A Meta-analysis to Assess the FDA DAVP's TLOVR Algorithm in HIV Submissions
The first meta-analysis of pivotal HIV study results utilizing data from 18 clinical trials involving seven NDAs with 8,046 patients of multiple NDA submissions for the treatment of HIV infection was used to determine if we can use a simplified version of the TLOVR algorithm for accelerated approval...
Gespeichert in:
| Veröffentlicht in: | Drug information journal 2011-05, Vol.45 (3), p.291-300 |
|---|---|
| Hauptverfasser: | , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 300 |
|---|---|
| container_issue | 3 |
| container_start_page | 291 |
| container_title | Drug information journal |
| container_volume | 45 |
| creator | Smith, Fraser Hammerstrom, Thomas Soon, Greg Zhou, Susan Chen, Baibai Mai, Yabing Struble, Kimberly Huque, Mohammad |
| description | The first meta-analysis of pivotal HIV study results utilizing data from 18 clinical trials involving seven NDAs with 8,046 patients of multiple NDA submissions for the treatment of HIV infection was used to determine if we can use a simplified version of the TLOVR algorithm for accelerated approval at week 24 and possibly for traditional approval at week 48. Standardized data sets for HIV RNA viral load, demography, CD4 counts, and discontinuation were created. These raw data sets used CDISC study data tabulation model naming conventions for most of the variables. Results obtained using the TLOVR algorithm, which utilized data from every visit to consider the pattern of HIV responses, were compared to a less complicated snapshot approach that only utilized HIV RNA data at the visit of interest. Given the similarity in results between the TLOVR and snapshot approaches, it appears that correcting for intermittent spikes in HIV RNA levels with the TLOVR algorithm does not have much regulatory impact. |
| doi_str_mv | 10.1177/009286151104500309 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_905947195</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_009286151104500309</sage_id><sourcerecordid>2550668312</sourcerecordid><originalsourceid>FETCH-LOGICAL-c386t-567eb3f0f3006dfc0acc3dc61dfde9ca02e9232cfe2cdae053fc6e3db65875c33</originalsourceid><addsrcrecordid>eNqNkMFOAjEQhjdGE4nyAp4aPXhambbbbnvcgAgRg1HkuindFpYAi53lwNu7BowHo3EuM4fv-5P5o-iKwh2ladoB0ExJKiiFRABw0CdRi1Gp4kRBcvp1pxrOozbiEprRSqRMtaLHjDy52sRmY1Z7LJHUFckQHTbXwpF-LyO9bPp8i2QyGk9fSLaaV6GsF2tSbshgOCWvu9m6RCyrDV5GZ96s0LWP-yJ6699PuoN4NH4YdrNRbLmSdSxk6mbcg-cAsvAWjLW8sJIWvnDaGmBOM86sd8wWxoHg3krHi5kUKhWW84vo-pC7DdX7zmGdL6tdaB7AXIPQSUq1aKCb3yAmBEipOGUNxQ6UDRVicD7fhnJtwj6nkH-Wm_8st5H4QcIG3sxd-I7-0-ocLTN3_zI-AASYhbY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>905947195</pqid></control><display><type>article</type><title>A Meta-analysis to Assess the FDA DAVP's TLOVR Algorithm in HIV Submissions</title><source>Access via SAGE</source><source>SpringerNature Journals</source><creator>Smith, Fraser ; Hammerstrom, Thomas ; Soon, Greg ; Zhou, Susan ; Chen, Baibai ; Mai, Yabing ; Struble, Kimberly ; Huque, Mohammad</creator><creatorcontrib>Smith, Fraser ; Hammerstrom, Thomas ; Soon, Greg ; Zhou, Susan ; Chen, Baibai ; Mai, Yabing ; Struble, Kimberly ; Huque, Mohammad</creatorcontrib><description>The first meta-analysis of pivotal HIV study results utilizing data from 18 clinical trials involving seven NDAs with 8,046 patients of multiple NDA submissions for the treatment of HIV infection was used to determine if we can use a simplified version of the TLOVR algorithm for accelerated approval at week 24 and possibly for traditional approval at week 48. Standardized data sets for HIV RNA viral load, demography, CD4 counts, and discontinuation were created. These raw data sets used CDISC study data tabulation model naming conventions for most of the variables. Results obtained using the TLOVR algorithm, which utilized data from every visit to consider the pattern of HIV responses, were compared to a less complicated snapshot approach that only utilized HIV RNA data at the visit of interest. Given the similarity in results between the TLOVR and snapshot approaches, it appears that correcting for intermittent spikes in HIV RNA levels with the TLOVR algorithm does not have much regulatory impact.