
505 0 _a1. Introduction -- 2. The Case Study of NCI-COG Pediatric Match Trials -- 3. The Case Study of Non-oncology (Lonafarnib) -- 4. Natural History and Patient Registry -- 5. Diagnostic Criteria and Endpoints -- 6. Enrichment Designs -- 7. Pediatric Extrapolation -- 8. Cross-over Designs -- 9. Adaptive Designs -- 10. Master Protocols -- 11. Other Designs -- 12. Modeling and Simulations -- 13. Frequentist Approaches -- 14. Bayesian Approaches -- 15. Operation and Other Considerations -- 16. Case Studies.
520 _aThis book discusses a multidisciplinary and multi-stakeholder collaborative approach to small population clinical trials. It provides and illustrates a systematic framework that depends upon a collaborative infrastructure between the patient community, patient advocacy groups, researchers and investigators, pharmaceutical companies, global regulatory agencies, and customers. The book also highlights the considerations of natural history and patient registry, diagnostic criteria determination, identification of clinically meaningful endpoints, and global regulatory guidance. The authors detail the nuances of clinical trial design as specific to small population disease, drawing from real examples.
650 0 _aBiometry.
_965981
650 0 _aClinical medicine
_xResearch.
_974123
650 0 _aStatistics .
_965982
650 0 _aArtificial intelligence
_xData processing.
650 0 _aMachine learning.
_955059
650 1 4 _aBiostatistics.
_965985
650 2 4 _aClinical Research.
_974124
650 2 4 _aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
_966911
650 2 4 _aApplied Statistics.
_965986
650 2 4 _aData Science.
650 2 4 _aMachine Learning.
_955059
700 1 _aNie, Lei.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987874
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031608421
776 0 8 _iPrinted edition:
_z9783031608445
776 0 8 _iPrinted edition:
_z9783031608452
830 0 _aICSA Book Series in Statistics,
_x2199-0999
_980221
856 4 0 _uhttps://doi.org/10.1007/978-3-031-60843-8
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912 _aZDB-2-SXMS
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