Meta-analysis of randomized clinical trials in the era of individual patient data sharing
Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kawahara, Takuya [verfasserIn] Fukuda, Musashi [verfasserIn] Oba, Koji [verfasserIn] Sakamoto, Junichi [verfasserIn] Buyse, Marc [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: International journal of clinical oncology - Tokyo : Springer, 1996, 23(2018), 3 vom: 12. Jan., Seite 403-409 |
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| Übergeordnetes Werk: |
volume:23 ; year:2018 ; number:3 ; day:12 ; month:01 ; pages:403-409 |
| Links: |
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| DOI / URN: |
10.1007/s10147-018-1237-z |
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| Katalog-ID: |
SPR008913552 |
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| 520 | |a Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. | ||
| 650 | 4 | |a Data sharing |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Individual patient data |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Meta-analysis |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Fukuda, Musashi |e verfasserin |4 aut | |
| 700 | 1 | |a Oba, Koji |e verfasserin |4 aut | |
| 700 | 1 | |a Sakamoto, Junichi |e verfasserin |4 aut | |
| 700 | 1 | |a Buyse, Marc |e verfasserin |4 aut | |
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10.1007/s10147-018-1237-z doi (DE-627)SPR008913552 (SPR)s10147-018-1237-z-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE 44.81 bkl Kawahara, Takuya verfasserin aut Meta-analysis of randomized clinical trials in the era of individual patient data sharing 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. Data sharing (dpeaa)DE-He213 Individual patient data (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Fukuda, Musashi verfasserin aut Oba, Koji verfasserin aut Sakamoto, Junichi verfasserin aut Buyse, Marc verfasserin aut Enthalten in International journal of clinical oncology Tokyo : Springer, 1996 23(2018), 3 vom: 12. Jan., Seite 403-409 (DE-627)300187033 (DE-600)1481773-1 1437-7772 nnns volume:23 year:2018 number:3 day:12 month:01 pages:403-409 https://dx.doi.org/10.1007/s10147-018-1237-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE AR 23 2018 3 12 01 403-409 |
| spelling |
10.1007/s10147-018-1237-z doi (DE-627)SPR008913552 (SPR)s10147-018-1237-z-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE 44.81 bkl Kawahara, Takuya verfasserin aut Meta-analysis of randomized clinical trials in the era of individual patient data sharing 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. Data sharing (dpeaa)DE-He213 Individual patient data (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Fukuda, Musashi verfasserin aut Oba, Koji verfasserin aut Sakamoto, Junichi verfasserin aut Buyse, Marc verfasserin aut Enthalten in International journal of clinical oncology Tokyo : Springer, 1996 23(2018), 3 vom: 12. Jan., Seite 403-409 (DE-627)300187033 (DE-600)1481773-1 1437-7772 nnns volume:23 year:2018 number:3 day:12 month:01 pages:403-409 https://dx.doi.org/10.1007/s10147-018-1237-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE AR 23 2018 3 12 01 403-409 |
| allfields_unstemmed |
10.1007/s10147-018-1237-z doi (DE-627)SPR008913552 (SPR)s10147-018-1237-z-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE 44.81 bkl Kawahara, Takuya verfasserin aut Meta-analysis of randomized clinical trials in the era of individual patient data sharing 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. Data sharing (dpeaa)DE-He213 Individual patient data (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Fukuda, Musashi verfasserin aut Oba, Koji verfasserin aut Sakamoto, Junichi verfasserin aut Buyse, Marc verfasserin aut Enthalten in International journal of clinical oncology Tokyo : Springer, 1996 23(2018), 3 vom: 12. Jan., Seite 403-409 (DE-627)300187033 (DE-600)1481773-1 1437-7772 nnns volume:23 year:2018 number:3 day:12 month:01 pages:403-409 https://dx.doi.org/10.1007/s10147-018-1237-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE AR 23 2018 3 12 01 403-409 |
| allfieldsGer |
10.1007/s10147-018-1237-z doi (DE-627)SPR008913552 (SPR)s10147-018-1237-z-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE 44.81 bkl Kawahara, Takuya verfasserin aut Meta-analysis of randomized clinical trials in the era of individual patient data sharing 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. Data sharing (dpeaa)DE-He213 Individual patient data (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Fukuda, Musashi verfasserin aut Oba, Koji verfasserin aut Sakamoto, Junichi verfasserin aut Buyse, Marc verfasserin aut Enthalten in International journal of clinical oncology Tokyo : Springer, 1996 23(2018), 3 vom: 12. Jan., Seite 403-409 (DE-627)300187033 (DE-600)1481773-1 1437-7772 nnns volume:23 year:2018 number:3 day:12 month:01 pages:403-409 https://dx.doi.org/10.1007/s10147-018-1237-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE AR 23 2018 3 12 01 403-409 |
