A proof-of-concept-to-confirmatory multiple adaptation design in the development of an anti-viral treatment
In the clinical development of some new infectious disease drugs, early clinical pharmacology trials may predict with high confidence that the efficacious doses are well below the range of the safety margin. In this case, a dose-ranging study may be unnecessary after a proof-of-concept (PoC) study t...
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| Veröffentlicht in: | Statistical methods in medical research 2019-12, Vol.28 (12), p.3491-3501 |
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| creator | Fan, Xiaoyin F Gallo, Paul Su, Guoqin Menton, Ronald Segal, Florencia |
| description | In the clinical development of some new infectious disease drugs, early clinical pharmacology trials may predict with high confidence that the efficacious doses are well below the range of the safety margin. In this case, a dose-ranging study may be unnecessary after a proof-of-concept (PoC) study testing the highest dose. A multi-stage adaptive design spanning both PoC and confirmatory stages is proposed in this context. The design incorporates two interim analyses allowing strategies for stopping, continuing, or expanding the study. A conditional power threshold for a binary endpoint is proposed to assess futility. Additional components of early efficacy and sample size adjustment are also included to enhance the design's flexibility and robustness. Design operating characteristics are evaluated by numerical calculation. We show that the proposed streamlined trial design has the same statistical rigor as a conventional phase 3 clinical trial with adequate power and a properly controlled type 1 error rate. Additional adaptive design options are also investigated and discussed. |
| doi_str_mv | 10.1177/0962280218807950 |
| format | Article |
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Additional adaptive design options are also investigated and discussed.</description><subject>Adaptive designs</subject><subject>Algorithms</subject><subject>Antiviral Agents - therapeutic use</subject><subject>Clinical research</subject><subject>Clinical trials</subject><subject>Confidence</subject><subject>Dosage</subject><subject>Drug Development - organization & administration</subject><subject>Efficacy</subject><subject>Endpoint Determination - statistics & numerical data</subject><subject>Flexibility</subject><subject>Futility</subject><subject>Humans</subject><subject>Infectious diseases</subject><subject>Pharmacology</subject><subject>Power</subject><subject>Research Design - statistics & numerical data</subject><subject>Robustness</subject><subject>Robustness (mathematics)</subject><subject>Safety margins</subject><subject>Sample Size</subject><issn>0962-2802</issn><issn>1477-0334</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><recordid>eNp1kU1r3DAQhkVoSLab3Hsqgl5yUTP6sGQfQ0jSQqCXvZuxLSdKbcuV5IX995XZpIFAYUAS7zOv5oOQLxy-c27MNVRaiBIEL0swVQEnZMOVMQykVJ_IZpXZqp-TzzG-AIABVZ2RcwnSFFnYkN83dA7e9yxH66fWzoklv157F0ZMPhzouAzJzYOl2OGcMDk_0c5G9zRRN9H0bPNrbwc_j3ZK1PcUpxzJsb0LONAULKZVuiCnPQ7RXr6eW7K7v9vd_mCPvx5-3t48slbyMjFdFIVWrW4ApRSy6zqhGsOLRlmUyihV8grBcK2x71rdNY3WAEJhZRqBrdySq6NtbuzPYmOqRxdbOww4Wb_EWnBheGWEVBn99gF98UuYcnF1nmulKq2UyBQcqTb4GIPt6zm4EcOh5lCve6g_7iGnfH01XprRdv8S3gafAXYEIj7Z91__a_gXwFmPjA</recordid><startdate>201912</startdate><enddate>201912</enddate><creator>Fan, Xiaoyin F</creator><creator>Gallo, Paul</creator><creator>Su, Guoqin</creator><creator>Menton, Ronald</creator><creator>Segal, Florencia</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QJ</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>K9.</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-0557-3903</orcidid></search><sort><creationdate>201912</creationdate><title>A proof-of-concept-to-confirmatory multiple adaptation design in the development of an anti-viral treatment</title><author>Fan, Xiaoyin F ; Gallo, Paul ; Su, Guoqin ; Menton, Ronald ; Segal, Florencia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c318t-655564c6b0a3323ddd24b715b4ea34744819a07166afdc6dbb660024a97b2ac3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adaptive designs</topic><topic>Algorithms</topic><topic>Antiviral Agents - therapeutic use</topic><topic>Clinical research</topic><topic>Clinical trials</topic><topic>Confidence</topic><topic>Dosage</topic><topic>Drug Development - organization & administration</topic><topic>Efficacy</topic><topic>Endpoint Determination - statistics & numerical data</topic><topic>Flexibility</topic><topic>Futility</topic><topic>Humans</topic><topic>Infectious diseases</topic><topic>Pharmacology</topic><topic>Power</topic><topic>Research Design - statistics & numerical data</topic><topic>Robustness</topic><topic>Robustness (mathematics)</topic><topic>Safety margins</topic><topic>Sample Size</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fan, Xiaoyin F</creatorcontrib><creatorcontrib>Gallo, Paul</creatorcontrib><creatorcontrib>Su, Guoqin</creatorcontrib><creatorcontrib>Menton, Ronald</creatorcontrib><creatorcontrib>Segal, Florencia</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>Statistical methods in medical research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fan, Xiaoyin F</au><au>Gallo, Paul</au><au>Su, Guoqin</au><au>Menton, Ronald</au><au>Segal, Florencia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A proof-of-concept-to-confirmatory multiple adaptation design in the development of an anti-viral treatment</atitle><jtitle>Statistical methods in medical research</jtitle><addtitle>Stat Methods Med Res</addtitle><date>2019-12</date><risdate>2019</risdate><volume>28</volume><issue>12</issue><spage>3491</spage><epage>3501</epage><pages>3491-3501</pages><issn>0962-2802</issn><eissn>1477-0334</eissn><abstract>In the clinical development of some new infectious disease drugs, early clinical pharmacology trials may predict with high confidence that the efficacious doses are well below the range of the safety margin. 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| subjects | Adaptive designs Algorithms Antiviral Agents - therapeutic use Clinical research Clinical trials Confidence Dosage Drug Development - organization & administration Efficacy Endpoint Determination - statistics & numerical data Flexibility Futility Humans Infectious diseases Pharmacology Power Research Design - statistics & numerical data Robustness Robustness (mathematics) Safety margins Sample Size |
| title | A proof-of-concept-to-confirmatory multiple adaptation design in the development of an anti-viral treatment |
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