Generalized Pairwise Comparisons for Survival Analysis
The Net Benefit and the Win Ratio are the effect measures used in clinical trials with survival endpoints such as oncology and cardiology. These measures are based on generalized pairwise comparisons. In a randomized trial, the statistical methods estimate the ‘win’ probability that a subject random...
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| Published in | Journal of the Japan Statistical Society, Japanese Issue Vol. 52; no. 2; pp. 319 - 354 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | Japanese |
| Published |
Japan Statistical Society
01.03.2023
一般社団法人 日本統計学会 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0389-5602 2189-1478 |
| DOI | 10.11329/jjssj.52.319 |
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| Abstract | The Net Benefit and the Win Ratio are the effect measures used in clinical trials with survival endpoints such as oncology and cardiology. These measures are based on generalized pairwise comparisons. In a randomized trial, the statistical methods estimate the ‘win’ probability that a subject randomly selected from the new treatment group has a better outcome than a subject from the control group and the ‘loss’ probability in the opposite situation. The Net Benefit is the difference between these probabilities, and the Win Ratio is the ratio between them. In this study, we review several estimators of the win/loss probability in terms of generalized pairwise comparisons, and the variance of those estimators based on U-statistic theory. Especially, we explain how to deal with the censored data to estimate those probabilities. Finally, we illustrate using the actual data to implement those statistical methods by R-packages. |
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| AbstractList | The Net Benefit and the Win Ratio are the effect measures used in clinical trials with survival endpoints such as oncology and cardiology. These measures are based on generalized pairwise comparisons. In a randomized trial, the statistical methods estimate the ‘win’ probability that a subject randomly selected from the new treatment group has a better outcome than a subject from the control group and the ‘loss’ probability in the opposite situation. The Net Benefit is the difference between these probabilities, and the Win Ratio is the ratio between them. In this study, we review several estimators of the win/loss probability in terms of generalized pairwise comparisons, and the variance of those estimators based on U-statistic theory. Especially, we explain how to deal with the censored data to estimate those probabilities. Finally, we illustrate using the actual data to implement those statistical methods by R-packages. The Net Benefit and the Win Ratio are the effect measures used in clinical trials with survival endpoints such as oncology and cardiology. These measures are based on generalized pairwise comparisons. In a randomized trial, the statistical methods estimate the ‘win’ probability that a subject randomly selected from the new treatment group has a better outcome than a subject from the control group and the ‘loss’ probability in the opposite situation. The Net Benefit is the difference between these probabilities, and the Win Ratio is the ratio between them. In this study, we review several estimators of the win/loss probability in terms of generalized pairwise comparisons, and the variance of those estimators based on U-statistic theory. Especially, we explain how to deal with the censored data to estimate those probabilities. Finally, we illustrate using the actual data to implement those statistical methods by R-packages. 生存時間を評価項目とするがん領域や循環器領域の医学系研究で，治療効果の指標としてNet BenefitやWin Ratioが利用されている．これらは一般化ペアワイズ比較に基づく指標として整理できる．一般化ペアワイズ比較では，新治療と標準治療を比較するランダム化比較試験の場合，各群から1人ずつをランダムに選んでできるペアに対する勝ち負けの確率を評価する．このとき，評価項目の大小関係に基づく様々な勝ち負けのルールを考えることができる．Net Benefitは勝ち負けの確率の差，Win Ratioは比として定義される指標である．本稿では，勝ち負けの確率，Net BenefitとWin Ratioの推定方法を一般化ペアワイズ比較の観点から整理し，U統計量理論から導かれる漸近分散を説明する．また，打ち切りを含む生存時間における推定の問題と対処方法を説明する．最後に，Rパッケージによる実装方法を例示する． |
| Author | Sakamaki, Kentaro Fukuda, Musashi Oba, Koji |
| Author_FL | 福田 武蔵 坂巻 顕太郎 大庭 幸治 |
| Author_FL_xml | – sequence: 1 fullname: 福田 武蔵 – sequence: 2 fullname: 坂巻 顕太郎 – sequence: 3 fullname: 大庭 幸治 |
| Author_xml | – sequence: 1 fullname: Fukuda, Musashi – sequence: 1 fullname: Oba, Koji – sequence: 1 fullname: Sakamaki, Kentaro |
| BackLink | https://cir.nii.ac.jp/crid/1390013795251461376$$DView record in CiNii |
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| ContentType | Journal Article |
| Copyright | 2023 Japan Statistical Society |
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| DOI | 10.11329/jjssj.52.319 |
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| Discipline | Statistics |
| DocumentTitleAlternate | 一般化ペアワイズ比較による生存時間解析 |
| DocumentTitle_FL | 一般化ペアワイズ比較による生存時間解析 |
| EISSN | 2189-1478 |
| EndPage | 354 |
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| PublicationTitle | Journal of the Japan Statistical Society, Japanese Issue |
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| PublicationTitle_FL | 日本統計学会和文誌 Journal of the Japan Statistical Society, Japanese Issue 日本統計学会誌 Journal of the Japan Statistical Society |
| PublicationYear | 2023 |
| Publisher | Japan Statistical Society 一般社団法人 日本統計学会 |
| Publisher_xml | – name: Japan Statistical Society – name: 一般社団法人 日本統計学会 |
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| Title | Generalized Pairwise Comparisons for Survival Analysis |
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