The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform
Masahiro Takeuchi - One of the best experts on this subject based on the ideXlab platform.
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a flexible and coherent Test estimation procedure based on restricted mean survival times for censored time to event data in randomized clinical trials
Statistics in Medicine, 2018Co-Authors: Miki Horiguchi, Angel M Cronin, Masahiro TakeuchiAbstract:: In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the Logrank Test is prespecified as the primary Test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the Logrank Test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted Logrank Tests, eg, Peto-Prentice-Wilcoxon Test. Alternatively, one may specify a robust Test as the primary Test, which can capture various patterns of difference between 2 event time distributions. However, most of those Tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary Test. Such incoherence in the "Test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent Test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified Test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the Test is dramatically more powerful than the Logrank, Wilcoxon Tests, and the restricted mean survival time-based Test with a fixed τ, for the patterns of difference seen in these cancer clinical trials.
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A flexible and coherent Test/estimation procedure based on restricted mean survival times for censored time-to-event data in randomized clinical trials.
Statistics in medicine, 2018Co-Authors: Miki Horiguchi, Angel M Cronin, Masahiro Takeuchi, Hajime UnoAbstract:In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the Logrank Test is prespecified as the primary Test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the Logrank Test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted Logrank Tests, eg, Peto-Prentice-Wilcoxon Test. Alternatively, one may specify a robust Test as the primary Test, which can capture various patterns of difference between 2 event time distributions. However, most of those Tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary Test. Such incoherence in the "Test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent Test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified Test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the Test is dramatically more powerful than the Logrank, Wilcoxon Tests, and the restricted mean survival time-based Test with a fixed τ, for the patterns of difference seen in these cancer clinical trials.
Miki Horiguchi - One of the best experts on this subject based on the ideXlab platform.
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a flexible and coherent Test estimation procedure based on restricted mean survival times for censored time to event data in randomized clinical trials
Statistics in Medicine, 2018Co-Authors: Miki Horiguchi, Angel M Cronin, Masahiro TakeuchiAbstract:: In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the Logrank Test is prespecified as the primary Test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the Logrank Test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted Logrank Tests, eg, Peto-Prentice-Wilcoxon Test. Alternatively, one may specify a robust Test as the primary Test, which can capture various patterns of difference between 2 event time distributions. However, most of those Tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary Test. Such incoherence in the "Test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent Test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified Test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the Test is dramatically more powerful than the Logrank, Wilcoxon Tests, and the restricted mean survival time-based Test with a fixed τ, for the patterns of difference seen in these cancer clinical trials.
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A flexible and coherent Test/estimation procedure based on restricted mean survival times for censored time-to-event data in randomized clinical trials.
Statistics in medicine, 2018Co-Authors: Miki Horiguchi, Angel M Cronin, Masahiro Takeuchi, Hajime UnoAbstract:In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the Logrank Test is prespecified as the primary Test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the Logrank Test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted Logrank Tests, eg, Peto-Prentice-Wilcoxon Test. Alternatively, one may specify a robust Test as the primary Test, which can capture various patterns of difference between 2 event time distributions. However, most of those Tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary Test. Such incoherence in the "Test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent Test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified Test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the Test is dramatically more powerful than the Logrank, Wilcoxon Tests, and the restricted mean survival time-based Test with a fixed τ, for the patterns of difference seen in these cancer clinical trials.
Shyryu - One of the best experts on this subject based on the ideXlab platform.
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Sample size determination for paired right-censored data based on the difference of Kaplan-Meier estimates
Computational Statistics & Data Analysis, 2014Co-Authors: Supei-fang, Lichung-i, ShyryuAbstract:Sample size determination is essential to planning clinical trials. Jung (2008) established a sample size calculation formula for paired right-censored data based on the Logrank Test, which has bee...
Hajime Uno - One of the best experts on this subject based on the ideXlab platform.
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A flexible and coherent Test/estimation procedure based on restricted mean survival times for censored time-to-event data in randomized clinical trials.
Statistics in medicine, 2018Co-Authors: Miki Horiguchi, Angel M Cronin, Masahiro Takeuchi, Hajime UnoAbstract:In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the Logrank Test is prespecified as the primary Test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the Logrank Test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted Logrank Tests, eg, Peto-Prentice-Wilcoxon Test. Alternatively, one may specify a robust Test as the primary Test, which can capture various patterns of difference between 2 event time distributions. However, most of those Tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary Test. Such incoherence in the "Test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent Test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified Test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the Test is dramatically more powerful than the Logrank, Wilcoxon Tests, and the restricted mean survival time-based Test with a fixed τ, for the patterns of difference seen in these cancer clinical trials.
Angel M Cronin - One of the best experts on this subject based on the ideXlab platform.
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a flexible and coherent Test estimation procedure based on restricted mean survival times for censored time to event data in randomized clinical trials
Statistics in Medicine, 2018Co-Authors: Miki Horiguchi, Angel M Cronin, Masahiro TakeuchiAbstract:: In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the Logrank Test is prespecified as the primary Test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the Logrank Test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted Logrank Tests, eg, Peto-Prentice-Wilcoxon Test. Alternatively, one may specify a robust Test as the primary Test, which can capture various patterns of difference between 2 event time distributions. However, most of those Tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary Test. Such incoherence in the "Test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent Test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified Test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the Test is dramatically more powerful than the Logrank, Wilcoxon Tests, and the restricted mean survival time-based Test with a fixed τ, for the patterns of difference seen in these cancer clinical trials.
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A flexible and coherent Test/estimation procedure based on restricted mean survival times for censored time-to-event data in randomized clinical trials.
Statistics in medicine, 2018Co-Authors: Miki Horiguchi, Angel M Cronin, Masahiro Takeuchi, Hajime UnoAbstract:In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the Logrank Test is prespecified as the primary Test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the Logrank Test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted Logrank Tests, eg, Peto-Prentice-Wilcoxon Test. Alternatively, one may specify a robust Test as the primary Test, which can capture various patterns of difference between 2 event time distributions. However, most of those Tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary Test. Such incoherence in the "Test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent Test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified Test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the Test is dramatically more powerful than the Logrank, Wilcoxon Tests, and the restricted mean survival time-based Test with a fixed τ, for the patterns of difference seen in these cancer clinical trials.