</description><identifier>ISSN: 2168-4790</identifier><identifier>ISSN: 0092-8615</identifier><identifier>EISSN: 2168-4804</identifier><identifier>EISSN: 2164-9200</identifier><identifier>DOI: 10.1177/009286151104500309</identifier><identifier>CODEN: DGIJB9</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Algorithms ; CD4 antigen ; Clinical trials ; Datasets ; Demography ; Drug Safety and Pharmacovigilance ; Drug therapy ; HIV ; Human immunodeficiency virus ; Meta-analysis ; Pharmacotherapy ; Pharmacy ; Ribonucleic acid ; RNA ; Sensitivity analysis ; Statistical methods ; Statistics ; Studies ; Tabulation</subject><ispartof>Drug information journal, 2011-05, Vol.45 (3), p.291-300</ispartof><rights>2011 Drug Information Association</rights><rights>Drug Information Association, Inc 2011</rights><rights>Drug Information Association, Inc 2011.</rights><rights>Copyright Drug Information Association May 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c386t-567eb3f0f3006dfc0acc3dc61dfde9ca02e9232cfe2cdae053fc6e3db65875c33</citedby><cites>FETCH-LOGICAL-c386t-567eb3f0f3006dfc0acc3dc61dfde9ca02e9232cfe2cdae053fc6e3db65875c33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/009286151104500309$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/009286151104500309$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,780,784,21819,27924,27925,43621,43622</link.rule.ids></links><search><creatorcontrib>Smith, Fraser</creatorcontrib><creatorcontrib>Hammerstrom, Thomas</creatorcontrib><creatorcontrib>Soon, Greg</creatorcontrib><creatorcontrib>Zhou, Susan</creatorcontrib><creatorcontrib>Chen, Baibai</creatorcontrib><creatorcontrib>Mai, Yabing</creatorcontrib><creatorcontrib>Struble, Kimberly</creatorcontrib><creatorcontrib>Huque, Mohammad</creatorcontrib><title>A Meta-analysis to Assess the FDA DAVP's TLOVR Algorithm in HIV Submissions</title><title>Drug information journal</title><addtitle>Ther Innov Regul Sci</addtitle><description>The first meta-analysis of pivotal HIV study results utilizing data from 18 clinical trials involving seven NDAs with 8,046 patients of multiple NDA submissions for the treatment of HIV infection was used to determine if we can use a simplified version of the TLOVR algorithm for accelerated approval at week 24 and possibly for traditional approval at week 48. Standardized data sets for HIV RNA viral load, demography, CD4 counts, and discontinuation were created. These raw data sets used CDISC study data tabulation model naming conventions for most of the variables. Results obtained using the TLOVR algorithm, which utilized data from every visit to consider the pattern of HIV responses, were compared to a less complicated snapshot approach that only utilized HIV RNA data at the visit of interest. Given the similarity in results between the TLOVR and snapshot approaches, it appears that correcting for intermittent spikes in HIV RNA levels with the TLOVR algorithm does not have much regulatory impact.</description><subject>Algorithms</subject><subject>CD4 antigen</subject><subject>Clinical trials</subject><subject>Datasets</subject><subject>Demography</subject><subject>Drug Safety and Pharmacovigilance</subject><subject>Drug therapy</subject><subject>HIV</subject><subject>Human immunodeficiency virus</subject><subject>Meta-analysis</subject><subject>Pharmacotherapy</subject><subject>Pharmacy</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>Sensitivity analysis</subject><subject>Statistical methods</subject><subject>Statistics</subject><subject>Studies</subject><subject>Tabulation</subject><issn>2168-4790</issn><issn>0092-8615</issn><issn>2168-4804</issn><issn>2164-9200</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqNkMFOAjEQhjdGE4nyAp4aPXhambbbbnvcgAgRg1HkuindFpYAi53lwNu7BowHo3EuM4fv-5P5o-iKwh2ladoB0ExJKiiFRABw0CdRi1Gp4kRBcvp1pxrOozbiEprRSqRMtaLHjDy52sRmY1Z7LJHUFckQHTbXwpF-LyO9bPp8i2QyGk9fSLaaV6GsF2tSbshgOCWvu9m6RCyrDV5GZ96s0LWP-yJ6699PuoN4NH4YdrNRbLmSdSxk6mbcg-cAsvAWjLW8sJIWvnDaGmBOM86sd8wWxoHg3krHi5kUKhWW84vo-pC7DdX7zmGdL6tdaB7AXIPQSUq1aKCb3yAmBEipOGUNxQ6UDRVicD7fhnJtwj6nkH-Wm_8st5H4QcIG3sxd-I7-0-ocLTN3_zI-AASYhbY</recordid><startdate>20110501</startdate><enddate>20110501</enddate><creator>Smith, Fraser</creator><creator>Hammerstrom, Thomas</creator><creator>Soon, Greg</creator><creator>Zhou, Susan</creator><creator>Chen, Baibai</creator><creator>Mai, Yabing</creator><creator>Struble, Kimberly</creator><creator>Huque, Mohammad</creator><general>SAGE Publications</general><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7U7</scope><scope>C1K</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88I</scope><scope>8AF</scope><scope>8AO</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M2O</scope><scope>M2P</scope><scope>M7P</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>S0X</scope></search><sort><creationdate>20110501</creationdate><title>A Meta-analysis to