| allfieldsSound |
10.1007/s10147-018-1237-z doi (DE-627)SPR008913552 (SPR)s10147-018-1237-z-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE 44.81 bkl Kawahara, Takuya verfasserin aut Meta-analysis of randomized clinical trials in the era of individual patient data sharing 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. Data sharing (dpeaa)DE-He213 Individual patient data (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Fukuda, Musashi verfasserin aut Oba, Koji verfasserin aut Sakamoto, Junichi verfasserin aut Buyse, Marc verfasserin aut Enthalten in International journal of clinical oncology Tokyo : Springer, 1996 23(2018), 3 vom: 12. Jan., Seite 403-409 (DE-627)300187033 (DE-600)1481773-1 1437-7772 nnns volume:23 year:2018 number:3 day:12 month:01 pages:403-409 https://dx.doi.org/10.1007/s10147-018-1237-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE AR 23 2018 3 12 01 403-409 |
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English |
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Enthalten in International journal of clinical oncology 23(2018), 3 vom: 12. Jan., Seite 403-409 volume:23 year:2018 number:3 day:12 month:01 pages:403-409 |
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Enthalten in International journal of clinical oncology 23(2018), 3 vom: 12. Jan., Seite 403-409 volume:23 year:2018 number:3 day:12 month:01 pages:403-409 |
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Data sharing Individual patient data Meta-analysis |
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International journal of clinical oncology |
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Kawahara, Takuya @@aut@@ Fukuda, Musashi @@aut@@ Oba, Koji @@aut@@ Sakamoto, Junichi @@aut@@ Buyse, Marc @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR008913552</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230519224538.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10147-018-1237-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR008913552</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10147-018-1237-z-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.81</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kawahara, Takuya</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Meta-analysis of randomized clinical trials in the era of individual patient data sharing</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. 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Kawahara, Takuya |
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Kawahara, Takuya ddc 610 bkl 44.81 misc Data sharing misc Individual patient data misc Meta-analysis Meta-analysis of randomized clinical trials in the era of individual patient data sharing |
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610 ASE 44.81 bkl Meta-analysis of randomized clinical trials in the era of individual patient data sharing Data sharing (dpeaa)DE-He213 Individual patient data (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 |
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Meta-analysis of randomized clinical trials in the era of individual patient data sharing |
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Kawahara, Takuya |
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International journal of clinical oncology |
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Kawahara, Takuya Fukuda, Musashi Oba, Koji Sakamoto, Junichi Buyse, Marc |
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meta-analysis of randomized clinical trials in the era of individual patient data sharing |
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Meta-analysis of randomized clinical trials in the era of individual patient data sharing |
| abstract |
Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. |
| abstractGer |
Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. |
| abstract_unstemmed |
Background Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. Methods First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Results Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Conclusions Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future. |
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| title_short |
Meta-analysis of randomized clinical trials in the era of individual patient data sharing |
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https://dx.doi.org/10.1007/s10147-018-1237-z |
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| author2 |
Fukuda, Musashi Oba, Koji Sakamoto, Junichi Buyse, Marc |
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Fukuda, Musashi Oba, Koji Sakamoto, Junichi Buyse, Marc |
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| doi_str |
10.1007/s10147-018-1237-z |
| up_date |
2024-07-03T23:50:25.194Z |
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| score |
7.398608 |