Assess the FDA DAVP's TLOVR Algorithm in HIV Submissions</title><author>Smith, Fraser ; Hammerstrom, Thomas ; Soon, Greg ; Zhou, Susan ; Chen, Baibai ; Mai, Yabing ; Struble, Kimberly ; Huque, Mohammad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c386t-567eb3f0f3006dfc0acc3dc61dfde9ca02e9232cfe2cdae053fc6e3db65875c33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>CD4 antigen</topic><topic>Clinical trials</topic><topic>Datasets</topic><topic>Demography</topic><topic>Drug Safety and Pharmacovigilance</topic><topic>Drug therapy</topic><topic>HIV</topic><topic>Human immunodeficiency virus</topic><topic>Meta-analysis</topic><topic>Pharmacotherapy</topic><topic>Pharmacy</topic><topic>Ribonucleic acid</topic><topic>RNA</topic><topic>Sensitivity analysis</topic><topic>Statistical methods</topic><topic>Statistics</topic><topic>Studies</topic><topic>Tabulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Smith, Fraser</creatorcontrib><creatorcontrib>Hammerstrom, Thomas</creatorcontrib><creatorcontrib>Soon, Greg</creatorcontrib><creatorcontrib>Zhou, Susan</creatorcontrib><creatorcontrib>Chen, Baibai</creatorcontrib><creatorcontrib>Mai, Yabing</creatorcontrib><creatorcontrib>Struble, Kimberly</creatorcontrib><creatorcontrib>Huque, Mohammad</creatorcontrib><collection>CrossRef</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>eLibrary</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><jtitle>Drug information journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Smith, Fraser</au><au>Hammerstrom, Thomas</au><au>Soon, Greg</au><au>Zhou, Susan</au><au>Chen, Baibai</au><au>Mai, Yabing</au><au>Struble, Kimberly</au><au>Huque, Mohammad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Meta-analysis to Assess the FDA DAVP's TLOVR Algorithm in HIV Submissions</atitle><jtitle>Drug information journal</jtitle><stitle>Ther Innov Regul Sci</stitle><date>2011-05-01</date><risdate>2011</risdate><volume>45</volume><issue>3</issue><spage>291</spage><epage>300</epage><pages>291-300</pages><issn>2168-4790</issn><issn>0092-8615</issn><eissn>2168-4804</eissn><eissn>2164-9200</eissn><coden>DGIJB9</coden><abstract>The first meta-analysis of pivotal HIV study results utilizing data from 18 clinical trials involving seven NDAs with 8,046 patients of multiple NDA submissions for the treatment of HIV infection was used to determine if we can use a simplified version of the TLOVR algorithm for accelerated approval at week 24 and possibly for traditional approval at week 48. Standardized data sets for HIV RNA viral load, demography, CD4 counts, and discontinuation were created. These raw data sets used CDISC study data tabulation model naming conventions for most of the variables. Results obtained using the TLOVR algorithm, which utilized data from every visit to consider the pattern of HIV responses, were compared to a less complicated snapshot approach that only utilized HIV RNA data at the visit of interest. Given the similarity in results between the TLOVR and snapshot approaches, it appears that correcting for intermittent spikes in HIV RNA levels with the TLOVR algorithm does not have much regulatory impact.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><doi>10.1177/009286151104500309</doi><tpages>10</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2168-4790 |
| ispartof | Drug information journal, 2011-05, Vol.45 (3), p.291-300 |
| issn | 2168-4790 0092-8615 2168-4804 2164-9200 |
| language | eng |
| recordid | cdi_proquest_journals_905947195 |
| source | Access via SAGE; SpringerNature Journals |
| subjects | Algorithms CD4 antigen Clinical trials Datasets Demography Drug Safety and Pharmacovigilance Drug therapy HIV Human immunodeficiency virus Meta-analysis Pharmacotherapy Pharmacy Ribonucleic acid RNA Sensitivity analysis Statistical methods Statistics Studies Tabulation |
| title | A Meta-analysis to Assess the FDA DAVP's TLOVR Algorithm in HIV Submissions |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T10%3A13%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Meta-analysis%20to%20Assess%20the%20FDA%20DAVP's%20TLOVR%20Algorithm%20in%20HIV%20Submissions&rft.jtitle=Drug%20information%20journal&rft.au=Smith,%20Fraser&rft.date=2011-05-01&rft.volume=45&rft.issue=3&rft.spage=291&rft.epage=300&rft.pages=291-300&rft.issn=2168-4790&rft.eissn=2168-4804&rft.coden=DGIJB9&rft_id=info:doi/10.1177/009286151104500309&rft_dat=%3Cproquest_cross%3E2550668312%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=905947195&rft_id=info:pmid/&rft_sage_id=10.1177_009286151104500309&rfr_iscdi=true |